@Article{info:doi/10.2196/65889, author="Burch, E. Kathleen and Tryon, L. Valerie and Pierce, M. Katherine and Tully, M. Laura and Ereshefsky, Sabrina and Savill, Mark and Smith, Leigh and Wilcox, B. Adam and Hakusui, Komei Christopher and Padilla, E. Viviana and McNamara, P. Amanda and Kado-Walton, Merissa and Padovani, J. Andrew and Miller, Chelyah and Miles, J. Madison and Sharma, Nitasha and Nguyen, H. Khanh Linh and Zhang, Yi and Niendam, A. Tara", title="Co-Designing a Web-Based and Tablet App to Evaluate Clinical Outcomes of Early Psychosis Service Users in a Learning Health Care Network: User-Centered Design Workshop and Pilot Study", journal="JMIR Hum Factors", year="2025", month="Apr", day="9", volume="12", pages="e65889", keywords="eHealth", keywords="user-centered design", keywords="learning health system", keywords="psychosis", keywords="early psychosis", keywords="user-driven development", keywords="web-based", keywords="data visualization", keywords="surveys and questionnaires", keywords="measurement-based care", abstract="Background: The Early Psychosis Intervention Network of California project, a learning health care network of California early psychosis intervention (EPI) programs, prioritized incorporation of community partner feedback while designing its eHealth app, Beehive. Though eHealth apps can support learning health care network data collection aims, low user acceptance or adoption can pose barriers to successful implementation. Adopting user-centered design (UCD) approaches, such as incorporation of user feedback, prototyping, iterative design, and continuous evaluation, can mitigate these potential barriers. Objective: We aimed to use UCD during development of a data collection and data visualization web-based and tablet app, Beehive, to promote engagement with Beehive as part of standard EPI care across a diverse user-base. Methods: Our UCD approach included incorporation of user feedback, prototyping, iterative design, and continuous evaluation. This started with user journey mapping to create storyboards, which were then presented in UCD workshops with service users, their support persons, and EPI providers. We incorporated feedback from these workshops into the alpha version of Beehive, which was also presented in a UCD workshop. Feedback was again incorporated into the beta version of Beehive. We provided Beehive training to 4 EPI programs who then piloted Beehive's beta version. During piloting, service users, their support persons, and EPI program providers completed Beehive surveys at enrollment and every 6 months after treatment initiation. To examine preliminary user acceptance and adoption during the piloting phase, we assessed rates of participant enrollment and survey completion, with a particular focus on completion of a prioritized survey: the Modified Colorado Symptom Index. Results: UCD workshop feedback resulted in the creation of new workflows and interface changes in Beehive to improve the user experience. During piloting, 48 service users, 42 support persons, and 72 EPI program providers enrolled in Beehive. Data were available for 88\% (n=42) of service users, including self-reported data for 79\% (n=38), collateral-reported data for 42\% (n=20), and clinician-entered data for 17\% (n=8). The Modified Colorado Symptom Index was completed by 54\% (n=26) of service users (total score: mean 24.16, SD 16.81). In addition, 35 service users had a support person who could complete the Modified Colorado Symptom Index, and 56\% (n=19) of support persons completed it (mean 26.71, SD 14.43). Conclusions: Implementing UCD principles while developing the Beehive app resulted in early workflow changes and produced an app that was acceptable and feasible for collection of self-reported clinical outcomes data from service users. Additional support is needed to increase collateral-reported and clinician-entered data. ", doi="10.2196/65889", url="https://humanfactors.jmir.org/2025/1/e65889" } @Article{info:doi/10.2196/63405, author="Spark, Jessica and Rowe, Elise and Alvarez-Jimenez, Mario and Bell, Imogen and Byrne, Linda and Dzafic, Ilvana and Ellinghaus, Carli and Lavoie, Suzie and Lum, Jarrad and McLean, Brooke and Thomas, Neil and Thompson, Andrew and Wadley, Greg and Whitford, Thomas and Wood, Stephen and Yuen, Pan Hok and Nelson, Barnaby", title="Integrating Virtual Reality, Neurofeedback, and Cognitive Behavioral Therapy for Auditory Verbal Hallucinations (Hybrid): Protocol of a Pilot, Unblinded, Single-Arm Interventional Study", journal="JMIR Res Protoc", year="2025", month="Apr", day="1", volume="14", pages="e63405", keywords="psychosis", keywords="first episode psychosis", keywords="schizophrenia", keywords="virtual reality", keywords="neurofeedback", keywords="EEG", keywords="auditory verbal hallucinations", keywords="voices", keywords="cognitive behavior therapy", keywords="youth mental health", keywords="pilot study", keywords="paracusias", keywords="paracusis", keywords="treatment", keywords="medication", keywords="psychotic disorder", keywords="efficacy", keywords="neuroscience", keywords="psychology", keywords="hybrid", keywords="adolescent", keywords="Australia", abstract="Background: Current treatments for schizophrenia and other psychotic disorders have limited efficacy, with high rates of nonresponse to ``gold standard'' treatments. New approaches are therefore urgently required. Objective: The aims of this pilot study are to investigate the feasibility, acceptability, safety, and usability of Hybrid treatment (primary aim); and to explore Hybrid's treatment efficacy and engagement of treatment targets (secondary aim). The primary aim will be assessed via face-to-face user experience surveys on a (self-assessed) 5-point Likert scale (and qualitative open-ended questions) examining: (1) acceptability, (2) helpfulness, (3) engagement, and (4) perceived safety. We will also examine consent and completion rates, and the number of sessions attended. Our threshold for moving on to efficacy trials will be at least 70\% of our participants to rate 3 and above (which corresponds to agree or strongly agree) that the intervention package was acceptable, feasible, and safe. The secondary aims will be assessed by observing whether individuals achieve self-directed modulation of high-$\beta$ neurophysiological activity (neural target) and progression upwards through the VR-based exposure hierarchy (psychological target), and by assessing symptom change scores. This study developed a new treatment approach for auditory verbal hallucinations, a major symptom of psychotic disorders, that integrates advances in psychological therapy (cognitive behavioral therapy for psychosis), technology (virtual reality, VR), and neuroscience (electroencephalography-based neurofeedback). Methods: Hybrid takes a ``symptom capture'' approach using individually tailored VR-based exposure exercises. Participants (N=10) will receive the intervention package weekly over 12 face-to-face sessions. Here, participants will be progressively exposed to symptom triggers and develop methods of downregulating neural activity associated with these symptoms (neurofeedback component) while concurrently receiving clinician-delivered cognitive behavioral therapy for psychosis. Results: As of February 2025, Hybrid has commenced (unblinded) recruitment activities from Orygen clinical services in Northwestern Melbourne, Australia. A total of 75 individuals have been approached and 64 individuals have been prescreened (41 individuals were deemed eligible, 15 individuals were ineligible, and 8 individuals declined or did not respond to contact attempts) and 5 individuals have been included in the study. Of the 5 individuals who have commenced the Hybrid treatment, 4 are actively engaged in the program and 1 individual has withdrawn. We expect recruitment to conclude in July 2025 and for the results to be published in 2026. Conclusions: The Hybrid study is piloting a novel approach that has the potential to address the shortcomings of current treatments for psychotic symptoms. If there is favorable evidence for the acceptability, feasibility, safety and usability of Hybrid, the study team will move on to efficacy trials. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12624000357550; https://tinyurl.com/24ey8hpy International Registered Report Identifier (IRRID): PRR1-10.2196/63405 ", doi="10.2196/63405", url="https://www.researchprotocols.org/2025/1/e63405" } @Article{info:doi/10.2196/68362, author="Zhang, Xiaolong and Berry, Natalie and Di Basilio, Daniela and Richardson, Cara and Eisner, Emily and Bucci, Sandra", title="Mental Health Professionals' Technology Usage and Attitudes Toward Digital Health for Psychosis: Comparative Cross-Sectional Survey Study", journal="JMIR Ment Health", year="2025", month="Mar", day="31", volume="12", pages="e68362", keywords="digital mental health", keywords="psychosis", keywords="attitudes", keywords="implementation", keywords="smartphone app", abstract="Background: Digital health technologies (DHTs) for psychosis have been developed and tested rapidly in recent years. However, research examining mental health professionals' views on the use of DHTs for people with psychosis is limited. Given the increased accessibility and availability of DHTs for psychosis, an up-to-date understanding of staff perception of DHTs for psychosis is warranted. Objective: In this study, we aimed to investigate mental health professionals' usage of technology and their perception of service users' technology usage; their views toward the use of DHTs for psychosis, including their concerns; and barriers for implementing DHTs in a mental health setting. Methods: Two cross-sectional surveys were distributed to mental health care staff who had experience of working with individuals experiencing psychosis in the United Kingdom. Survey 1 (from April 2018 to September 2020) was distributed to 3 local UK National Health Service (NHS) trusts in Northwest England; survey 2 was administered nationally across 31 UK NHS trusts or health boards (from November 2022 to March 2024). The COVID-19 pandemic occurred between the 2 survey periods. Data were analyzed descriptively. Results: A total of 155 and 352 participants completed surveys 1 and 2, respectively. Staff reported high levels of technology ownership and usage in both surveys. In general, staff expressed positive views regarding the use of DHTs for psychosis; however, barriers and concerns, including affordability, digital literacy, and potential negative effects on service users' mental health, were also reported. We did not find notable changes in terms of staff use of digital technology in clinical practice over time. Conclusions: Staff sampled from a broad and diverse range expressed consistent optimism about the potential implementation of DHTs in practice, though they also noted some concerns regarding safety and access. While the COVID-19 pandemic is frequently regarded as a catalyst for the adoption of digital health care tools, the sustainability of this transition from traditional to digital health care appeared to be suboptimal. To address staff concerns regarding safety and potentially facilitate the implementation of DHTs, systematic evaluation of adverse effects of using DHTs and dissemination of evidence are needed. Organizational support and training should be offered to staff to help address barriers and increase confidence in recommending and using DHTs with service users. ", doi="10.2196/68362", url="https://mental.jmir.org/2025/1/e68362" } @Article{info:doi/10.2196/69820, author="Waaler, Niklas Per and Hussain, Musarrat and Molchanov, Igor and Bongo, Ailo Lars and Elvev{\aa}g, Brita", title="Prompt Engineering an Informational Chatbot for Education on Mental Health Using a Multiagent Approach for Enhanced Compliance With Prompt Instructions: Algorithm Development and Validation", journal="JMIR AI", year="2025", month="Mar", day="26", volume="4", pages="e69820", keywords="schizophrenia", keywords="mental health", keywords="prompt engineering", keywords="AI in health care", keywords="AI safety", keywords="self-reflection", keywords="limiting scope of AI", keywords="large language model", keywords="LLM", keywords="GPT-4", keywords="AI transparency", keywords="adaptive learning", abstract="Background: People with schizophrenia often present with cognitive impairments that may hinder their ability to learn about their condition. Education platforms powered by large language models (LLMs) have the potential to improve the accessibility of mental health information. However, the black-box nature of LLMs raises ethical and safety concerns regarding the controllability of chatbots. In particular, prompt-engineered chatbots may drift from their intended role as the conversation progresses and become more prone to hallucinations. Objective: This study aimed to develop and evaluate a critical analysis filter (CAF) system that ensures that an LLM-powered prompt-engineered chatbot reliably complies with its predefined instructions and scope while delivering validated mental health information. Methods: For a proof of concept, we prompt engineered an educational chatbot for schizophrenia powered by GPT-4 that could dynamically access information from a schizophrenia manual written for people with schizophrenia and their caregivers. In the CAF, a team of prompt-engineered LLM agents was used to critically analyze and refine the chatbot's responses and deliver real-time feedback to the chatbot. To assess the ability of the CAF to re-establish the chatbot's adherence to its instructions, we generated 3 conversations (by conversing with the chatbot with the CAF disabled) wherein the chatbot started to drift from its instructions toward various unintended roles. We used these checkpoint conversations to initialize automated conversations between the chatbot and adversarial chatbots designed to entice it toward unintended roles. Conversations were repeatedly sampled with the CAF enabled and disabled. In total, 3 human raters independently rated each chatbot response according to criteria developed to measure the chatbot's integrity, specifically, its transparency (such as admitting when a statement lacked explicit support from its scripted sources) and its tendency to faithfully convey the scripted information in the schizophrenia manual. Results: In total, 36 responses (3 different checkpoint conversations, 3 conversations per checkpoint, and 4 adversarial queries per conversation) were rated for compliance with the CAF enabled and disabled. Activating the CAF resulted in a compliance score that was considered acceptable (?2) in 81\% (7/36) of the responses, compared to only 8.3\% (3/36) when the CAF was deactivated. Conclusions: Although more rigorous testing in realistic scenarios is needed, our results suggest that self-reflection mechanisms could enable LLMs to be used effectively and safely in educational mental health platforms. This approach harnesses the flexibility of LLMs while reliably constraining their scope to appropriate and accurate interactions. ", doi="10.2196/69820", url="https://ai.jmir.org/2025/1/e69820", url="http://www.ncbi.nlm.nih.gov/pubmed/39992720" } @Article{info:doi/10.2196/65632, author="Harvey, Daisy and Rayson, Paul and Lobban, Fiona and Palmier-Claus, Jasper and Dolman, Clare and Chataign{\'e}, Anne and Jones, Steven", title="Using Natural Language Processing Methods to Build the Hypersexuality in Bipolar Reddit Corpus: Infodemiology Study of Reddit", journal="JMIR Infodemiology", year="2025", month="Mar", day="6", volume="5", pages="e65632", keywords="bipolar", keywords="hypersexuality", keywords="natural language processing", keywords="Linguistic Inquiry and Word Count", keywords="LIWC", keywords="BERTopic", keywords="topic modeling", keywords="computational linguistics", abstract="Background: Bipolar is a severe mental health condition affecting at least 2\% of the global population, with clinical observations suggesting that individuals experiencing elevated mood states, such as mania or hypomania, may have an increased propensity for engaging in risk-taking behaviors, including hypersexuality. Hypersexuality has historically been stigmatized in society and in health care provision, which makes it more difficult for service users to talk about their behaviors. There is a need for greater understanding of hypersexuality to develop better evidence-based treatment, support, and training for health professionals. Objective: This study aimed to develop and assess effective methodologies for identifying posts on Reddit related to hypersexuality posted by people with a self-reported bipolar diagnosis. Using natural language processing techniques, this research presents a specialized dataset, the Talking About Bipolar on Reddit Corpus (TABoRC). We used various computational tools to filter and categorize posts that mentioned hypersexuality, forming the Hypersexuality in Bipolar Reddit Corpus (HiB-RC). This paper introduces a novel methodology for detecting hypersexuality-related conversations on Reddit and offers both methodological insights and preliminary findings, laying the groundwork for further research in this emerging field. Methods: A toolbox of computational linguistic methods was used to create the corpora and infer demographic variables for the Redditors in the dataset. The key psychological domains in the corpus were measured using Linguistic Inquiry and Word Count, and a topic model was built using BERTopic to identify salient language clusters. This paper also discusses ethical considerations associated with this type of analysis. Results: The TABoRC is a corpus of 6,679,485 posts from 5177 Redditors, and the HiB-RC is a corpus totaling 2146 posts from 816 Redditors. The results demonstrate that, between 2012 and 2021, there was a 91.65\% average yearly increase in posts in the HiB-RC (SD 119.6\%) compared to 48.14\% in the TABoRC (SD 51.2\%) and an 86.97\% average yearly increase in users (SD 93.8\%) compared to 27.17\% in the TABoRC (SD 38.7\%). These statistics suggest that there was an increase in posting activity related to hypersexuality that exceeded the increase in general Reddit use over the same period. Several key psychological domains were identified as significant in the HiB-RC (P<.001), including more negative tone, more discussion of sex, and less discussion of wellness compared to the TABoRC. Finally, BERTopic was used to identify 9 key topics from the dataset. Conclusions: Hypersexuality is an important symptom that is discussed by people with bipolar on Reddit and needs to be systematically recognized as a symptom of this illness. This research demonstrates the utility of a computational linguistic framework and offers a high-level overview of hypersexuality in bipolar, providing empirical evidence that paves the way for a deeper understanding of hypersexuality from a lived experience perspective. ", doi="10.2196/65632", url="https://infodemiology.jmir.org/2025/1/e65632", url="http://www.ncbi.nlm.nih.gov/pubmed/40053804" } @Article{info:doi/10.2196/68251, author="Kimhy, David and Ospina, H. Luz and Wall, Melanie and Alschuler, M. Daniel and Jarskog, F. Lars and Ballon, S. Jacob and McEvoy, Joseph and Bartels, N. Matthew and Buchsbaum, Richard and Goodman, Marianne and Miller, A. Sloane and Stroup, Scott T.", title="Telehealth-Based vs In-Person Aerobic Exercise in Individuals With Schizophrenia: Comparative Analysis of Feasibility, Safety, and Efficacy", journal="JMIR Ment Health", year="2025", month="Feb", day="14", volume="12", pages="e68251", keywords="schizophrenia", keywords="psychosis", keywords="exercise", keywords="aerobic fitness", keywords="VO2max", keywords="telehealth", keywords="telemedicine", keywords="COVID-19", keywords="clinical trial", keywords="safety", keywords="maximum oxygen consumption", abstract="Background: Aerobic exercise (AE) training has been shown to enhance aerobic fitness in people with schizophrenia. Traditionally, such training has been administered in person at gyms or other communal exercise spaces. However, following the advent of the COVID-19 pandemic, many clinics transitioned their services to telehealth-based delivery. Yet, at present, there is scarce information about the feasibility, safety, and efficacy of telehealth-based AE in this population. Objective: To examine the feasibility, safety, and efficacy of trainer-led, at-home, telehealth-based AE in individuals with schizophrenia. Methods: We analyzed data from the AE arm (n=37) of a single-blind, randomized clinical trial examining the impact of a 12-week AE intervention in people with schizophrenia. Following the onset of the COVID-19 pandemic, the AE trial intervention transitioned from in-person to at-home, telehealth-based delivery of AE, with the training frequency and duration remaining identical. We compared the feasibility, safety, and efficacy of the delivery of trainer-led AE training among participants undergoing in-person (pre--COVID-19; n=23) versus at-home telehealth AE (post--COVID-19; n=14). Results: The telehealth and in-person participants attended a similar number of exercise sessions across the 12-week interventions (26.8, SD 10.2 vs 26.1, SD 9.7, respectively; P=.84) and had similar number of weeks with at least 1 exercise session (10.4, SD 3.4 vs 10.6, SD 3.1, respectively; P=.79). The telehealth-based AE was associated with a significantly lower drop-out rate (telehealth: 0/14, 0\%; in-person: 7/23, 30.4\%; P=.04). There were no significant group differences in total time spent exercising (telehealth: 1246, SD 686 min; in-person: 1494, SD 580 min; P=.28); however, over the 12-week intervention, the telehealth group had a significantly lower proportion of session-time exercising at or above target intensity (telehealth: 33.3\%, SD 21.4\%; in-person: 63.5\%, SD 16.3\%; P<.001). There were no AE-related serious adverse events associated with either AE delivery format. Similarly, there were no significant differences in the percentage of participants experiencing minor or moderate adverse events, such as muscle soreness, joint pain, blisters, or dyspnea (telehealth: 3/14, 21\%; in-person: 5/19, 26\%; P>.99) or in the percentage of weeks per participant with at least 1 exercise-related adverse event (telehealth: 31\%, SD 33\%; in-person: 40\%, SD 33\%; P=.44). There were no significant differences between the telehealth versus in-person groups regarding changes in aerobic fitness as indexed by maximum oxygen consumption (VO2max; P=.27). Conclusions: Our findings provide preliminary support for the delivery of telehealth-based AE for individuals with schizophrenia. Our results indicate that in-home telehealth-based AE is feasible and safe in this population, although when available, in-person AE appears preferable given the opportunity for social interactions and the higher intensity of exercises. We discuss the findings' clinical implications, specifically within the context of the COVID-19 pandemic, as well as review potential challenges for the implementation of telehealth-based AE among people with schizophrenia. ", doi="10.2196/68251", url="https://mental.jmir.org/2025/1/e68251" } @Article{info:doi/10.2196/56185, author="Yang, Zixu and Heaukulani, Creighton and Sim, Amelia and Buddhika, Thisum and Abdul Rashid, Amirah Nur and Wang, Xuancong and Zheng, Shushan and Quek, Feng Yue and Basu, Sutapa and Lee, Wei Kok and Tang, Charmaine and Verma, Swapna and Morris, T. Robert J. and Lee, Jimmy", title="Utility of Digital Phenotyping Based on Wrist Wearables and Smartphones in Psychosis: Observational Study", journal="JMIR Mhealth Uhealth", year="2025", month="Feb", day="5", volume="13", pages="e56185", keywords="schizophrenia", keywords="psychosis", keywords="digital phenotyping", keywords="wrist wearables", keywords="mobile phone", abstract="Background: Digital phenotyping provides insights into an individual's digital behaviors and has potential clinical utility. Objective: In this observational study, we explored digital biomarkers collected from wrist-wearable devices and smartphones and their associations with clinical symptoms and functioning in patients with schizophrenia. Methods: We recruited 100 outpatients with schizophrenia spectrum disorder, and we collected various digital data from commercially available wrist wearables and smartphones over a 6-month period. In this report, we analyzed the first week of digital data on heart rate, sleep, and physical activity from the wrist wearables and travel distance, sociability, touchscreen tapping speed, and screen time from the smartphones. We analyzed the relationships between these digital measures and patient baseline measurements of clinical symptoms assessed with the Positive and Negative Syndrome Scale, Brief Negative Symptoms Scale, and Calgary Depression Scale for Schizophrenia, as well as functioning as assessed with the Social and Occupational Functioning Assessment Scale. Linear regression was performed for each digital and clinical measure independently, with the digital measures being treated as predictors. Results: Digital data were successfully collected from both the wearables and smartphones throughout the study, with 91\% of the total possible data successfully collected from the wearables and 82\% from the smartphones during the first week of the trial---the period under analysis in this report. Among the clinical outcomes, negative symptoms were associated with the greatest number of digital measures (10 of the 12 studied here), followed by overall measures of psychopathology symptoms, functioning, and positive symptoms, which were each associated with at least 3 digital measures. Cognition and cognitive/disorganization symptoms were each associated with 1 or 2 digital measures. Conclusions: We found significant associations between nearly all digital measures and a wide range of symptoms and functioning in a community sample of individuals with schizophrenia. These findings provide insights into the digital behaviors of individuals with schizophrenia and highlight the potential of using commercially available wrist wearables and smartphones for passive monitoring in schizophrenia. International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2020-046552 ", doi="10.2196/56185", url="https://mhealth.jmir.org/2025/1/e56185" } @Article{info:doi/10.2196/66330, author="Choomung, Pichsinee and He, Yupeng and Matsunaga, Masaaki and Sakuma, Kenji and Kishi, Taro and Li, Yuanying and Tanihara, Shinichi and Iwata, Nakao and Ota, Atsuhiko", title="Estimating the Prevalence of Schizophrenia in the General Population of Japan Using an Artificial Neural Network--Based Schizophrenia Classifier: Web-Based Cross-Sectional Survey", journal="JMIR Form Res", year="2025", month="Jan", day="29", volume="9", pages="e66330", keywords="schizophrenia", keywords="schizophrenic", keywords="prevalence", keywords="artificial neural network", keywords="neural network", keywords="neural networks", keywords="ANN", keywords="deep learning", keywords="machine learning", keywords="SZ classifier", keywords="web-based survey", keywords="epidemiology", keywords="epidemiological", keywords="Japan", keywords="classifiers", keywords="mental illness", keywords="mental disorder", keywords="mental health", abstract="Background: Estimating the prevalence of schizophrenia in the general population remains a challenge worldwide, as well as in Japan. Few studies have estimated schizophrenia prevalence in the Japanese population and have often relied on reports from hospitals and self-reported physician diagnoses or typical schizophrenia symptoms. These approaches are likely to underestimate the true prevalence owing to stigma, poor insight, or lack of access to health care among respondents. To address these issues, we previously developed an artificial neural network (ANN)--based schizophrenia classification model (SZ classifier) using data from a large-scale Japanese web-based survey to enhance the comprehensiveness of schizophrenia case identification in the general population. In addition, we also plan to introduce a population-based survey to collect general information and sample participants matching the population's demographic structure, thereby achieving a precise estimate of the prevalence of schizophrenia in Japan. Objective: This study aimed to estimate the prevalence of schizophrenia by applying the SZ classifier to random samples from the Japanese population. Methods: We randomly selected a sample of 750 participants where the age, sex, and regional distributions were similar to Japan's demographic structure from a large-scale Japanese web-based survey. Demographic data, health-related backgrounds, physical comorbidities, psychiatric comorbidities, and social comorbidities were collected and applied to the SZ classifier, as this information was also used for developing the SZ classifier. The crude prevalence of schizophrenia was calculated through the proportion of positive cases detected by the SZ classifier. The crude estimate was further refined by excluding false-positive cases and including false-negative cases to determine the actual prevalence of schizophrenia. Results: Out of 750 participants, 62 were classified as schizophrenia cases by the SZ classifier, resulting in a crude prevalence of schizophrenia in the general population of Japan of 8.3\% (95\% CI 6.6\%-10.1\%). Among these 62 cases, 53 were presumed to be false positives, and 3 were presumed to be false negatives. After adjustment, the actual prevalence of schizophrenia in the general population was estimated to be 1.6\% (95\% CI 0.7\%-2.5\%). Conclusions: This estimated prevalence was slightly higher than that reported in previous studies, possibly due to a more comprehensive disease classification methodology or, conversely, model limitations. This study demonstrates the capability of an ANN-based model to improve the estimation of schizophrenia prevalence in the general population, offering a novel approach to public health analysis. ", doi="10.2196/66330", url="https://formative.jmir.org/2025/1/e66330" } @Article{info:doi/10.2196/64959, author="Snipes, Cassandra and Dorner?Ciossek, Cornelia and Hare, D. Brendan and Besedina, Olya and Campellone, Tim and Petrova, Mariya and Lakhan, E. Shaheen and Pratap, Abhishek", title="Establishment and Maintenance of a Digital Therapeutic Alliance in People Living With Negative Symptoms of Schizophrenia: Two Exploratory Single-Arm Studies", journal="JMIR Ment Health", year="2025", month="Jan", day="27", volume="12", pages="e64959", keywords="therapeutic alliance", keywords="digital working alliance", keywords="experiential negative symptoms", keywords="schizophrenia", keywords="digital therapeutics", keywords="digital literacy", abstract="Background: Evidence-based digital therapeutics represent a new treatment modality in mental health, potentially providing cost-efficient, accessible means of augmenting existing treatments for chronic mental illnesses. CT-155/BI 3972080 is a prescription digital therapeutic under development as an adjunct to standard of care treatments for patients 18 years of age and older with experiential negative symptoms (ENS) of schizophrenia. Individual components of CT-155/BI 3972080 are designed based on the underlying principles of face-to-face treatment. A positive therapeutic alliance between patients and health care providers is linked with improved clinical outcomes in mental health. Likewise, establishing a similar therapeutic alliance with a digital therapeutic (ie, digital working alliance [DWA]) may be important for engagement and treatment effectiveness of this modality. Objective: This study aimed to investigate the establishment and maintenance of a DWA between a beta version of CT-155/BI 3972080 (CT-155 beta) and adults with ENS of schizophrenia. Methods: Two multicenter, exploratory, single-arm studies (study 1: CT-155-C-001 and study 2: CT-155-C-002) enrolled adults with schizophrenia and ENS receiving stable antipsychotic medication (?12 weeks). Participants had access to CT-155 beta and were presented with daily in-app activities during a 3-week orientation phase that included lessons designed to facilitate building of a DWA. In study 2, the 3-week orientation phase was followed by an abbreviated active 4-week phase. Digital literacy at baseline was evaluated using the Mobile Device Proficiency Questionnaire (MDPQ). The mobile Agnew Relationship Measure (mARM) was used to assess DWA establishment after 3 weeks in both studies, and after 7 weeks in study 2 to assess DWA maintenance. Participant safety, digital literacy, and correlations between negative symptom severity and DWA were assessed in both studies. Results: Of the enrolled participants, 94\% (46/49) and 86\% (43/50) completed studies 1 and 2, respectively. Most were male (study 1: 71\%, 35/49; study 2: 80\%, 40/50). The baseline digital literacy assessed through MDPQ score was comparable in both studies (study 1: mean 30.56, SD 8.06; study 2: mean 28.69, SD 8.31) indicating proficiency in mobile device use. After 3 weeks, mARM scores (study 1: mean 5.16, SD 0.8; study 2: mean 5.36, SD 1.06) indicated that a positive DWA was established in both studies. In study 2, the positive DWA established at week 3 was maintained at week 7 (mARM: mean 5.48, SD 0.97). There were no adverse events (AEs) in study 1, and 3 nonserious and nontreatment-related AEs in study 2. Conclusions: A positive DWA was established between participants and CT-155 beta within 3 weeks. The second 7-week study showed maintenance of the DWA to the end of the study. Results support the establishment and maintenance of a DWA between adults with ENS of schizophrenia and a beta version of CT-155/BI 3972080, a prescription digital therapeutic under development to target these symptoms. Trial Registration: Clinicaltrials.gov NCT05486312; https://clinicaltrials.gov/study/NCT05486312 ", doi="10.2196/64959", url="https://mental.jmir.org/2025/1/e64959" } @Article{info:doi/10.2196/66925, author="Tay, Ling Jing and Qu, Yuanrong and Lim, Lucas and Puthran, Rohan and Tan, Robert Chye Lee and Rajendran, Rajkirren and Wei, Chiah Ker and Xie, Huiting and Sim, Kang", title="Impact of a Virtual Reality Intervention on Stigma, Empathy, and Attitudes Toward Patients With Psychotic Disorders Among Mental Health Care Professionals: Randomized Controlled Trial", journal="JMIR Ment Health", year="2025", month="Jan", day="21", volume="12", pages="e66925", keywords="virtual reality", keywords="social distance", keywords="stigma", keywords="empathy", keywords="mental health", keywords="schizophrenia", keywords="psychosis", keywords="psychotic disorder", keywords="mental disorder", keywords="healthcare professional", keywords="VR", keywords="randomized controlled trial", keywords="RCT", keywords="user satisfaction", abstract="Background: Previous studies have found that psychotic disorders are among the most stigmatized mental disorders. Of note, virtual reality (VR) interventions have been associated with improvements in attitudes and empathy and reduced stigma toward individuals with psychotic disorders, especially among undergraduates, but this has not been examined among mental health care professionals. Objective: We aimed to evaluate the effectiveness of a newly developed VR intervention for mental health care professionals to improve attitudes and empathy and reduce stigma toward people with psychotic disorders. Methods: We conducted a randomized controlled trial and recruited eligible mental health care professionals from a tertiary mental health care institution. Both arms (VR intervention and VR control groups) were evaluated at baseline, postintervention, and 1-month follow up. The evaluation included outcomes related to attitudes (modified attitudes toward people with schizophrenia scale), stigma (social distance scale, personal stigma scale), and empathy (empathetic concern subscale of the Interpersonal Reactivity Index). The experience with the VR intervention was assessed using a user satisfaction questionnaire, and qualitative feedback was gathered. Results: Overall, 180 mental health care professionals participated and completed the study. Both groups showed improvements in attitude, social distance, and stigma scores but not the empathy score following the intervention. The VR intervention group had better user satisfaction than the VR control group. In addition, certain outcome measures were positively associated with specific factors including female gender, higher education level, certain job roles, years of work, and presence of loved ones with a mental disorder. Conclusions: Both the intervention and control VR groups of mental health care professionals showed improvements in attitudes, stigma, and social distance toward people with psychotic disorders. Future longitudinal studies may want to evaluate the impact of VR on caregivers and the public on these same and other outcome measures to reduce stigma and improve empathy toward individuals with psychotic disorders. Trial Registration: clinicaltrials.gov NCT05982548; https://clinicaltrials.gov/study/NCT05982548 ", doi="10.2196/66925", url="https://mental.jmir.org/2025/1/e66925" } @Article{info:doi/10.2196/65246, author="Eisner, Emily and Faulkner, Sophie and Allan, Stephanie and Ball, Hannah and Di Basilio, Daniela and Nicholas, Jennifer and Priyam, Aansha and Wilson, Paul and Zhang, Xiaolong and Bucci, Sandra", title="Barriers and Facilitators of User Engagement With Digital Mental Health Interventions for People With Psychosis or Bipolar Disorder: Systematic Review and Best-Fit Framework Synthesis", journal="JMIR Ment Health", year="2025", month="Jan", day="20", volume="12", pages="e65246", keywords="psychosis", keywords="bipolar", keywords="schizophrenia", keywords="smartphone", keywords="digital", keywords="wearable", keywords="mobile phone", keywords="PRISMA", abstract="Background: Digital mental health interventions (DMHIs) to monitor and improve the health of people with psychosis or bipolar disorder show promise; however, user engagement is variable, and integrated clinical use is low. Objective: This prospectively registered systematic review examined barriers and facilitators of clinician and patient engagement with DMHIs, to inform implementation within real-world settings. Methods: A systematic search of 7 databases identified empirical studies reporting qualitative or quantitative data about factors affecting staff or patient engagement with DMHIs aiming to monitor or improve the mental or physical health of people with psychosis or bipolar disorder. The Consolidated Framework for Implementation Research was used to synthesize data on barriers and facilitators, following a best-fit framework synthesis approach. Results: The review included 175 papers (150 studies; 11,446 participants) describing randomized controlled trials; surveys; qualitative interviews; and usability, cohort, and case studies. Samples included people with schizophrenia spectrum psychosis (98/150, 65.3\% of studies), bipolar disorder (62/150, 41.3\% of studies), and clinicians (26/150, 17.3\% of studies). Key facilitators were a strong recognition of DMHIs' relative advantages, a clear link between intervention focus and specific patient needs, a simple, low-effort digital interface, human-supported delivery, and device provision where needed. Although staff thought patients would lose, damage, or sell devices, reviewed studies found only 11\% device loss. Barriers included intervention complexity, perceived risks, user motivation, discomfort with self-reflection, digital poverty, symptoms of psychosis, poor compatibility with existing clinical workflows, staff and patient fears that DMHIs would replace traditional face-to-face care, infrastructure limitations, and limited financial support for delivery. Conclusions: Identified barriers and facilitators highlight key considerations for DMHI development and implementation. As to broader implications, sustainable business models are needed to ensure that evidence-based DMHIs are maintained and deployed. Trial Registration: PROSPERO CRD42021282871; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=282871 ", doi="10.2196/65246", url="https://mental.jmir.org/2025/1/e65246" } @Article{info:doi/10.2196/59540, author="Katsushima, Masayuki and Nakamura, Hideki and Shiko, Yuki and Hanaoka, Hideki and Shimizu, Eiji", title="Effectiveness of a Videoconference-Based Cognitive Behavioral Therapy Program for Patients with Schizophrenia: Pilot Randomized Controlled Trial", journal="JMIR Form Res", year="2025", month="Jan", day="14", volume="9", pages="e59540", keywords="schizophrenia", keywords="randomized controlled trial", keywords="cognitive behavioral therapy", keywords="videoconference", keywords="remote therapy", abstract="Background: Cognitive behavioral therapy for psychosis (CBTp) is not sufficiently widespread in clinical practice, although evidence has been presented. Objective: The purpose of this study was to explore whether one-on-one videoconference-based CBTp (vCBTp) is more effective than usual care (UC) alone for improving psychiatric symptoms in patients with schizophrenia attending outpatient clinics. Methods: In this exploratory randomized controlled trial, patients with schizophrenia and schizoaffective disorders who were still taking medication in an outpatient clinic were randomly assigned to either the vCBTp plus UC group (n=12) or the UC group (n=12). The vCBTp program was conducted once a week, with each session lasting for 50 minutes, for a total of 7 sessions conducted in real-time and in a one-on-one format remotely using a loaned tablet computer (iPad). The primary outcome was the Positive and Negative Syndrome Scale (PANSS) total score, which measures the difference in the mean change from baseline (week 0) to posttest (week 8). Results: The study included 24 participants. There were no significant differences between the 2 groups at baseline. With regard to significant differences between the 2 groups in terms of the primary outcome, the mean change in the PANSS total score from baseline to week 8 in the vCBTp plus UC group was --9.5 (95\% CI --12.09 to --6.91) and the mean change in the UC alone group was 6.9 (95\% CI 1.54-12.30). The difference between the 2 groups was significant (P<.001). In addition, significant improvements were observed in the subscales of positive (P<.001) and negative (P=.004) symptoms and general psychopathology (P<.001). Significant differences were also observed in the secondary outcomes of the General Anxiety Disorder-7 (GAD-7; P=.04) and EQ-5D-5L (P=.005). There were no dropouts and no serious adverse events in this study. Conclusions: A total of 7 remote vCBTp sessions conducted in the vCBTp plus UC group could be safely administered to patients with schizophrenia. They were also observed to be effective for psychiatric symptoms, general anxiety, and quality of life. However, because of the observed worsening of scores in the UC group, caution is required in interpreting significant differences between the 2 groups. This approach is expected to improve accessibility to CBTp for outpatients with schizophrenia and social anxiety regarding transportation use and financial and physical burdens related to transportation, and to contribute to promoting CBTp acceptability by compensating for the shortage of implementers. Trial Registration: University Hospital Medical Information Network Clinical Trials Registry UMIN000043396; https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr\_view.cgi?recptno=R000049544 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2022-069734 ", doi="10.2196/59540", url="https://formative.jmir.org/2025/1/e59540", url="http://www.ncbi.nlm.nih.gov/pubmed/39610049" } @Article{info:doi/10.2196/59261, author="Tanaka, Hiroki and Miyamoto, Kana and Hamet Bagnou, Jennifer and Prigent, Elise and Clavel, C{\'e}line and Martin, Jean-Claude and Nakamura, Satoshi", title="Analysis of Social Performance and Action Units During Social Skills Training: Focus Group Study of Adults With Autism Spectrum Disorder and Schizophrenia", journal="JMIR Form Res", year="2025", month="Jan", day="10", volume="9", pages="e59261", keywords="social performance rating scale", keywords="social skills training", keywords="autism spectrum disorder", keywords="schizophrenia", keywords="facial expressions", keywords="social", keywords="autism", keywords="training", keywords="communication", keywords="trainers", keywords="tool", keywords="neurological", abstract="Background: Social communication is a crucial factor influencing human social life. Quantifying the degree of difficulty faced in social communication is necessary for understanding developmental and neurological disorders and for creating systems used in automatic symptom screening and assistive methods such as social skills training (SST). SST by a human trainer is a well-established method. Previous SST used a modified roleplay test to evaluate human social communication skills. However, there are no widely accepted evaluation criteria or social behavioral markers to quantify social performance during SST. Objective: This paper has 2 objectives. First, we propose applying the Social Performance Rating Scale (SPRS) to SST data to measure social communication skills. We constructed a Japanese version of the SPRS already developed in English and French. Second, we attempt to quantify action units during SST for people with autism spectrum disorder (ASD) or schizophrenia. Methods: We used videos of interactions between trainers, adults with ASD (n=16) or schizophrenia (n=15), and control participants (n=19) during SST sessions. Two raters applied the proposed scale to annotate the collected data. We investigated the differences between roleplay tasks and participant groups (ASD, schizophrenia, and control). Furthermore, the intensity of action units on the OpenFace toolkit was measured in terms of mean and SD during SST roleplaying. Results: We found significantly greater gaze scores in adults with ASD than in adults with schizophrenia. Differences were also found between the ratings of different tasks in the adults with schizophrenia and the control participants. Action units numbered AU06 and AU12 were significantly deactivated in people with schizophrenia compared with the control group. Moreover, AU02 was significantly activated in people with ASD compared with the other groups. Conclusions: The results suggest that the SPRS can be a useful tool for assessing social communication skills in different cultures and different pathologies when used with the modified roleplay test. Furthermore, facial expressions could provide effective social and behavioral markers to characterize psychometric properties. Possible future directions include using the SPRS for assessing social behavior during interaction with a digital agent. ", doi="10.2196/59261", url="https://formative.jmir.org/2025/1/e59261" } @Article{info:doi/10.2196/55924, author="Loh, Yi Pei and Martinengo, Laura and Heaukulani, Creighton and Tan, Yang Xin and Hng, Moses and Cheah, Yin Yong and Morris, T. Robert J. and Tudor Car, Lorainne and Lee, Jimmy", title="Characteristics and Outcomes of mHealth Interventions in Psychosis: Systematic Mapping Review", journal="J Med Internet Res", year="2024", month="Dec", day="23", volume="26", pages="e55924", keywords="mHealth", keywords="digital health", keywords="mobile applications", keywords="psychosis", keywords="schizophrenia", keywords="schizophrenia spectrum", keywords="psychotic disorders", keywords="mapping review", abstract="Background: Mobile health (mHealth) interventions have gained popularity in augmenting psychiatric care for adults with psychosis. Interest has grown in leveraging mHealth to empower individuals living with severe mental illness and extend continuity of care beyond the hospital to the community. However, reported outcomes have been mixed, likely attributed in part to the intervention and adopted outcomes, which affected between-study comparisons. Objective: This study aimed to critically review outcome measures used to evaluate mHealth interventions for adults with psychosis in relation to the characteristics of mHealth interventions. Methods: A systematic mapping review was conducted. We searched PubMed, CINAHL, Embase, PsycINFO, and Cochrane Libraries from 1973 to the present. Selection criteria included randomized controlled studies of mHealth interventions in adults diagnosed with schizophrenia spectrum disorders. Reviewers worked in pairs to screen and extract data from included studies independently using a standardized form; disagreements were resolved by consensus with an independent reviewer. We report our findings in line with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Results: A total of 1703 citations were screened; 29 publications reporting on 23 studies were included in this review. mHealth interventions for psychosis span a wide range, with psychological therapy being the most-deployed intervention (12/23, 52\%), followed by psychoeducation (8/23, 35\%) and active self-monitoring (8/23, 35\%). Several mHealth interventions for psychosis targeted multiple pillars of biopsychosocial well-being (10/23, 43\%); the bulk of interventions (16/23, 70\%) incorporated features promoting users' self-management. The majority of mHealth interventions were delivered through applications (14/23, 61\%) as the main medium and smartphones (17/23, 74\%) as the main channel of delivery. Interventions were primarily administered in the outpatient and community settings (16/23, 70\%); many were also blended with in-person sessions (11/23, 48\%) or guided remotely (6/23, 26\%) by persons, including health care providers or trained peer supporters. The severity of psychosis-related symptoms (21/23, 91\%) was the most prevalent outcome, of which positive symptoms (13/23, 57\%), mood and anxiety (10/23, 43\%), and overall psychopathology severity (9/23, 39\%) were most commonly measured. Patient-centric outcomes, including well-being (17/23, 74\%)---particularly quality of life (10/23, 43\%)---and user experience (15/23, 65\%), including feasibility (7/23, 30\%), acceptability (7/23, 30\%), and engagement (7/23, 26\%). Notably, outcome choices remained diverse despite stratification by type of mHealth intervention. Conclusions: mHealth interventions for psychosis encompass a wide range of modalities and use outcome measures that probe various social and behavioral determinants of health. These should be considered complex interventions, and a holistic evaluation approach combining clinical and patient-centric outcomes is recommended. ", doi="10.2196/55924", url="https://www.jmir.org/2024/1/e55924", url="http://www.ncbi.nlm.nih.gov/pubmed/39714907" } @Article{info:doi/10.2196/63743, author="M{\"u}nchenberg, Sarah Pauline and Yessimova, Dinara and Panteli, Dimitra and Kurth, Tobias", title="Digital Health Interventions for Informal Family Caregivers of People With First-Episode Psychosis: Systematic Review on User Experience and Effectiveness", journal="JMIR Ment Health", year="2024", month="Nov", day="28", volume="11", pages="e63743", keywords="first-episode psychosis", keywords="early psychosis", keywords="digital health interventions", keywords="telepsychiatry", keywords="informal caregivers", keywords="family caregivers", keywords="telehealth", keywords="severe mental disorders", keywords="psychosis", keywords="digital intervention", keywords="digital health", keywords="mental health", keywords="psychoeducation", keywords="mobile phone", abstract="Background: First-episode psychosis (FEP) imposes a substantial burden not only on the individual affected but also on their families. Given that FEP usually occurs during adolescence, families overtake a big part of informal care. Early family interventions, especially psychoeducation, are crucial for informal family caregivers to best support the recovery of their loved one with FEP and to reduce the risk of a psychotic relapse as much as possible, but also to avoid chronic stress within the family due to the burden of care. Digital health interventions offer the possibility to access help quicker, use less resources, and improve informal family caregiver outcomes, for example, by reducing stress and improving caregiver quality of life. Objective: This study aimed to systematically identify studies on digital health interventions for informal family caregivers of people with FEP and to describe and synthesize the available literature on user experience, as well as the effectiveness of such digital applications on the clinical outcomes, consisting of (1) perceived caregiver stress, (2) expressed emotion, and (3) parental self-efficacy. Methods: A systematic search was carried out across 4 electronic databases. In addition, reference lists of relevant studies were hand-searched. This review aimed to include only primary studies on informal family caregivers, who had to care for a person with FEP between 15 years and 40 years of age and a diagnosis of FEP with onset of observed symptoms within the past 5 years. All types of digital interventions were included. This systematic review is aligned with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020 guidelines. Results: The search identified 7 studies that reported on user experience or effectiveness of digital health interventions on perceived caregiver stress, expressed emotion, and parental self-efficacy, including 377 informal family FEP caregivers across trials. Digital health interventions--web-based, videoconferences, and mHealth--were well accepted and perceived as relevant, easy to use, and helpful by informal family FEP caregivers. Psychoeducational content was rated as the most important across studies. Perceived caregiver stress, expressed emotion, and parental self-efficacy improved in all studies that reported on these clinical outcomes. Conclusions: The results of this review suggest that digital health interventions aimed at informal family caregivers of individuals with FEP can improve relevant clinical outcomes, with participants reporting a positive user experience. However, for some interventions reviewed, specialized in-person family care outperformed the digital intervention and partially led to better results in perceived caregiver stress and parental self-efficacy. Therefore, while digital interventions present a promising approach to alleviate the burden of care and improve informal family FEP caregiver outcomes, more studies with well-powered experimental designs are needed to further investigate the effectiveness of such applications in this population. Trial Registration: PROSPERO CRD42024536715; https://tinyurl.com/bdd3u7v9 ", doi="10.2196/63743", url="https://mental.jmir.org/2024/1/e63743" } @Article{info:doi/10.2196/57109, author="van Aubel, Evelyne and Vaessen, Thomas and Uyttebroek, Lotte and Steinhart, Henrietta and Beijer-Klippel, Annelie and Batink, Tim and van Winkel, Ruud and de Haan, Lieuwe and van der Gaag, Mark and van Amelsvoort, Th{\'e}r{\`e}se and Marcelis, Machteld and Schirmbeck, Frederike and Reininghaus, Ulrich and Myin-Germeys, Inez", title="Engagement and Acceptability of Acceptance and Commitment Therapy in Daily Life in Early Psychosis: Secondary Findings From a Multicenter Randomized Controlled Trial", journal="JMIR Form Res", year="2024", month="Nov", day="21", volume="8", pages="e57109", keywords="acceptance and commitment therapy", keywords="ACT", keywords="first episode of psychosis", keywords="FEP", keywords="ultrahigh risk for psychosis", keywords="UHR", keywords="ecological momentary intervention", keywords="EMI", keywords="mobile health", keywords="mHealth", keywords="blended care", keywords="mobile phone", abstract="Background: Acceptance and commitment therapy (ACT) is promising in the treatment of early psychosis. Augmenting face-to-face ACT with mobile health ecological momentary interventions may increase its treatment effects and empower clients to take treatment into their own hands. Objective: This study aimed to investigate and predict treatment engagement with and acceptability of acceptance and commitment therapy in daily life (ACT-DL), a novel ecological momentary intervention for people with an ultrahigh risk state and a first episode of psychosis. Methods: In the multicenter randomized controlled trial, 148 individuals with ultrahigh risk or first-episode psychosis aged 15-65 years were randomized to treatment as usual only (control) or to ACT-DL combined with treatment as usual (experimental), consisting of 8 face-to-face sessions augmented with an ACT-based smartphone app, delivering ACT skills and techniques in daily life. For individuals in the intervention arm, we collected data on treatment engagement with and acceptability of ACT-DL during and after the intervention. Predictors of treatment engagement and acceptability included baseline demographic, clinical, and functional outcomes. Results: Participants who received ACT-DL in addition to treatment as usual (n=71) completed a mean of 6 (SD 3) sessions, with 59\% (n=42) of participants completing all sessions. App engagement data (n=58) shows that, on a weekly basis, participants used the app 13 times and were compliant with 6 of 24 (25\%) notifications. Distribution plots of debriefing scores (n=46) show that 85\%-96\% of participants reported usefulness on all acceptability items to at least some extent (scores ?2; 1=no usefulness) and that 91\% (n=42) of participants reported perceived burden by number and length of notifications (scores ?2; 1=no burden). Multiple linear regression models were fitted to predict treatment engagement and acceptability. Ethnic minority backgrounds predicted lower notification response compliance (B=--4.37; P=.01), yet higher app usefulness (B=1.25; P=.049). Negative (B=--0.26; P=.01) and affective (B=0.14; P=.04) symptom severity predicted lower and higher ACT training usefulness, respectively. Being female (B=--1.03; P=.005) predicted lower usefulness of the ACT metaphor images on the app. Conclusions: Our results corroborate good treatment engagement with and acceptability of ACT-DL in early psychosis. We provide recommendations for future intervention optimization. Trial Registration: OMON NL46439.068.13; https://onderzoekmetmensen.nl/en/trial/24803 ", doi="10.2196/57109", url="https://formative.jmir.org/2024/1/e57109", url="http://www.ncbi.nlm.nih.gov/pubmed/39570655" } @Article{info:doi/10.2196/57150, author="D'Arcey, Jessica and Torous, John and Asuncion, Toni-Rose and Tackaberry-Giddens, Leah and Zahid, Aqsa and Ishak, Mira and Foussias, George and Kidd, Sean", title="Leveraging Personal Technologies in the Treatment of Schizophrenia Spectrum Disorders: Scoping Review", journal="JMIR Ment Health", year="2024", month="Sep", day="30", volume="11", pages="e57150", keywords="schizophrenia", keywords="digital mental health", keywords="personal technology", keywords="access to specialized resources", keywords="mental health", keywords="scoping review", keywords="mental health care", keywords="feasibility", keywords="efficacy", keywords="clinical integration", keywords="support", keywords="specialized care", keywords="care", keywords="database", keywords="schizophrenia spectrum disorder", keywords="text messaging", keywords="text", keywords="user feedback", keywords="usability", keywords="acceptability", keywords="satisfaction", keywords="engagement", keywords="digital health", keywords="technology", keywords="health technology", keywords="mood disorder", keywords="mood disorders", keywords="neurodevelopment", keywords="eHealth", keywords="mobile phone", abstract="Background: Digital mental health is a rapidly growing field with an increasing evidence base due to its potential scalability and impacts on access to mental health care. Further, within underfunded service systems, leveraging personal technologies to deliver or support specialized service delivery has garnered attention as a feasible and cost-effective means of improving access. Digital health relevance has also improved as technology ownership in individuals with schizophrenia has improved and is comparable to that of the general population. However, less digital health research has been conducted in groups with schizophrenia spectrum disorders compared to other mental health conditions, and overall feasibility, efficacy, and clinical integration remain largely unknown. Objective: This review aims to describe the available literature investigating the use of personal technologies (ie, phone, computer, tablet, and wearables) to deliver or support specialized care for schizophrenia and examine opportunities and barriers to integrating this technology into care. Methods: Given the size of this review, we used scoping review methods. We searched 3 major databases with search teams related to schizophrenia spectrum disorders, various personal technologies, and intervention outcomes related to recovery. We included studies from the full spectrum of methodologies, from development papers to implementation trials. Methods and reporting follow the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Results: This search resulted in 999 studies, which, through review by at least 2 reviewers, included 92 publications. Included studies were published from 2010 to 2023. Most studies examined multitechnology interventions (40/92, 43\%) or smartphone apps (25/92, 27\%), followed by SMS text messaging (16/92, 17\%) and internet-based interventions (11/92, 12\%). No studies used wearable technology on its own to deliver an intervention. Regarding the stage of research in the field, the largest number of publications were pilot studies (32/92, 35\%), followed by randomized control trials (RCTs; 20/92, 22\%), secondary analyses (16/92, 17\%), RCT protocols (16/92, 17\%), development papers (5/92, 5\%), and nonrandomized or quasi-experimental trials (3/92, 3\%). Most studies did not report on safety indices (55/92, 60\%) or privacy precautions (64/92, 70\%). Included studies tend to report consistent positive user feedback regarding the usability, acceptability, and satisfaction with technology; however, engagement metrics are highly variable and report mixed outcomes. Furthermore, efficacy at both the pilot and RCT levels report mixed findings on primary outcomes. Conclusions: Overall, the findings of this review highlight the discrepancy between the high levels of acceptability and usability of these digital interventions, mixed efficacy results, and difficulties with sustained engagement. The discussion highlights common patterns that may underscore this observation in the field; however, as this was a scoping review, a more in-depth systematic review or meta-analysis may be required to better understand the trends outlined in this review. ", doi="10.2196/57150", url="https://mental.jmir.org/2024/1/e57150", url="http://www.ncbi.nlm.nih.gov/pubmed/39348196" } @Article{info:doi/10.2196/56977, author="Ritchie, Gabrielle and Nwachukwu, Harriet and Parker, Stephen and Dark, Frances", title="Impact of Biological Sex on Emotional Perception Among Adults With Schizophrenia Spectrum Disorders: Protocol for a Systematic Review", journal="JMIR Res Protoc", year="2024", month="Sep", day="10", volume="13", pages="e56977", keywords="schizophrenia", keywords="emotional perception", keywords="systematic review", keywords="sex differences", keywords="psychosis", keywords="social cognition", keywords="emotional processing", abstract="Background: It is well established that individuals with schizophrenia experience deficits in emotional perception that can impact long-term social and occupational functioning. Understanding the factors that impact these impairments is important for targeting interventions to improve recovery. In the general population, compared with males, females tend to show greater perception of emotions. Whether this sex difference persists in schizophrenia is less clear. In contrast to males, females diagnosed with schizophrenia tend to have a higher age of disease onset and better premorbid functioning but do not necessarily have better outcomes. Effective treatments for social cognitive impairments are highly relevant to long-term functional rehabilitation. A greater understanding of the cognitive deficits in emotional perception within females and males living with schizophrenia may assist interventions to be better tailored to individuals. Objective: This systematic review aims to collate, synthesize, and critically appraise evidence considering the influence of biological sex (female and male) on the emotional perception of individuals with schizophrenia. Methods: This is a systematic review protocol based on the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) guidelines. The electronic databases MEDLINE, Embase, CENTRAL, CINAHL, and PsycINFO will be systematically searched. To be included in this review, studies must compare the emotional perceptions of male and female participants older than 18 years who have a primary diagnosis of a schizophrenia spectrum disorder. Qualitative studies, case reports, case series, unpublished manuscripts, and studies not reported in English will be excluded. Key search strategies will include combinations of the following terms: ``men,'' ``male,'' ``man,'' ``female,'' ``women,'' ``woman,'' ``sex,'' ``gender,'' ``emotional perception,'' ``emotional processing,'' ``schizophrenia,'' ``schizophren,'' ``psychotic disorders,'' ``psychosis,'' ``psychoses,'' ``psychotic,'' ``schizoaffective,'' ``schizotypal personality disorder,'' and ``schizotyp.'' Identified studies will be uploaded to the web-based Covidence systematic review management software. The risk of bias for individual studies will be assessed using the relevant Joanna Briggs Institute checklist tools. The GRADE (Grading of Recommendations Assessment, Development, and Evaluation) system will also be used to evaluate the strength of the evidence base. Findings will be synthesized to provide a systematic summary of the existing literature. If sufficiently comparable data to permit meta-analysis emerges, a random-effects meta-analysis will be performed. Results: This systematic review was registered with the PROSPERO (International Prospective Register of Systematic Reviews) in October 2023. The search and screening of study titles and abstracts are currently underway. Data are expected to be extracted and analyzed in July 2024. Conclusions: Results will contribute to an improved understanding of the social cognitive profiles of males and females with schizophrenia. This knowledge is expected to inform the adaptation of interventions to improve functional outcomes. Trial Registration: PROSPERO CRD42023463561; https://tinyurl.com/34sr3rnf International Registered Report Identifier (IRRID): DERR1-10.2196/56977 ", doi="10.2196/56977", url="https://www.researchprotocols.org/2024/1/e56977" } @Article{info:doi/10.2196/57031, author="Fonseca, Olivia Ana and Gomes, Silveira July and Novaes, Barros Rafael Angulo Condoretti and Dias, Lopes C{\'i}ntia and Rodrigues, Alves Maria Eva de Miranda and Gadelha, Ary and Noto, Cristiano", title="Feuerstein Instrumental Enrichment Program for People With Schizophrenia After the First Episode of Psychosis: Protocol for an Open-Label Intervention Study", journal="JMIR Res Protoc", year="2024", month="Sep", day="6", volume="13", pages="e57031", keywords="schizophrenia", keywords="Feuerstein Instrumental Enrichment program", keywords="cognitive intervention", keywords="functionality", keywords="first-episode psychosis", keywords="early stages", keywords="Feuerstein Instrumental Enrichment", keywords="FIE", keywords="psychotic disorder", keywords="psychotic disorders", keywords="neurocognitive deficits", keywords="economic burden", keywords="cognitive rehabilitation", keywords="quality of life", keywords="daily living", keywords="cognitive assessment", keywords="maze task", keywords="mental disorder", keywords="cognitive deficits", keywords="mental health", keywords="psychosis", abstract="Background: Schizophrenia is a disorder associated with neurocognitive deficits that adversely affect daily functioning and impose an economic burden. Cognitive rehabilitation interventions, particularly during the early phases of illness, have been shown to improve cognition, functionality, and quality of life. The Feuerstein Instrumental Enrichment (FIE) program, based on the Mediated Learning Experience and the Structural Cognitive Modifiability theory, has been applied in various disorders, but its applicability in schizophrenia has not yet been clarified. Objective: This study aims to investigate the effects of the FIE program on the functionality of patients with first-episode schizophrenia. Methods: In total, 17 patients will be recruited for an open-label intervention consisting of twice-weekly sessions for 10 weeks. The primary outcome measure will be changes in the Goal Achievement Scale score. Maze task performance from the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) battery will serve as a secondary outcome measure. At the same time, changes in Positive and Negative Syndrome Scale scores and other MATRICS domains will be analyzed as exploratory outcomes. Assessments will be administered before and after the intervention, with a follow-up period of 6 months. Results: This trial was preregistered in The Brazilian Registry of Clinical Trials (RBR-4gzhy4s). By February 2024, 11 participants were enrolled in the training. Recruitment is expected to be completed by May 2024. Data analysis will be conducted between May and September 2024. The results are expected to be published in January 2025. Conclusions: This study may establish a protocol for the FIE program that uses mediation techniques for individuals in the early stages of schizophrenia. The results will add to the knowledge about strategies to promote cognitive skills and functional impairment in daily life. International Registered Report Identifier (IRRID): DERR1-10.2196/57031 ", doi="10.2196/57031", url="https://www.researchprotocols.org/2024/1/e57031", url="http://www.ncbi.nlm.nih.gov/pubmed/39240685" } @Article{info:doi/10.2196/59198, author="Paquin, Vincent and Ackerman, A. Robert and Depp, A. Colin and Moore, C. Raeanne and Harvey, D. Philip and Pinkham, E. Amy", title="Media Use and Its Associations With Paranoia in Schizophrenia and Bipolar Disorder: Ecological Momentary Assessment", journal="JMIR Ment Health", year="2024", month="Jul", day="3", volume="11", pages="e59198", keywords="paranoia", keywords="social media", keywords="digital media", keywords="technology", keywords="psychosis", keywords="schizophrenia", keywords="schizoaffective", keywords="bipolar disorder", keywords="ecological momentary assessment", keywords="spectrum", keywords="sociodemographic", keywords="linear mixed model", keywords="media use", keywords="mental health", keywords="digital intervention", keywords="adult", keywords="adults", keywords="medical center", keywords="mental health clinic", keywords="psychiatry", keywords="psychiatrist", abstract="Background: Paranoia is a spectrum of fear-related experiences that spans diagnostic categories and is influenced by social and cognitive factors. The extent to which social media and other types of media use are associated with paranoia remains unclear. Objective: We aimed to examine associations between media use and paranoia at the within- and between-person levels. Methods: Participants were 409 individuals diagnosed with schizophrenia spectrum or bipolar disorder. Measures included sociodemographic and clinical characteristics at baseline, followed by ecological momentary assessments (EMAs) collected 3 times daily over 30 days. EMA evaluated paranoia and 5 types of media use: social media, television, music, reading or writing, and other internet or computer use. Generalized linear mixed models were used to examine paranoia as a function of each type of media use and vice versa at the within- and between-person levels. Results: Of the 409 participants, the following subgroups reported at least 1 instance of media use: 261 (63.8\%) for using social media, 385 (94.1\%) for watching TV, 292 (71.4\%) for listening to music, 191 (46.7\%) for reading or writing, and 280 (68.5\%) for other internet or computer use. Gender, ethnoracial groups, educational attainment, and diagnosis of schizophrenia versus bipolar disorder were differentially associated with the likelihood of media use. There was a within-person association between social media use and paranoia: using social media was associated with a subsequent decrease of 5.5\% (fold-change 0.945, 95\% CI 0.904-0.987) in paranoia. The reverse association, from paranoia to subsequent changes in social media use, was not statistically significant. Other types of media use were not significantly associated with paranoia. Conclusions: This study shows that social media use was associated with a modest decrease in paranoia, perhaps reflecting the clinical benefits of social connection. However, structural disadvantage and individual factors may hamper the accessibility of media activities, and the mental health correlates of media use may further vary as a function of contents and contexts of use. ", doi="10.2196/59198", url="https://mental.jmir.org/2024/1/e59198" } @Article{info:doi/10.2196/58390, author="Adrien, Vladimir and Bosc, Nicolas and Peccia Galletto, Claire and Diot, Thomas and Claverie, Damien and Reggente, Nicco and Trousselard, Marion and Bui, Eric and Baubet, Thierry and Schoeller, F{\'e}lix", title="Enhancing Agency in Posttraumatic Stress Disorder Therapies Through Sensorimotor Technologies", journal="J Med Internet Res", year="2024", month="Jul", day="1", volume="26", pages="e58390", keywords="posttraumatic stress disorder", keywords="PTSD", keywords="agency", keywords="proprioception", keywords="trauma", keywords="self-control", keywords="sensorimotor technology", keywords="enactive perspective", keywords="peritraumatic dissociation", keywords="proprioceptive reafferent fibers", keywords="gesture sonification devices", doi="10.2196/58390", url="https://www.jmir.org/2024/1/e58390", url="http://www.ncbi.nlm.nih.gov/pubmed/38742989" } @Article{info:doi/10.2196/56668, author="Morita, Kentaro and Miura, Kenichiro and Toyomaki, Atsuhito and Makinodan, Manabu and Ohi, Kazutaka and Hashimoto, Naoki and Yasuda, Yuka and Mitsudo, Takako and Higuchi, Fumihiro and Numata, Shusuke and Yamada, Akiko and Aoki, Yohei and Honda, Hiromitsu and Mizui, Ryo and Honda, Masato and Fujikane, Daisuke and Matsumoto, Junya and Hasegawa, Naomi and Ito, Satsuki and Akiyama, Hisashi and Onitsuka, Toshiaki and Satomura, Yoshihiro and Kasai, Kiyoto and Hashimoto, Ryota", title="Tablet-Based Cognitive and Eye Movement Measures as Accessible Tools for Schizophrenia Assessment: Multisite Usability Study", journal="JMIR Ment Health", year="2024", month="May", day="30", volume="11", pages="e56668", keywords="schizophrenia", keywords="cognitive function", keywords="eye movement", keywords="diagnostic biomarkers", keywords="digital health tools", abstract="Background: Schizophrenia is a complex mental disorder characterized by significant cognitive and neurobiological alterations. Impairments in cognitive function and eye movement have been known to be promising biomarkers for schizophrenia. However, cognitive assessment methods require specialized expertise. To date, data on simplified measurement tools for assessing both cognitive function and eye movement in patients with schizophrenia are lacking. Objective: This study aims to assess the efficacy of a novel tablet-based platform combining cognitive and eye movement measures for classifying schizophrenia. Methods: Forty-four patients with schizophrenia, 67 healthy controls, and 41 patients with other psychiatric diagnoses participated in this study from 10 sites across Japan. A free-viewing eye movement task and 2 cognitive assessment tools (Codebreaker task from the THINC-integrated tool and the CognitiveFunctionTest app) were used for conducting assessments in a 12.9-inch iPad Pro. We performed comparative group and logistic regression analyses for evaluating the diagnostic efficacy of the 3 measures of interest. Results: Cognitive and eye movement measures differed significantly between patients with schizophrenia and healthy controls (all 3 measures; P<.001). The Codebreaker task showed the highest classification effectiveness in distinguishing schizophrenia with an area under the receiver operating characteristic curve of 0.90. Combining cognitive and eye movement measures further improved accuracy with a maximum area under the receiver operating characteristic curve of 0.94. Cognitive measures were more effective in differentiating patients with schizophrenia from healthy controls, whereas eye movement measures better differentiated schizophrenia from other psychiatric conditions. Conclusions: This multisite study demonstrates the feasibility and effectiveness of a tablet-based app for assessing cognitive functioning and eye movements in patients with schizophrenia. Our results suggest the potential of tablet-based assessments of cognitive function and eye movement as simple and accessible evaluation tools, which may be useful for future clinical implementation. ", doi="10.2196/56668", url="https://mental.jmir.org/2024/1/e56668", url="http://www.ncbi.nlm.nih.gov/pubmed/38815257" } @Article{info:doi/10.2196/49916, author="Fernandes, Sara and Brousse, Yann and Zendjidjian, Xavier and Cano, Delphine and Riedberger, J{\'e}r{\'e}mie and Llorca, Pierre-Michel and Samalin, Ludovic and Dassa, Daniel and Trichard, Christian and Laprevote, Vincent and Sauvaget, Anne and Abbar, Mocrane and Misdrahi, David and Berna, Fabrice and Lancon, Christophe and Coulon, Nathalie and El-Hage, Wissam and Rozier, Pierre-Emmanuel and Benoit, Michel and Giordana, Bruno and Caqueo-Ur{\'i}zar, Alejandra and Yon, Keon Dong and Tran, Bach and Auquier, Pascal and Fond, Guillaume and Boyer, Laurent", title="Psychometric Assessment of an Item Bank for Adaptive Testing on Patient-Reported Experience of Care Environment for Severe Mental Illness: Validation Study", journal="JMIR Ment Health", year="2024", month="May", day="16", volume="11", pages="e49916", keywords="psychiatry", keywords="public mental health", keywords="schizophrenia", keywords="major depressive disorders", keywords="bipolar disorders", keywords="patient-reported experience measures", keywords="quality of care", keywords="health services research", keywords="computerized adaptive testing", keywords="real-world data", abstract="Background: The care environment significantly influences the experiences of patients with severe mental illness and the quality of their care. While a welcoming and stimulating environment enhances patient satisfaction and health outcomes, psychiatric facilities often prioritize staff workflow over patient needs. Addressing these challenges is crucial to improving patient experiences and outcomes in mental health care. Objective: This study is part of the Patient-Reported Experience Measure for Improving Quality of Care in Mental Health (PREMIUM) project and aims to establish an item bank (PREMIUM-CE) and to develop computerized adaptive tests (CATs) to measure the experience of the care environment of adult patients with schizophrenia, bipolar disorder, or major depressive disorder. Methods: We performed psychometric analyses including assessments of item response theory (IRT) model assumptions, IRT model fit, differential item functioning (DIF), item bank validity, and CAT simulations. Results: In this multicenter cross-sectional study, 498 patients were recruited from outpatient and inpatient settings. The final PREMIUM-CE 13-item bank was sufficiently unidimensional (root mean square error of approximation=0.082, 95\% CI 0.067-0.097; comparative fit index=0.974; Tucker-Lewis index=0.968) and showed an adequate fit to the IRT model (infit mean square statistic ranging between 0.7 and 1.0). DIF analysis revealed no item biases according to gender, health care settings, diagnosis, or mode of study participation. PREMIUM-CE scores correlated strongly with satisfaction measures (r=0.69-0.78; P<.001) and weakly with quality-of-life measures (r=0.11-0.21; P<.001). CAT simulations showed a strong correlation (r=0.98) between CAT scores and those of the full item bank, and around 79.5\% (396/498) of the participants obtained a reliable score with the administration of an average of 7 items. Conclusions: The PREMIUM-CE item bank and its CAT version have shown excellent psychometric properties, making them reliable measures for evaluating the patient experience of the care environment among adults with severe mental illness in both outpatient and inpatient settings. These measures are a valuable addition to the existing landscape of patient experience assessment, capturing what truly matters to patients and enhancing the understanding of their care experiences. Trial Registration: ClinicalTrials.gov NCT02491866; https://clinicaltrials.gov/study/NCT02491866 ", doi="10.2196/49916", url="https://mental.jmir.org/2024/1/e49916", url="http://www.ncbi.nlm.nih.gov/pubmed/38753416" } @Article{info:doi/10.2196/57155, author="Smith, A. Katharine and Hardy, Amy and Vinnikova, Anastasia and Blease, Charlotte and Milligan, Lea and Hidalgo-Mazzei, Diego and Lambe, Sin{\'e}ad and Marzano, Lisa and Uhlhaas, J. Peter and Ostinelli, G. Edoardo and Anmella, Gerard and Zangani, Caroline and Aronica, Rosario and Dwyer, Bridget and Torous, John and Cipriani, Andrea", title="Digital Mental Health for Schizophrenia and Other Severe Mental Illnesses: An International Consensus on Current Challenges and Potential Solutions", journal="JMIR Ment Health", year="2024", month="May", day="8", volume="11", pages="e57155", keywords="digital", keywords="mental health", keywords="severe mental illness", keywords="consensus", keywords="lived experience", keywords="ethics", keywords="user-centered design", keywords="patient and public involvement", keywords="mobile phone", abstract="Background: Digital approaches may be helpful in augmenting care to address unmet mental health needs, particularly for schizophrenia and severe mental illness (SMI). Objective: An international multidisciplinary group was convened to reach a consensus on the challenges and potential solutions regarding collecting data, delivering treatment, and the ethical challenges in digital mental health approaches for schizophrenia and SMI. Methods: The consensus development panel method was used, with an in-person meeting of 2 groups: the expert group and the panel. Membership was multidisciplinary including those with lived experience, with equal participation at all stages and coproduction of the consensus outputs and summary. Relevant literature was shared in advance of the meeting, and a systematic search of the recent literature on digital mental health interventions for schizophrenia and psychosis was completed to ensure that the panel was informed before the meeting with the expert group. Results: Four broad areas of challenge and proposed solutions were identified: (1) user involvement for real coproduction; (2) new approaches to methodology in digital mental health, including agreed standards, data sharing, measuring harms, prevention strategies, and mechanistic research; (3) regulation and funding issues; and (4) implementation in real-world settings (including multidisciplinary collaboration, training, augmenting existing service provision, and social and population-focused approaches). Examples are provided with more detail on human-centered research design, lived experience perspectives, and biomedical ethics in digital mental health approaches for SMI. Conclusions: The group agreed by consensus on a number of recommendations: (1) a new and improved approach to digital mental health research (with agreed reporting standards, data sharing, and shared protocols), (2) equal emphasis on social and population research as well as biological and psychological approaches, (3) meaningful collaborations across varied disciplines that have previously not worked closely together, (4) increased focus on the business model and product with planning and new funding structures across the whole development pathway, (5) increased focus and reporting on ethical issues and potential harms, and (6) organizational changes to allow for true communication and coproduction with those with lived experience of SMI. This study approach, combining an international expert meeting with patient and public involvement and engagement throughout the process, consensus methodology, discussion, and publication, is a helpful way to identify directions for future research and clinical implementation in rapidly evolving areas and can be combined with measurements of real-world clinical impact over time. Similar initiatives will be helpful in other areas of digital mental health and similarly fast-evolving fields to focus research and organizational change and effect improved real-world clinical implementation. ", doi="10.2196/57155", url="https://mental.jmir.org/2024/1/e57155", url="http://www.ncbi.nlm.nih.gov/pubmed/38717799" } @Article{info:doi/10.2196/49217, author="O'Sullivan, Shaunagh and McEnery, Carla and Cagliarini, Daniela and Hinton, X. Jordan D. and Valentine, Lee and Nicholas, Jennifer and Chen, A. Nicola and Castagnini, Emily and Lester, Jacqueline and Kanellopoulos, Esta and D'Alfonso, Simon and Gleeson, F. John and Alvarez-Jimenez, Mario", title="A Novel Blended Transdiagnostic Intervention (eOrygen) for Youth Psychosis and Borderline Personality Disorder: Uncontrolled Single-Group Pilot Study", journal="JMIR Ment Health", year="2024", month="Apr", day="1", volume="11", pages="e49217", keywords="digital intervention", keywords="blended care", keywords="youth mental health", keywords="transdiagnostic intervention", keywords="psychotic disorders", keywords="borderline personality disorder", keywords="digital health", keywords="mobile phone", abstract="Background: Integrating innovative digital mental health interventions within specialist services is a promising strategy to address the shortcomings of both face-to-face and web-based mental health services. However, despite young people's preferences and calls for integration of these services, current mental health services rarely offer blended models of care. Objective: This pilot study tested an integrated digital and face-to-face transdiagnostic intervention (eOrygen) as a blended model of care for youth psychosis and borderline personality disorder. The primary aim was to evaluate the feasibility, acceptability, and safety of eOrygen. The secondary aim was to assess pre-post changes in key clinical and psychosocial outcomes. An exploratory aim was to explore the barriers and facilitators identified by young people and clinicians in implementing a blended model of care into practice. Methods: A total of 33 young people (aged 15-25 years) and 18 clinicians were recruited over 4 months from two youth mental health services in Melbourne, Victoria, Australia: (1) the Early Psychosis Prevention and Intervention Centre, an early intervention service for first-episode psychosis; and (2) the Helping Young People Early Clinic, an early intervention service for borderline personality disorder. The feasibility, acceptability, and safety of eOrygen were evaluated via an uncontrolled single-group study. Repeated measures 2-tailed t tests assessed changes in clinical and psychosocial outcomes between before and after the intervention (3 months). Eight semistructured qualitative interviews were conducted with the young people, and 3 focus groups, attended by 15 (83\%) of the 18 clinicians, were conducted after the intervention. Results: eOrygen was found to be feasible, acceptable, and safe. Feasibility was established owing to a low refusal rate of 25\% (15/59) and by exceeding our goal of young people recruited to the study per clinician. Acceptability was established because 93\% (22/24) of the young people reported that they would recommend eOrygen to others, and safety was established because no adverse events or unlawful entries were recorded and there were no worsening of clinical and social outcome measures. Interviews with the young people identified facilitators to engagement such as peer support and personalized therapy content, as well as barriers such as low motivation, social anxiety, and privacy concerns. The clinician focus groups identified evidence-based content as an implementation facilitator, whereas a lack of familiarity with the platform was identified as a barrier owing to clinicians' competing priorities, such as concerns related to risk and handling acute presentations, as well as the challenge of being understaffed. Conclusions: eOrygen as a blended transdiagnostic intervention has the potential to increase therapeutic continuity, engagement, alliance, and intensity. Future research will need to establish the effectiveness of blended models of care for young people with complex mental health conditions and determine how to optimize the implementation of such models into specialized services. ", doi="10.2196/49217", url="https://mental.jmir.org/2024/1/e49217", url="http://www.ncbi.nlm.nih.gov/pubmed/38557432" } @Article{info:doi/10.2196/49849, author="Cugnetto, L. Marilyn and Morris, J. Eric M. and Bonfield, F. Siobain and Gates, Jesse and Morrison, Ilona and Newman, R. Ellie and Nicholls, D. Julia and Soares, M. Lisa and Antonucci, T. Megan and Clemente, R. Jacinta and Garratt, M. Claire L. and Goldstone, Eliot and Pavone, A. David and Farhall, John", title="Group Acceptance and Commitment Therapy for Recovery From Psychosis: Protocol for a Single-Group Waitlist Trial", journal="JMIR Res Protoc", year="2024", month="Mar", day="18", volume="13", pages="e49849", keywords="Acceptance and Commitment Therapy", keywords="ACT", keywords="group therapy", keywords="interventions", keywords="personal recovery", keywords="protocol", keywords="psychosis", keywords="psychotic disorders", keywords="public mental health services", abstract="Background: Psychological interventions, along with antipsychotic medications, are recommended for adults diagnosed with a psychotic disorder. While initially designed to mitigate positive symptoms, psychological interventions targeting personal recovery were developed and aligned with the recovery framework that many mental health services have adopted. Acceptance and Commitment Therapy (ACT) for psychosis is one such intervention that shows promise when delivered in an individual format. There is preliminary evidence that ACT for psychosis in a group format improves recovery. Objective: This trial aims to evaluate the effectiveness of the ``Recovery ACT'' group program on personal recovery among adults living with a psychotic disorder. Methods: Our unfunded study is a multiagency, prospective, nonrandomized, waitlist control, single-group trial of the Recovery ACT group program. The program involves 7 weekly group sessions of 90 minutes duration and a 90-minute booster session held 1 month later. We intend to recruit 160 adults living with a psychotic disorder who enroll in a group that is offered as a routine clinical service at participating public mental health services in Melbourne, Victoria, Australia. The 4 assessment time points are 4-6 weeks before the start of the group program, at the start of the group program, at the end of the group program, and at the booster session. There is an optional midgroup assessment and follow-up study. The primary outcome is personal recovery. Secondary outcomes include participants' well-being and psychological flexibility processes. Qualitative data are also collected from participants and facilitators. Results: Recruitment began in September 2019 and is ongoing until 2024, subsequent to a 24-month disruption due to the COVID-19 pandemic. As of the submission of this paper, 93 participants consented to the evaluation, 65 completed T1 measures, and 40 had a complete data set for the proposed analyses. Conclusions: This is the first trial evaluating the effectiveness of the Recovery ACT group program on personal recovery for adults living with a psychotic disorder. Findings will contribute to knowledge about psychosocial interventions for adults living with psychosis. This trial may also serve as an example of a partnership between clinicians and academics that can facilitate the translation of research into practice. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12620000223932; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12620000223932 International Registered Report Identifier (IRRID): DERR1-10.2196/49849 ", doi="10.2196/49849", url="https://www.researchprotocols.org/2024/1/e49849", url="http://www.ncbi.nlm.nih.gov/pubmed/38498035" } @Article{info:doi/10.2196/54202, author="Veldmeijer, Lars and Terlouw, Gijs and Van Os, Jim and Van 't Veer, Job and Boonstra, Nynke", title="The Frequency of Design Studies Targeting People With Psychotic Symptoms and Features in Mental Health Care Innovation: Secondary Analysis of a Systematic Review", journal="JMIR Ment Health", year="2024", month="Jan", day="9", volume="11", pages="e54202", keywords="design approaches", keywords="design", keywords="innovation", keywords="innovative", keywords="innovate", keywords="innovations", keywords="psychiatry", keywords="mental health care", keywords="mental health", keywords="mental illness", keywords="mental disease", keywords="involvement", keywords="service users", keywords="people with lived experience", keywords="people with lived experiences", keywords="lived experience", keywords="lived experiences", keywords="co-creation", keywords="cocreation", keywords="psychosis", keywords="psychotic", keywords="schizophrenia", keywords="schizoid", keywords="schizotypal", keywords="paranoia", keywords="neurosis", keywords="hallucinosis", keywords="hallucination", keywords="hallucinations", doi="10.2196/54202", url="https://mental.jmir.org/2024/1/e54202", url="http://www.ncbi.nlm.nih.gov/pubmed/38194249" } @Article{info:doi/10.2196/50806, author="Chen, Hwa Huan and Hsu, Tien Hsin and Lin, Chao Pei and Chen, Chin-Yin and Hsieh, Fen Hsiu and Ko, Hung Chih", title="Efficacy of a Smartphone App in Enhancing Medication Adherence and Accuracy in Individuals With Schizophrenia During the COVID-19 Pandemic: Randomized Controlled Trial", journal="JMIR Ment Health", year="2023", month="Dec", day="14", volume="10", pages="e50806", keywords="cognitive functions", keywords="medication adherence", keywords="psychiatric symptoms", keywords="schizophrenia", keywords="smartphone app", abstract="Background: Poor medication adherence or inaccuracy in taking prescribed medications plays an important role in the recurrence or worsening of psychiatric symptoms in patients with schizophrenia, and the COVID-19 pandemic impacted their medication adherence with exacerbated symptoms or relapse. The use of mobile health services increased during the COVID-19 pandemic, and their role in improving mental health is becoming clearer. Objective: This study aimed to explore the effectiveness of a smartphone app (MedAdhere) on medication adherence and accuracy among patients with schizophrenia and to measure their psychiatric symptoms and cognitive functions. Methods: In this 12-week experimental study, participants were provided interventions with the MedAdhere app, and data were collected between June 2021 and September 2022. A total of 105 participants were randomly assigned to either the experimental or control groups. We used the Positive and Negative Syndrome Scale and Mini-Mental State Examination to measure the participants' psychiatric symptoms and cognitive functions. Generalized estimating equations were used for data analysis. Results: A total of 94 participants met the inclusion criteria and completed the protocol, and the medication adherence rate of the experimental group was 94.72\% (2785/2940) during the intervention. Psychotic symptoms (positive, negative, and general psychopathology symptoms) and cognitive functions (memory, language, and executive function) were significantly improved in the experimental group compared to the control group after the intervention. Conclusions: The MedAdhere app effectively and significantly improved medication adherence and, thereby, the psychiatric symptoms of patients with schizophrenia. This artificial intelligence assisted app could be extended to all patients who need to be reminded to take medication on schedule. Trial Registration: ClinicalTrials.gov NCT05892120; https://clinicaltrials.gov/study/NCT05892120 ", doi="10.2196/50806", url="https://mental.jmir.org/2023/1/e50806", url="http://www.ncbi.nlm.nih.gov/pubmed/38096017" } @Article{info:doi/10.2196/45453, author="Hsu, Che-Wei and Stahl, Daniel and Mouchlianitis, Elias and Peters, Emmanuelle and Vamvakas, George and Keppens, Jeroen and Watson, Miles and Schmidt, Nora and Jacobsen, Pamela and McGuire, Philip and Shergill, Sukhi and Kabir, Thomas and Hirani, Tia and Yang, Ziyang and Yiend, Jenny", title="User-Centered Development of STOP (Successful Treatment for Paranoia): Material Development and Usability Testing for a Digital Therapeutic for Paranoia", journal="JMIR Hum Factors", year="2023", month="Dec", day="8", volume="10", pages="e45453", keywords="cognitive bias modification", keywords="paranoia", keywords="content specificity", keywords="mental health", keywords="mobile app", keywords="mhealth", keywords="digital therapeutic", keywords="user-centered development", keywords="user", keywords="user-friendly app", keywords="paranoid", keywords="persecution", keywords="persecution complex", keywords="delusions", keywords="obsession", keywords="megalomania", keywords="monomania", keywords="psychosis", keywords="psychotic", abstract="Background: Paranoia is a highly debilitating mental health condition. One novel intervention for paranoia is cognitive bias modification for paranoia (CBM-pa). CBM-pa comes from a class of interventions that focus on manipulating interpretation bias. Here, we aimed to develop and evaluate new therapy content for CBM-pa for later use in a self-administered digital therapeutic for paranoia called STOP (``Successful Treatment of Paranoia''). Objective: This study aimed to (1) take a user-centered approach with input from living experts, clinicians, and academics to create and evaluate paranoia-relevant item content to be used in STOP and (2) engage with living experts and the design team from a digital health care solutions company to cocreate and pilot-test the STOP mobile app prototype. Methods: We invited 18 people with living or lived experiences of paranoia to create text exemplars of personal, everyday emotionally ambiguous scenarios that could provoke paranoid thoughts. Researchers then adapted 240 suitable exemplars into corresponding intervention items in the format commonly used for CBM training and created 240 control items for the purpose of testing STOP. Each item included newly developed, visually enriching graphics content to increase the engagement and realism of the basic text scenarios. All items were then evaluated for their paranoia severity and readability by living experts (n=8) and clinicians (n=7) and for their item length by the research team. Items were evenly distributed into six 40-item sessions based on these evaluations. Finalized items were presented in the STOP mobile app, which was co-designed with a digital health care solutions company, living or lived experts, and the academic team; user acceptance was evaluated across 2 pilot tests involving living or lived experts. Results: All materials reached predefined acceptable thresholds on all rating criteria: paranoia severity (intervention items: ?1; control items: ?1, readability: ?3, and length of the scenarios), and there was no systematic difference between the intervention and control group materials overall or between individual sessions within each group. For item graphics, we also found no systematic differences in users' ratings of complexity (P=.68), attractiveness (P=.15), and interest (P=.14) between intervention and control group materials. User acceptance testing of the mobile app found that it is easy to use and navigate, interactive, and helpful. Conclusions: Material development for any new digital therapeutic requires an iterative and rigorous process of testing involving multiple contributing groups. Appropriate user-centered development can create user-friendly mobile health apps, which may improve face validity and have a greater chance of being engaging and acceptable to the target end users. ", doi="10.2196/45453", url="https://humanfactors.jmir.org/2023/1/e45453", url="http://www.ncbi.nlm.nih.gov/pubmed/38064256" } @Article{info:doi/10.2196/50522, author="Buck, Benjamin and Wingerson, Mary and Whiting, Erica and Snyder, Jaime and Monroe-DeVita, Maria and Ben-Zeev, Dror", title="User-Centered Development of Bolster, an mHealth Intervention for Early Psychosis Caregivers: Needs Assessment, Prototyping, and Field Trial", journal="JMIR Ment Health", year="2023", month="Nov", day="30", volume="10", pages="e50522", keywords="caregiving", keywords="psychosis", keywords="mobile health", keywords="mHealth", keywords="user-centered design", keywords="mobile phone", keywords="artificial intelligence", keywords="AI", abstract="Background: Caregivers play a critical role in the treatment and recovery of youth and young adults at risk for psychosis. Caregivers often report feeling isolated, overwhelmed, and lacking in resources. Mobile health (mHealth) has the potential to provide scalable, accessible, and in-the-moment support to caregivers. To date, few if any mHealth resources have been developed specifically for this population. Objective: The aim of this study was to conduct user-centered design and testing of an mHealth intervention to support early psychosis caregivers. Methods: We conducted a multiphase user-centered development process to develop the Bolster mobile app. In phase 1, a total of 21 caregivers were recruited to participate in a qualitative needs assessment and respond to an initial prototype of the Bolster platform. Content analysis was used to identify key needs and design objectives, which guided the development of the Bolster mobile app. In phase 2, a total of 11 caregivers were recruited to participate in a 1-week field trial wherein they provided qualitative and quantitative feedback regarding the usability and acceptability of Bolster; in addition, they provided baseline and posttest assessments of the measures of distress, illness appraisals, and family communication. Results: In phase 1, participants identified psychoeducation, communication coaching, a guide to seeking services, and support for coping as areas to address. Live prototype interaction sessions led to multiple design objectives, including ensuring that messages from the platform were actionable and tailored to the caregiver experience, delivering messages in multiple modalities (eg, video and text), and eliminating a messaging-style interface. These conclusions were used to develop the final version of Bolster tested in the field trial. In phase 2, of the 11 caregivers, 10 (91\%) reported that they would use Bolster if they had access to it and would recommend it to another caregiver. They also reported marked changes in their appraisals of illness (Cohen d=0.55-0.68), distress (Cohen d=1.77), and expressed emotion (Cohen d=0.52). Conclusions: To our knowledge, this study is the first to design an mHealth intervention specifically for early psychosis caregivers. Preliminary data suggest that Bolster is usable, acceptable, and promising to improve key targets and outcomes. A future fully powered clinical trial will help determine whether mHealth can reduce caregiver burdens and increase engagement in services among individuals affected by psychosis. ", doi="10.2196/50522", url="https://mental.jmir.org/2023/1/e50522", url="http://www.ncbi.nlm.nih.gov/pubmed/38032692" } @Article{info:doi/10.2196/50998, author="Yu, Shirui and Wang, Ziyang and Nan, Jiale and Li, Aihua and Yang, Xuemei and Tang, Xiaoli", title="Potential Schizophrenia Disease-Related Genes Prediction Using Metagraph Representations Based on a Protein-Protein Interaction Keyword Network: Framework Development and Validation", journal="JMIR Form Res", year="2023", month="Nov", day="15", volume="7", pages="e50998", keywords="disease gene prediction", keywords="metagraph", keywords="protein representations", keywords="schizophrenia", keywords="keyword network", abstract="Background: Schizophrenia is a serious mental disease. With increased research funding for this disease, schizophrenia has become one of the key areas of focus in the medical field. Searching for associations between diseases and genes is an effective approach to study complex diseases, which may enhance research on schizophrenia pathology and lead to the identification of new treatment targets. Objective: The aim of this study was to identify potential schizophrenia risk genes by employing machine learning methods to extract topological characteristics of proteins and their functional roles in a protein-protein interaction (PPI)-keywords (PPIK) network and understand the complex disease--causing property. Consequently, a PPIK-based metagraph representation approach is proposed. Methods: To enrich the PPI network, we integrated keywords describing protein properties and constructed a PPIK network. We extracted features that describe the topology of this network through metagraphs. We further transformed these metagraphs into vectors and represented proteins with a series of vectors. We then trained and optimized our model using random forest (RF), extreme gradient boosting, light gradient boosting machine, and logistic regression models. Results: Comprehensive experiments demonstrated the good performance of our proposed method with an area under the receiver operating characteristic curve (AUC) value between 0.72 and 0.76. Our model also outperformed baseline methods for overall disease protein prediction, including the random walk with restart, average commute time, and Katz models. Compared with the PPI network constructed from the baseline models, complementation of keywords in the PPIK network improved the performance (AUC) by 0.08 on average, and the metagraph-based method improved the AUC by 0.30 on average compared with that of the baseline methods. According to the comprehensive performance of the four models, RF was selected as the best model for disease protein prediction, with precision, recall, F1-score, and AUC values of 0.76, 0.73, 0.72, and 0.76, respectively. We transformed these proteins to their encoding gene IDs and identified the top 20 genes as the most probable schizophrenia-risk genes, including the EYA3, CNTN4, HSPA8, LRRK2, and AFP genes. We further validated these outcomes against metagraph features and evidence from the literature, performed a features analysis, and exploited evidence from the literature to interpret the correlation between the predicted genes and diseases. Conclusions: The metagraph representation based on the PPIK network framework was found to be effective for potential schizophrenia risk genes identification. The results are quite reliable as evidence can be found in the literature to support our prediction. Our approach can provide more biological insights into the pathogenesis of schizophrenia. ", doi="10.2196/50998", url="https://formative.jmir.org/2023/1/e50998", url="http://www.ncbi.nlm.nih.gov/pubmed/37966892" } @Article{info:doi/10.2196/50193, author="He, Yupeng and Matsunaga, Masaaki and Li, Yuanying and Kishi, Taro and Tanihara, Shinichi and Iwata, Nakao and Tabuchi, Takahiro and Ota, Atsuhiko", title="Classifying Schizophrenia Cases by Artificial Neural Network Using Japanese Web-Based Survey Data: Case-Control Study", journal="JMIR Form Res", year="2023", month="Nov", day="15", volume="7", pages="e50193", keywords="artificial neural network", keywords="schizophrenia", keywords="prevalence", keywords="Japan", keywords="web-based survey", keywords="mental health", keywords="psychosis", keywords="machine learning", keywords="epidemiology", abstract="Background: In Japan, challenges were reported in accurately estimating the prevalence of schizophrenia among the general population. Retrieving previous studies, we investigated that patients with schizophrenia were more likely to experience poor subjective well-being and various physical, psychiatric, and social comorbidities. These factors might have great potential for precisely classifying schizophrenia cases in order to estimate the prevalence. Machine learning has shown a positive impact on many fields, including epidemiology, due to its high-precision modeling capability. It has been applied in research on mental disorders. However, few studies have applied machine learning technology to the precise classification of schizophrenia cases by variables of demographic and health-related backgrounds, especially using large-scale web-based surveys. Objective: The aim of the study is to construct an artificial neural network (ANN) model that can accurately classify schizophrenia cases from large-scale Japanese web-based survey data and to verify the generalizability of the model. Methods: Data were obtained from a large Japanese internet research pooled panel (Rakuten Insight, Inc) in 2021. A total of 223 individuals, aged 20-75 years, having schizophrenia, and 1776 healthy controls were included. Answers to the questions in a web-based survey were formatted as 1 response variable (self-report diagnosed with schizophrenia) and multiple feature variables (demographic, health-related backgrounds, physical comorbidities, psychiatric comorbidities, and social comorbidities). An ANN was applied to construct a model for classifying schizophrenia cases. Logistic regression (LR) was used as a reference. The performances of the models and algorithms were then compared. Results: The model trained by the ANN performed better than LR in terms of area under the receiver operating characteristic curve (0.86 vs 0.78), accuracy (0.93 vs 0.91), and specificity (0.96 vs 0.94), while the model trained by LR showed better sensitivity (0.63 vs 0.56). Comparing the performances of the ANN and LR, the ANN was better in terms of area under the receiver operating characteristic curve (bootstrapping: 0.847 vs 0.773 and cross-validation: 0.81 vs 0.72), while LR performed better in terms of accuracy (0.894 vs 0.856). Sleep medication use, age, household income, and employment type were the top 4 variables in terms of importance. Conclusions: This study constructed an ANN model to classify schizophrenia cases using web-based survey data. Our model showed a high internal validity. The findings are expected to provide evidence for estimating the prevalence of schizophrenia in the Japanese population and informing future epidemiological studies. ", doi="10.2196/50193", url="https://formative.jmir.org/2023/1/e50193", url="http://www.ncbi.nlm.nih.gov/pubmed/37966882" } @Article{info:doi/10.2196/44194, author="Tully, M. Laura and Nye, E. Kathleen and Ereshefsky, Sabrina and Tryon, L. Valerie and Hakusui, Komei Christopher and Savill, Mark and Niendam, A. Tara", title="Incorporating Community Partner Perspectives on eHealth Technology Data Sharing Practices for the California Early Psychosis Intervention Network: Qualitative Focus Group Study With a User-Centered Design Approach", journal="JMIR Hum Factors", year="2023", month="Nov", day="14", volume="10", pages="e44194", keywords="attitude", keywords="content analysis", keywords="data sharing", keywords="eHealth", keywords="ethic", keywords="focus group", keywords="health information exchange", keywords="mental health", keywords="perspective", keywords="preference", keywords="psychosis", keywords="psychotic", keywords="qualitative data", abstract="Background: Increased use of eHealth technology and user data to drive early identification and intervention algorithms in early psychosis (EP) necessitates the implementation of ethical data use practices to increase user acceptability and trust. Objective: First, the study explored EP community partner perspectives on data sharing best practices, including beliefs, attitudes, and preferences for ethical data sharing and how best to present end-user license agreements (EULAs). Second, we present a test case of adopting a user-centered design approach to develop a EULA protocol consistent with community partner perspectives and priorities. Methods: We conducted an exploratory, qualitative, and focus group--based study exploring mental health data sharing and privacy preferences among individuals involved in delivering or receiving EP care within the California Early Psychosis Intervention Network. Key themes were identified through a content analysis of focus group transcripts. Additionally, we conducted workshops using a user-centered design approach to develop a EULA that addresses participant priorities. Results: In total, 24 participants took part in the study (14 EP providers, 6 clients, and 4 family members). Participants reported being receptive to data sharing despite being acutely aware of widespread third-party sharing across digital domains, the risk of breaches, and motives hidden in the legal language of EULAs. Consequently, they reported feeling a loss of control and a lack of protection over their data. Participants indicated these concerns could be mitigated through user-level control for data sharing with third parties and an understandable, transparent EULA, including multiple presentation modalities, text at no more than an eighth-grade reading level, and a clear definition of key terms. These findings were successfully integrated into the development of a EULA and data opt-in process that resulted in 88.1\% (421/478) of clients who reviewed the video agreeing to share data. Conclusions: Many of the factors considered pertinent to informing data sharing practices in a mental health setting are consistent among clients, family members, and providers delivering or receiving EP care. These community partners' priorities can be successfully incorporated into developing EULA practices that can lead to high voluntary data sharing rates. ", doi="10.2196/44194", url="https://humanfactors.jmir.org/2023/1/e44194", url="http://www.ncbi.nlm.nih.gov/pubmed/37962921" } @Article{info:doi/10.2196/48634, author="Fisher, Melissa and Etter, Kevin and Murray, Aimee and Ghiasi, Neelu and LaCross, Kristin and Ramsay, Ian and Currie, Ariel and Fitzpatrick, Karrie and Biagianti, Bruno and Schlosser, Danielle and Loewy, Rachel and Vinogradov, Sophia", title="The Effects of Remote Cognitive Training Combined With a Mobile App Intervention on Psychosis: Double-Blind Randomized Controlled Trial", journal="J Med Internet Res", year="2023", month="Nov", day="13", volume="25", pages="e48634", keywords="schizophrenia", keywords="psychosis", keywords="cognitive training", keywords="motivation", keywords="mobile intervention", keywords="mobile phone", abstract="Background: Impairments in cognition and motivation are core features of psychosis and strong predictors of social and occupational functioning. Accumulating evidence indicates that cognitive deficits in psychosis can be improved by computer-based cognitive training programs; however, barriers include access and adherence to cognitive training exercises. Limited evidence-based methods have been established to enhance motivated behavior. In this study, we tested the effects of web-based targeted cognitive and social cognitive training (TCT) delivered in conjunction with an innovative digital smartphone app called Personalized Real-Time Intervention for Motivational Enhancement (PRIME). The PRIME app provides users with a motivational coach to set personalized goals and secure social networking for peer support. Objective: This study investigated whether deficits in cognition and motivation in people with a psychosis spectrum disorder (N=100) can be successfully addressed with 30 hours of TCT+PRIME as compared with 30 hours of a computer games control condition (CG) plus PRIME (CG+PRIME). Here, we describe our study procedures, the feasibility and acceptability of the intervention, and the results on all primary outcomes. Methods: In this double-blind randomized controlled trial, English-speaking participants completed all cognitive training, PRIME activities, and assessments remotely. Participants completed a diagnostic interview and remote cognitive, clinical, and self-report measures at baseline, posttraining, and at a 6-month follow-up. Results: This study included participants from 27 states across the United States and 8 countries worldwide. The study population was 58\% (58/100) female, with a mean age of 33.77 (SD 10.70) years. On average, participants completed more than half of the cognitive training regimen (mean 18.58, SD 12.47 hours of training), and logged into the PRIME app 4.71 (SD 1.58) times per week. The attrition rate of 22\% (22/100) was lower than that reported in our previous studies on remote cognitive training. The total sample showed significant gains in global cognition (P=.03) and attention (P<.001). The TCT+PRIME participants showed significantly greater gains in emotion recognition (P<.001) and global cognition at the trend level (P=.09), although this was not statistically significant, relative to the CG+PRIME participants. The total sample also showed significant improvements on multiple indices of motivation (P=.02-0.05), in depression (P=.04), in positive symptoms (P=.04), and in negative symptoms at a trend level (P=.09), although this was not statistically significant. Satisfaction with the PRIME app was rated at 7.74 (SD 2.05) on a scale of 1 to 10, with higher values indicating more satisfaction. Conclusions: These results demonstrate the feasibility and acceptability of remote cognitive training combined with the PRIME app and that this intervention can improve cognition, motivation, and symptoms in individuals with psychosis. TCT+PRIME appeared more effective in improving emotion recognition and global cognition than CG+PRIME. Future analyses will test the relationship between hours of cognitive training completed; PRIME use; and changes in cognition, motivation, symptoms, and functioning. Trial Registration: ClinicalTrials.gov NCT02782442; https://clinicaltrials.gov/study/NCT02782442 ", doi="10.2196/48634", url="https://www.jmir.org/2023/1/e48634", url="http://www.ncbi.nlm.nih.gov/pubmed/37955951" } @Article{info:doi/10.2196/46491, author="Green, B. James and Rodriguez, Joey and Keshavan, Matcheri and Lizano, Paulo and Torous, John", title="Implementing Technologies to Enhance Coordinated Specialty Care Framework: Implementation Outcomes From a Development and Usability Study", journal="JMIR Form Res", year="2023", month="Oct", day="3", volume="7", pages="e46491", keywords="psychosis", keywords="digital health", keywords="digital mental health", keywords="coordinated specialty care", keywords="digital navigator", keywords="clinical high risk", keywords="schizophrenia", keywords="implementation science", keywords="technology", keywords="mobile phone", abstract="Background: Coordinated specialty care (CSC) has demonstrated efficacy in improving outcomes in individuals at clinical high risk for psychosis and individuals with first-episode psychosis. Given the limitations of scalability and staffing needs, the augmentation of services using digital mental health interventions (DMHIs) may be explored to help support CSC service delivery. Objective: In this study, we aimed to understand the methods to implement and support technology in routine CSC and offered insights from a quality improvement study assessing the implementation outcomes of DMHIs in CSC. Methods: Patients and clinicians including psychiatrists, therapists, and supported education and employment specialists from a clinical-high-risk-for-psychosis clinic (Center for Early Detection Assessment and Response to Risk [CEDAR]) and a first-episode--psychosis clinic (Advancing Services for Psychosis Integration and Recovery [ASPIRE]) participated in a quality improvement project exploring the feasibility of DMHIs following the Access, Alignment, Connection, Care, and Scalability framework to implement mindLAMP, a flexible and evidenced-based DMHI. Digital navigators were used at each site to assist clinicians and patients in implementing mindLAMP. To explore the differences in implementation outcomes associated with the app format, a menu-style format was delivered at CEDAR, and a modular approach was used at ASPIRE. Qualitative baseline and follow-up data were collected to assess the specific implementation outcomes. Results: In total, 5 patients (ASPIRE: n=3, 60\%; CEDAR: n=2, 40\%) were included: 3 (60\%) White individuals, 2 (40\%) male and 2 (40\%) female patients, and 1 (20\%) transgender man, with a mean age of 19.6 (SD 2.05) years. Implementation outcome data revealed that patients and clinicians demonstrated high accessibility, acceptability, interest, and belief in the sustainability of DMHIs. Clinicians and patients presented a wide range of interest in unique use cases of DMHI in CSC and expressed variable feasibility and appropriateness associated with nuanced barriers and needs. In addition, the results suggest that adoption, penetration, feasibility, and appropriateness outcomes were moderate and might continue to be explored and targeted. Conclusions: Implementation outcomes from this project suggest the need for a patient- and clinician-centered approach that is guided by digital navigators and provides versatility, autonomy, and structure. Leveraging these insights has the potential to build on growing research regarding the need for versatility, autonomy, digital navigator support, and structured applications. We anticipate that by continuing to research and improve implementation barriers impeding the adoption and penetration of DMHIs in CSC, accessibility and uptake of DMHIs will improve, therefore connecting patients to the demonstrated benefits of technology-augmented care. ", doi="10.2196/46491", url="https://formative.jmir.org/2023/1/e46491", url="http://www.ncbi.nlm.nih.gov/pubmed/37788066" } @Article{info:doi/10.2196/47769, author="Ajani, Arinola Atinuke and Olanrewaju, Olatunde Fatai and Oninla, Abimbola Olumayowa and Ibigbami, Olanrewaju and Mosaku, Kolawole Samuel and Onayemi, Emmanuel Olaniyi and Olasode, Olayinka", title="Psychodermatological Disorders in Patients With Primary Psychiatric Conditions: Cross-Sectional Study", journal="JMIR Dermatol", year="2023", month="Oct", day="2", volume="6", pages="e47769", keywords="affective disorders", keywords="anxiety, stress-related, and somatoform disorders", keywords="primary dermatological disorders with psychiatric co-morbidity", keywords="primary psychiatric disorders with dermatologic manifestations", keywords="primary psychiatric psychodermatoses", keywords="psychocutaneous disorders", keywords="psychophysiological disorders", keywords="schizophrenia", abstract="Background: Psychodermatological disorders (PDs) and their associations with mental health problems are one of the most frequent research themes in dermatology outpatient settings. Surprisingly, very few studies have been conducted to evaluate PDs among patients with primary psychiatric conditions. As such, the relationship between preexisting psychiatric conditions and comorbid PDs is underrepresented in the literature. Objective: This study examined the prevalence and distribution of PDs among adults with primary psychiatric conditions and determined their association with underlying psychiatric diagnoses. Methods: We conducted a cross-sectional analysis at a tertiary health care facility in southwestern Nigeria. Comorbid PDs were identified and classified using preexisting classification systems. A bivariate analysis was conducted to determine the association between PDs and underlying psychiatric conditions. The level of statistical significance was set at P<.05. Results: The study included 107 patients with mental health disorders, of whom 64 (59.8\%) were female. The mean age of the patients was 40.73 (SD 13.08) years. A total of 75 (75/107, 70\%) patients had at least one comorbid PD. The prevalence of PDs was highest in patients with affective disorders (15/20, 75\%) and least in those with schizophrenia (45/66, 68\%). PDs associated with delusions or hallucinations and somatoform symptoms were 9 and 13 times more frequent in patients with anxiety disorders compared to those with other psychiatric conditions (P=.01; odds ratio [OR] 9.88, 95\% CI 1.67-58.34 and P=.003; OR 13.13, 95\% CI 2.34-73.65), respectively. In contrast, patients with schizophrenia were significantly less likely to be diagnosed with dermatoses resulting from delusions or hallucinations (P=.002; OR 0.04, 95\% CI 0.00-0.75). A weak but significant negative association was also found between psychophysiological PDs and anxiety disorders (?=--0.236; P=.02). Conclusions: This study provides important insights into the overwhelming burden of psychodermatological conditions in patients with mental health disorders and specific associations with underlying psychiatric diagnosis. ", doi="10.2196/47769", url="https://derma.jmir.org/2023/1/e47769", url="http://www.ncbi.nlm.nih.gov/pubmed/37782534" } @Article{info:doi/10.2196/47722, author="Gleeson, John and Lin, Ashleigh and Koval, Peter and Hopkins, Liza and Denborough, Paul and Lederman, Reeva and Herrman, Helen and Bendall, Sarah and Eleftheriadis, Dina and Cotton, Sue and Perry, Yael and Kaess, Michael and Alvarez-Jimenez, Mario", title="Moderated Online Social Therapy for Carers of Early Psychosis Clients in Real-World Settings: Cluster Randomized Controlled Trial", journal="JMIR Ment Health", year="2023", month="Sep", day="6", volume="10", pages="e47722", keywords="first-episode psychosis", keywords="carers", keywords="eHealth", keywords="families", keywords="stress", keywords="psychosis", keywords="digital mental health intervention", keywords="web-based therapy", keywords="social therapy", abstract="Background: Family carers of youth recovering from early psychosis experience significant stress; however, access to effective family interventions is poor. Digital interventions provide a promising solution. Objective: Our objective was to evaluate across multiple Australian early psychosis services the effectiveness of a novel, web-based early psychosis intervention for carers. Methods: In this cluster randomized controlled trial conducted across multiple Australian early psychosis services, our digital moderated online social therapy for carers (Altitudes) plus enhanced family treatment as usual (TAU) was compared with TAU alone on the primary outcome of perceived stress and secondary outcomes including mental health symptoms and family variables at the 6-month follow-up. Results: Eighty-six caregivers were randomized and data were available for 74 young people in their care. Our primary hypothesis that carers randomized to Altitudes+TAU would report greater improvements in perceived stress at follow-up compared with carers randomized to TAU alone was not supported, with the TAU alone group showing more improvement. For secondary outcomes, the TAU alone group showed improved mindfulness over time. Regardless of group assignment, we observed improvements in satisfaction with life, quality of life, emotional overinvolvement, and burden of care. In contrast, hair cortisol concentration increased. Post hoc analyses revealed more contact with early psychosis services in the intervention group compared to TAU alone and that improvements in perceived stress and social support were associated with use of the intervention in the Altitudes+TAU group. In this study, 80\% (12/15) reported a positive experience with Altitudes and 93\% (14/15) would recommend it to others. Conclusions: Our trial did not show a treatment effect for Altitudes in perceived stress. However, our post hoc analysis indicated that the amount of use of Altitudes related to improvements in stress and social support. Additional design work is indicated to continue users' engagement and to significantly improve outcomes in problem-solving, communication, and self-care. Trial Registration: Australian and New Zealand Clinical Trials Registry ACTRN12617000942358; https://trialsearch.who.int/Trial2.aspx?TrialID=ACTRN12617000942358 ", doi="10.2196/47722", url="https://mental.jmir.org/2023/1/e47722", url="http://www.ncbi.nlm.nih.gov/pubmed/37672335" } @Article{info:doi/10.2196/42093, author="Zarbo, Cristina and Zamparini, Manuel and Nielssen, Olav and Casiraghi, Letizia and Rocchetti, Matteo and Starace, Fabrizio and de Girolamo, Giovanni and ", title="Comparing Adherence to the Experience Sampling Method Among Patients With Schizophrenia Spectrum Disorder and Unaffected Individuals: Observational Study From the Multicentric DiAPAson Project", journal="J Med Internet Res", year="2023", month="Jul", day="18", volume="25", pages="e42093", keywords="ecological momentary assessment", keywords="multicenter study", keywords="mobile application", keywords="mobile app", keywords="compliance", keywords="psychosis", abstract="Background: The Experience Sampling Method (ESM) is a valid method of remotely recording activities and mood, but the predictors of adherence to ESM in patients with Schizophrenia Spectrum Disorder (SSD) are not known. Studies on adherence are significant as they highlight the strengths and weaknesses of ESM-based study designs and allow the development of recommendations and practical guidelines for implementing future studies or treatment plans. Objective: The aim of this study was to compare the adherence to ESM in patients with SSD and unaffected control individuals, investigate their patterns, and report the predictors of adherence. Methods: In total, 131 patients with SSD (74 in residential facilities and 57 outpatients) and 115 unaffected control individuals were recruited at 10 different centers in Italy as part of the DiAPAson project. Demographic information, symptom severity, disability level, and level of function were recorded for the clinical sample. Participants were evaluated for daily time use and mood through a smartphone-based ESM 8 times a day for 7 consecutive days. Adherence was measured by the response rate to ESM notifications. Results were analyzed using the chi-square test, ANOVA, Kruskal-Wallis test, and Friedman test, and a logistic regression model. Results: The overall adherence rate in this study was 50\% for residents, 59\% for outpatients, and 78\% for unaffected control individuals. Indeed, patients with SSD had a lower rate of adherence to ESM than the unaffected control group (P?.001), independent of time slot, day of monitoring, or day of the week. No differences in adherence rates between weekdays and weekends were found among the 3 groups. The adherence rate was the lowest in the late evening time slot (8 PM to 12 AM) and days 6-7 of the study for both patients with SSD and unaffected control individuals. The adherence rate among patients with SSD was not predicted by sociodemographic characteristics, cognitive function, or other clinical features. A higher adherence rate (ie, ?70\%) among patients with SSD was predicted by higher collaboration skills (odds ratio [OR] 2.952; P=.046) and self-esteem (OR 3.394; P=.03), and lower positive symptom severity (OR 0.835; P=.04). Conclusions: Adherence to ESM prompts for both patients with SSD and unaffected control individuals decreased during late evening and after 6 days of monitoring. Higher self-esteem and collaboration skills predicted higher adherence to ESM among patients with SSD, while higher positive symptom scores predicted lower adherence rates. This study provides important information to guide protocols for future studies using ESM. Future clinical or research studies should set ESM monitoring to waking hours, limit the number of days of monitoring, select patients with more collaborative skills and avoid those with marked positive symptoms, provide intensive training sessions, and improve participants' self-confidence with technologies. International Registered Report Identifier (IRRID): RR2-10.1186/s12888-020-02588-y ", doi="10.2196/42093", url="https://www.jmir.org/2023/1/e42093", url="http://www.ncbi.nlm.nih.gov/pubmed/37463030" } @Article{info:doi/10.2196/44812, author="O'Sullivan, Shaunagh and van Berkel, Niels and Kostakos, Vassilis and Schmaal, Lianne and D'Alfonso, Simon and Valentine, Lee and Bendall, Sarah and Nelson, Barnaby and Gleeson, F. John and Alvarez-Jimenez, Mario", title="Understanding What Drives Long-term Engagement in Digital Mental Health Interventions: Secondary Causal Analysis of the Relationship Between Social Networking and Therapy Engagement", journal="JMIR Ment Health", year="2023", month="May", day="22", volume="10", pages="e44812", keywords="digital intervention", keywords="digital health", keywords="youth mental health", keywords="psychotic disorders", keywords="usage metrics", keywords="log data", keywords="social networking", abstract="Background: Low engagement rates with digital mental health interventions are a major challenge in the field. Multicomponent digital interventions aim to improve engagement by adding components such as social networks. Although social networks may be engaging, they may not be sufficient to improve clinical outcomes or lead users to engage with key therapeutic components. Therefore, we need to understand what components drive engagement with digital mental health interventions overall and what drives engagement with key therapeutic components. Objective: Horyzons was an 18-month digital mental health intervention for young people recovering from first-episode psychosis, incorporating therapeutic content and a private social network. However, it is unclear whether use of the social network leads to subsequent use of therapeutic content or vice versa. This study aimed to determine the causal relationship between the social networking and therapeutic components of Horyzons. Methods: Participants comprised 82 young people (16-27 years) recovering from first-episode psychosis. Multiple convergent cross mapping was used to test causality, as a secondary analysis of the Horyzons intervention. Multiple convergent cross mapping tested the direction of the relationship between each pair of social and therapeutic system usage variables on Horyzons, using longitudinal usage data. Results: Results indicated that the social networking aspects of Horyzons were most engaging. Posting on the social network drove engagement with all therapeutic components (r=0.06-0.36). Reacting to social network posts drove engagement with all therapeutic components (r=0.39-0.65). Commenting on social network posts drove engagement with most therapeutic components (r=0.11-0.18). Liking social network posts drove engagement with most therapeutic components (r=0.09-0.17). However, starting a therapy pathway led to commenting on social network posts (r=0.05) and liking social network posts (r=0.06), and completing a therapy action led to commenting on social network posts (r=0.14) and liking social network posts (r=0.15). Conclusions: The online social network was a key driver of long-term engagement with the Horyzons intervention and fostered engagement with key therapeutic components and ingredients of the intervention. Online social networks can be further leveraged to engage young people with therapeutic content to ensure treatment effects are maintained and to create virtuous cycles between all intervention components to maintain engagement. Trial Registration: Australian New Zealand Clinical Trials Registry: ACTRN12614000009617; https://www.australianclinicaltrials.gov.au/anzctr/trial/ACTRN12614000009617 ", doi="10.2196/44812", url="https://mental.jmir.org/2023/1/e44812", url="http://www.ncbi.nlm.nih.gov/pubmed/37213197" } @Article{info:doi/10.2196/44980, author="Jenkins, Matthew and Gardiner, Tracey and Pekepo, Crystal and Ramritu, P?yal and Drysdale, Briony and Every-Palmer, Susanna and Chinn, Victoria", title="Developing a System of Health Support for Young People Experiencing First-Episode Psychosis: Protocol for a Co-design Process", journal="JMIR Res Protoc", year="2023", month="May", day="2", volume="12", pages="e44980", keywords="psychosis", keywords="health", keywords="well-being", keywords="co-design", keywords="lived experience", keywords="early intervention", abstract="Background: People living with psychosis face a substantially increased risk of poor psychological well-being and physical health and premature mortality. Encouraging positive health behaviors from an early stage is crucial to the health and well-being of this population but is often overshadowed by symptom management within early intervention services. Objective: Experience-based co-design is a participant-centered approach that aims to combine service user narratives with service design methods to design systems of support for health and well-being. This study aims to use experience-based co-design principles to co-design a system that supports the health and well-being of young people experiencing first-episode psychosis (FEP), which considers the lived experience of these people within the context of early intervention services. We also aim to develop a set of principles to guide future systems to support the health and well-being of young people experiencing FEP. Methods: Up to 15 young people living with FEP aged 16 to 24 years who are service users of early intervention services in psychosis, their immediate support networks (family or friends), and health professionals involved with early intervention services in psychosis will be invited to participate in a series of co-design workshops. Data will be collected in various forms, including expressive forms (eg, art and spoken word) and traditional methods (interview transcription and surveys), with phenomenographic and thematic analyses being used to understand these data. Furthermore, the co-design process will draw upon indigenous (M?ori) knowledge and the lived experience of mental health services from the perspectives of the members of the research team. The co-design process will be evaluated in terms of acceptability from the perspective of service users via rating scales and interviews. The study will be conducted within the Lower North Island in Aotearoa New Zealand. Results: Data collection will be performed between August 2022 and February 2023. Drawing from extended consultations with service users and service providers, we have developed a robust co-design process with which we intend to collect rich qualitative and quantitative data. The results of this process will be used to create a system of support that can be immediately applied and as preliminary evidence for funding and resource applications to deliver and evaluate a ``full'' version of the co-designed system of support. Conclusions: The co-designed system of support and accompanying set of principles will offer a potentially impactful health and well-being intervention for young people experiencing FEP in Aotearoa New Zealand. Furthermore, making the co-design process transparent will further the field in terms of providing a blueprint for this form of participant-focused research. Trial Registration: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12622001323718; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=384775\&isReview=true International Registered Report Identifier (IRRID): DERR1-10.2196/44980 ", doi="10.2196/44980", url="https://www.researchprotocols.org/2023/1/e44980", url="http://www.ncbi.nlm.nih.gov/pubmed/37129953" } @Article{info:doi/10.2196/34147, author="Daemen, Maud and van Amelsvoort, Therese and and Reininghaus, Ulrich", title="Momentary Self-esteem as a Process Underlying the Association Between Childhood Trauma and Psychosis: Experience Sampling Study", journal="JMIR Ment Health", year="2023", month="Apr", day="5", volume="10", pages="e34147", keywords="psychosis", keywords="self-esteem", keywords="childhood trauma", keywords="childhood adversity", keywords="experience sampling method", keywords="ecological momentary assessment", abstract="Background: Exposure to childhood trauma is associated with an increased risk of developing and maintaining psychotic symptoms later in life. Self-esteem might be an important psychological process underlying the association between childhood trauma and psychosis, but there is only limited evidence to support this claim, especially in daily life. Objective: In this study, we aimed to investigate whether exposure to childhood trauma (physical, emotional, and sexual abuse and physical and emotional neglect) moderates the cross-sectional and temporal associations between self-esteem and psychotic experiences in patients with psychotic disorders, their first-degree relatives, and controls. Methods: We assessed momentary self-esteem and psychotic experiences in daily life using the experience sampling method in 139 patients with psychotic disorders, 118 first-degree relatives of patients with psychotic disorders, and 111 controls. Childhood trauma was measured using the Childhood Trauma Questionnaire. We fitted linear mixed models and added two-way and three-way interaction terms to test the hypotheses. Results: The association between momentary self-esteem and psychotic experiences in daily life was modified by prior exposure to high versus low levels of several types of childhood trauma, that is, physical ($\chi$22=24.9, family-wise error-corrected P<.001) and sexual abuse ($\chi$22=15.9, P<.001) and physical neglect ($\chi$22=116.7, P<.001). Specifically, momentary self-esteem was associated with more intense psychotic experiences in patients exposed to high versus low levels of physical neglect, in relatives exposed to high versus low levels of physical abuse, and in relatives and controls exposed to high versus low levels of sexual abuse. When investigating temporal order, the results showed no evidence that childhood trauma modified the temporal associations between self-esteem at tn-1 and psychotic experiences at tn or those between psychotic experiences at tn-1 and self-esteem at tn. Conclusions: The association between self-esteem and psychotic experiences in daily life was found to be stronger in those exposed to high versus low levels of several types of childhood trauma (ie, physical abuse, sexual abuse, and physical neglect). ", doi="10.2196/34147", url="https://mental.jmir.org/2023/1/e34147", url="http://www.ncbi.nlm.nih.gov/pubmed/37018034" } @Article{info:doi/10.2196/37293, author="Pennou, Antoine and Lecomte, Tania and Potvin, St{\'e}phane and Riopel, Gabrielle and V{\'e}zina, Camille and Villeneuve, Marie and Abdel-Baki, Amal and Khazaal, Yasser", title="A Mobile Health App (ChillTime) Promoting Emotion Regulation in Dual Disorders: Acceptability and Feasibility Pilot Study", journal="JMIR Form Res", year="2023", month="Jan", day="27", volume="7", pages="e37293", keywords="dual disorder", keywords="concomitant disorder", keywords="mental disorder", keywords="mental illness", keywords="satisfaction", keywords="mobile app", keywords="mHealth", keywords="mobile health", keywords="emotion regulation", keywords="distress management", keywords="substance use disorder", keywords="substance use", keywords="emotion", keywords="distress", keywords="mental health", keywords="acceptability", keywords="feasibility", keywords="psychosis", keywords="psychotic", keywords="schizophrenia", keywords="emotional health", keywords="pilot study", abstract="Background: A growing number of studies highlight the importance of emotion regulation in the treatment and recovery of individuals with psychosis and concomitant disorders such as substance use disorder (SUD), for whom access to integrated dual-disorder treatments is particularly difficult. In this context, dedicated smartphone apps may be useful tools to provide immediate support to individuals in need. However, few studies to date have focused on the development and assessment of apps aimed at promoting emotional regulation for people with psychosis. Objective: The aim of this study was to evaluate the feasibility, acceptability, and potential clinical impact of a dedicated app (ChillTime) for individuals with psychotic disorders and concurrent SUD. The app design process followed recommendations for reducing cognitive effort on a mobile app. A total of 20 coping strategies regrouped in four categories (behavioral, emotional, cognitive, spiritual) were included in the app. Methods: This open pilot study followed a pre-post design. After the initial assessment, researchers asked participants to use the app as part of their treatment over a 30-day period. Feasibility was determined by the frequency of use of the app and measured using the number of completed strategies. Acceptability was determined by measuring ease of use, ease of learning, satisfaction, and perceived utility at the end of the 30-day study period based on responses to satisfaction questionnaires. Clinical scales measuring emotion regulation, substance use (ie, type of substance, amount taken, and frequency of use), and various psychiatric symptoms were administered at the beginning and end of the 30-day period. Results: A total of 13 participants were recruited from two first-episode psychosis clinics in Montreal, Quebec, Canada. All participants were symptomatically stable, were between 18 and 35 years of age (mostly men; 70\% of the sample), and had a schizophrenia spectrum disorder with a comorbid substance use diagnosis. A total of 11 participants completed the study (attrition<20\%). Approximately half of the participants used the tool at least 33\% of the days (11-21 days). Cognitive and emotion-focused techniques were rated the highest in terms of usefulness and were the most frequently used. The majority of participants gave positive answers about the ease of use and the ease of learning the tool. A nonsignificant association of ChillTime use with negative symptoms and drug use was observed. No other statistically significant changes were observed. Conclusions: The ChillTime app showed good feasibility (approximately half of the participants used the tool at least 33\% of the days) and acceptability among people with schizophrenia spectrum disorder and SUD. Trends suggesting a potential impact on certain clinical outcomes will need to be replicated in larger-sample studies before any conclusion can be drawn. ", doi="10.2196/37293", url="https://formative.jmir.org/2023/1/e37293", url="http://www.ncbi.nlm.nih.gov/pubmed/36705963" } @Article{info:doi/10.2196/38065, author="Bond, Jessica and Kenny, Alexandra and Pinfold, Vanessa and Couperthwaite, Lisa and and Kabir, Thomas and Larkin, Michael and Beckley, Ariane and Rosebrock, Laina and Lambe, Sin{\'e}ad and Freeman, Daniel and Waite, Felicity and Robotham, Dan", title="A Safe Place to Learn: Peer Research Qualitative Investigation of gameChange Virtual Reality Therapy", journal="JMIR Serious Games", year="2023", month="Jan", day="16", volume="11", pages="e38065", keywords="peer research", keywords="lived experience", keywords="qualitative methods", keywords="interpretative phenomenological analysis", keywords="IPA", keywords="anxiety", keywords="psychosis", keywords="virtual reality", keywords="VR", keywords="cognitive therapy", keywords="automated", keywords="implementation", abstract="Background: Automated virtual reality (VR) therapy has the potential to substantially increase access to evidence-based psychological treatments. The results of a multicenter randomized controlled trial showed that gameChange VR cognitive therapy reduces the agoraphobic avoidance of people diagnosed with psychosis, especially for those with severe avoidance. Objective: We set out to use a peer research approach to explore participants' experiences with gameChange VR therapy. This in-depth experiential exploration of user experience may inform the implementation in clinical services and future VR therapy development. Methods: Peer-led semistructured remote interviews were conducted with 20 people with a diagnosis of psychosis who had received gameChange as part of the clinical trial (ISRCTN17308399). Data were analyzed using interpretative phenomenological analysis and template analyses. A multiperspectival approach was taken to explore subgroups. Credibility checks were conducted with the study Lived Experience Advisory Panel. Results: Participants reported the substantial impact of anxious avoidance on their lives before the VR intervention, leaving some of them housebound and isolated. Those who were struggling the most with agoraphobic avoidance expressed the most appreciation for, and gains from, the gameChange therapy. The VR scenarios provided ``a place to practise.'' Immersion within the VR scenarios triggered anxiety, yet participants were able to observe this and respond in different ways than usual. The ``security of knowing the VR scenarios are not real'' created a safe place to learn about fears. The ``balance of safety and anxiety'' could be calibrated to the individual. The new learning made in VR was ``taken into the real world'' through practice and distilling key messages with support from the delivery staff member. Conclusions: Automated VR can provide a therapeutic simulation that allows people diagnosed with psychosis to learn and embed new ways of responding to the situations that challenge them. An important process in anxiety reduction is enabling the presentation of stimuli that induce the original anxious fears yet allow for learning of safety. In gameChange, the interaction of anxiety and safety could be calibrated to provide a safe place to learn about fears and build confidence. This navigation of therapeutic learning can be successfully managed by patients themselves in an automated therapy, with staff support, that provides users with personalized control. The clinical improvements for people with severe anxious avoidance, the positive experience of VR, and the maintenance of a sense of control are likely to facilitate implementation. ", doi="10.2196/38065", url="https://games.jmir.org/2023/1/e38065", url="http://www.ncbi.nlm.nih.gov/pubmed/36645707" } @Article{info:doi/10.2196/39747, author="Nguyen, Cuong Viet and Lu, Nathaniel and Kane, M. John and Birnbaum, L. Michael and De Choudhury, Munmun", title="Cross-Platform Detection of Psychiatric Hospitalization via Social Media Data: Comparison Study", journal="JMIR Ment Health", year="2022", month="Dec", day="30", volume="9", number="12", pages="e39747", keywords="schizophrenia", keywords="mental health", keywords="machine learning", keywords="clinical informatics", keywords="social media", keywords="mobile phone", abstract="Background: Previous research has shown the feasibility of using machine learning models trained on social media data from a single platform (eg, Facebook or Twitter) to distinguish individuals either with a diagnosis of mental illness or experiencing an adverse outcome from healthy controls. However, the performance of such models on data from novel social media platforms unseen in the training data (eg, Instagram and TikTok) has not been investigated in previous literature. Objective: Our study examined the feasibility of building machine learning classifiers that can effectively predict an upcoming psychiatric hospitalization given social media data from platforms unseen in the classifiers' training data despite the preliminary evidence on identity fragmentation on the investigated social media platforms. Methods: Windowed timeline data of patients with a diagnosis of schizophrenia spectrum disorder before a known hospitalization event and healthy controls were gathered from 3 platforms: Facebook (254/268, 94.8\% of participants), Twitter (51/268, 19\% of participants), and Instagram (134/268, 50\% of participants). We then used a 3 {\texttimes} 3 combinatorial binary classification design to train machine learning classifiers and evaluate their performance on testing data from all available platforms. We further compared results from models in intraplatform experiments (ie, training and testing data belonging to the same platform) to those from models in interplatform experiments (ie, training and testing data belonging to different platforms). Finally, we used Shapley Additive Explanation values to extract the top predictive features to explain and compare the underlying constructs that predict hospitalization on each platform. Results: We found that models in intraplatform experiments on average achieved an F1-score of 0.72 (SD 0.07) in predicting a psychiatric hospitalization because of schizophrenia spectrum disorder, which is 68\% higher than the average of models in interplatform experiments at an F1-score of 0.428 (SD 0.11). When investigating the key drivers for divergence in construct validities between models, an analysis of top features for the intraplatform models showed both low predictive feature overlap between the platforms and low pairwise rank correlation (<0.1) between the platforms' top feature rankings. Furthermore, low average cosine similarity of data between platforms within participants in comparison with the same measurement on data within platforms between participants points to evidence of identity fragmentation of participants between platforms. Conclusions: We demonstrated that models built on one platform's data to predict critical mental health treatment outcomes such as hospitalization do not generalize to another platform. In our case, this is because different social media platforms consistently reflect different segments of participants' identities. With the changing ecosystem of social media use among different demographic groups and as web-based identities continue to become fragmented across platforms, further research on holistic approaches to harnessing these diverse data sources is required. ", doi="10.2196/39747", url="https://mental.jmir.org/2022/12/e39747", url="http://www.ncbi.nlm.nih.gov/pubmed/36583932" } @Article{info:doi/10.2196/39047, author="Richey, G. Anabel and Kovacs, Ildiko and Browne, Sara", title="Use of an Ingestible, Sensor-Based Digital Adherence System to Strengthen the Therapeutic Relationship in Serious Mental Illness", journal="JMIR Ment Health", year="2022", month="Dec", day="2", volume="9", number="12", pages="e39047", keywords="patient-physician relationship", keywords="ingestible sensor", keywords="mental health", keywords="serious mental illness", keywords="antipsychotic", keywords="medication adherence", keywords="digital adherence", keywords="therapy", keywords="digital intervention", keywords="digital mental health", doi="10.2196/39047", url="https://mental.jmir.org/2022/12/e39047", url="http://www.ncbi.nlm.nih.gov/pubmed/36459392" } @Article{info:doi/10.2196/41482, author="Stefancic, Ana and Rogers, Tyler R. and Styke, Sarah and Xu, Xiaoyan and Buchsbaum, Richard and Nossel, Ilana and Cabassa, J. Leopoldo and Stroup, Scott T. and Kimhy, David", title="Development of the First Episode Digital Monitoring mHealth Intervention for People With Early Psychosis: Qualitative Interview Study With Clinicians", journal="JMIR Ment Health", year="2022", month="Nov", day="4", volume="9", number="11", pages="e41482", keywords="first-episode psychosis", keywords="early psychosis", keywords="coordinated specialty care", keywords="mental health treatment", keywords="shared decision-making", keywords="mobile health", keywords="smartphone apps", keywords="qualitative", keywords="digital psychiatry", keywords="mobile phone", abstract="Background: Mobile health (mHealth) technologies have been used extensively in psychosis research. In contrast, their integration into real-world clinical care has been limited despite the broad availability of smartphone-based apps targeting mental health care. Most apps developed for treatment of individuals with psychosis have focused primarily on encouraging self-management skills of patients via practicing cognitive behavioral techniques learned during face-to-face clinical sessions (eg, challenging dysfunctional thoughts and relaxation exercises), reminders to engage in health-promoting activities (eg, exercising, sleeping, and socializing), or symptom monitoring. In contrast, few apps have sought to enhance the clinical encounter itself to improve shared decision-making (SDM) and therapeutic relationships with clinicians, which have been linked to positive clinical outcomes. Objective: This qualitative study sought clinicians' input to develop First Episode Digital Monitoring (FREEDoM), an app-based mHealth intervention. FREEDoM was designed to improve the quality, quantity, and timeliness of clinical and functional data available to clinicians treating patients experiencing first-episode psychosis (FEP) to enhance their therapeutic relationship and increase SDM. Methods: Following the app's initial development, semistructured qualitative interviews were conducted with 11 FEP treatment providers at 3 coordinated specialty care clinics to elicit input on the app's design, the data report for clinicians, and planned usage procedures. We then generated a summary template and conducted matrix analysis to systematically categorize suggested adaptations to the evidence-based intervention using dimensions of the Framework for Reporting Adaptations and Modifications?Enhanced (FRAME) and documented the rationale for adopting or rejecting suggestions. Results: The clinicians provided 31 suggestions (18 adopted and 13 rejected). Suggestions to add or refine the content were most common (eg, adding questions in the app). Adaptations to context were most often related to plans for implementing the intervention, how the reported data were displayed to clinicians, and with whom the reports were shared. Reasons for suggestions primarily included factors related to health narratives and priorities of the patients (eg, focus on the functional impact of symptoms vs their severity), providers' clinical judgment (eg, need for clinically relevant information), and organizations' mission and culture. Reasons for rejecting suggestions included requests for data and procedures beyond the intervention's scope, concerns regarding dilution of the intervention's core components, and concerns about increasing patient burden while using the app. Conclusions: FREEDoM focuses on a novel target for the deployment of mHealth technologies in the treatment of FEP patients---the enhancement of SDM and improvement of therapeutic relationships. This study illustrates the use of the FRAME, along with methods and tools for rapid qualitative analysis, to systematically track adaptations to the app as part of its development process. Such adaptations may contribute to enhanced acceptance of the intervention by clinicians and a higher likelihood of integration into clinical care. Trial Registration: ClinicalTrials.gov NCT04248517; https://tinyurl.com/tjuyxvv6 ", doi="10.2196/41482", url="https://mental.jmir.org/2022/11/e41482", url="http://www.ncbi.nlm.nih.gov/pubmed/36331539" } @Article{info:doi/10.2196/35837, author="Jones, Steven and Atanasova, Dimitrinka and Dodd, Susanna and Flowers, Susan and Rosala-Hallas, Anna and Robinson, Heather and Semino, Elena and Lobban, Fiona", title="Use of an Online Forum for Relatives of People With Psychosis and Bipolar Disorder: Mixed Methods Study", journal="JMIR Ment Health", year="2022", month="Oct", day="20", volume="9", number="10", pages="e35837", keywords="psychosis", keywords="bipolar disorder", keywords="relative", keywords="carer", keywords="mental health", keywords="forum", keywords="online", keywords="digital health", keywords="Relatives Education and Coping Toolkit", keywords="REACT", keywords="trial", abstract="Background: Relatives of people with psychosis or bipolar disorder experience high levels of distress but are typically not offered the support they need. Online peer forums may offer a solution, but knowledge about who uses them, how, and why is limited. This study reported on online forum use during the Relatives Education and Coping Toolkit (REACT) trial. Objective: We aimed to report who used the forum and why; how sociodemographic factors are associated with participation; the relationship among frequency, type of use, and outcomes; and how the forum was used. Methods: The relationships between key sociodemographic characteristics, levels of forum use, and distress were statistically analyzed. We used thematic and semantic analyses to understand the reasons for relatives joining the forum and the key topics initiated by them. We also used the University Centre for Computer Corpus Research on Language Semantic Analysis System to compare how relatives and REACT supporters (moderators) used the forum. Results: A total of 348 participants with full forum use data from REACT were included in this study. The forum was accessed by 59.4\% (207/348) of the relatives across the entire age range, with no significant associations between sociodemographic factors and forum participation, or between level or type of use and relatives' distress levels. Relatives joined the forum primarily to find people in similar circumstances, express concerns, and talk about stressful events. Relatives were most concerned about recent events, negative emotions linked to caring, experiences of conflict or threat, and concerns about suicide. These posts underscored both the challenges the relatives were facing and the fact that they felt safe sharing them in this context. Conclusions: Although only a proportion of REACT participants engaged actively with its forum, they were widely distributed across age and other sociodemographic groupings. Relatives used the forum for information, support, and guidance and to offer detailed information about their experiences. The topics raised highlighted the burden carried by relatives and the potential value of easy-access, moderated, peer-supported forums in helping relatives to manage the challenges they faced. ", doi="10.2196/35837", url="https://mental.jmir.org/2022/10/e35837", url="http://www.ncbi.nlm.nih.gov/pubmed/36264621" } @Article{info:doi/10.2196/36986, author="Lejeune, Alban and Robaglia, Benoit-Marie and Walter, Michel and Berrouiguet, Sofian and Lemey, Christophe", title="Use of Social Media Data to Diagnose and Monitor Psychotic Disorders: Systematic Review", journal="J Med Internet Res", year="2022", month="Sep", day="6", volume="24", number="9", pages="e36986", keywords="schizophrenia", keywords="psychotic disorders", keywords="psychiatric disorders", keywords="artificial intelligence", keywords="AI", keywords="machine learning", keywords="neural network", keywords="social media", abstract="Background: Schizophrenia is a disease associated with high burden, and improvement in care is necessary. Artificial intelligence (AI) has been used to diagnose several medical conditions as well as psychiatric disorders. However, this technology requires large amounts of data to be efficient. Social media data could be used to improve diagnostic capabilities. Objective: The objective of our study is to analyze the current capabilities of AI to use social media data as a diagnostic tool for psychotic disorders. Methods: A systematic review of the literature was conducted using several databases (PubMed, Embase, Cochrane, PsycInfo, and IEEE Xplore) using relevant keywords to search for articles published as of November 12, 2021. We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria to identify, select, and critically assess the quality of the relevant studies while minimizing bias. We critically analyzed the methodology of the studies to detect any bias and presented the results. Results: Among the 93 studies identified, 7 studies were included for analyses. The included studies presented encouraging results. Social media data could be used in several ways to care for patients with schizophrenia, including the monitoring of patients after the first episode of psychosis. We identified several limitations in the included studies, mainly lack of access to clinical diagnostic data, small sample size, and heterogeneity in study quality. We recommend using state-of-the-art natural language processing neural networks, called language models, to model social media activity. Combined with the synthetic minority oversampling technique, language models can tackle the imbalanced data set limitation, which is a necessary constraint to train unbiased classifiers. Furthermore, language models can be easily adapted to the classification task with a procedure called ``fine-tuning.'' Conclusions: The use of social media data for the diagnosis of psychotic disorders is promising. However, most of the included studies had significant biases; we therefore could not draw conclusions about accuracy in clinical situations. Future studies need to use more accurate methodologies to obtain unbiased results. ", doi="10.2196/36986", url="https://www.jmir.org/2022/9/e36986", url="http://www.ncbi.nlm.nih.gov/pubmed/36066938" } @Article{info:doi/10.2196/39519, author="Pollock Star, Ariel and Bachner, G. Yaacov and Cohen, Bar and Haglili, Ophir and O'Rourke, Norm", title="Social Media Use and Well-being With Bipolar Disorder During the COVID-19 Pandemic: Path Analysis", journal="JMIR Form Res", year="2022", month="Aug", day="18", volume="6", number="8", pages="e39519", keywords="bipolar disorder", keywords="COVID-19", keywords="life satisfaction", keywords="loneliness", keywords="social media use", keywords="social media", keywords="Facebook", keywords="social support", keywords="mental health", keywords="mental illness", keywords="mental disorder", keywords="social media advertising", keywords="advertising", keywords="advertisement", keywords="mania", keywords="hypo/mania", keywords="manic", keywords="depressive", keywords="depression", abstract="Background: Reliable and consistent social support is associated with the mental health and well-being of persons with severe mental illness, including bipolar disorder (BD). Yet the COVID-19 pandemic and associated social distancing measures (eg, shelter in place) reduced access to regular social contacts, while social media use (SMU) increased concomitantly. Little is currently known about associations between the well-being of adults with BD and different types of SMU (eg, passive and active). Objective: For this study, we had two goals. First, we report descriptive information regarding SMU by persons with BD during COVID-19 (all platforms). Specific to Facebook, we next developed and tested a hypothesized model to identify direct and indirect associations between BD symptoms, social support, loneliness, life satisfaction, and SMU. Responses were collected during the global spread of the Delta variant and prior/concurrent with the Omicron variant, 20 months after the World Health Organization declared COVID-19 a global pandemic. Methods: Over 8 weeks, we obtained responses from an international sample of 102 adults with BD using the Qualtrics online platform. Most had previously participated in the BADAS (Bipolar Affective Disorders and older Adults) Study (n=89, 87.3\%); the remainder were recruited specifically for this research (n=13, 2.7\%). The subsamples did not differ in age (t100=1.64; P=.10), gender ($\chi$22=0.2; P=.90), socioeconomic status ($\chi$26=9.9; P=.13), or time since BD diagnosis (t97=1.27; P=.21). Both were recruited using social media advertising micro-targeted to adults with BD. On average, participants were 53.96 (SD 13.22, range 20-77) years of age, they had completed 15.4 (SD 4.28) years of education, and were diagnosed with BD 19.6 (SD 10.31) years ago. Path analyses were performed to develop and test our hypothesized model. Results: Almost all participants (n=95, 93.1\%) reported having both Facebook and LinkedIn accounts; 91.2\% (n=93) reported regular use of either or both. During the pandemic, most (n=62, 60.8\%) reported accessing social media several times a day; 36.3\% (n=37) reported using social media more often since the emergence of COVID-19. Specific to Facebook, the model we hypothesized differed somewhat from what emerged. The resulting model suggests that symptoms of depression predict loneliness and, inversely, social support and life satisfaction. Social support predicts social Facebook use, whereas passive Facebook use predicts life satisfaction. Symptoms of depression emerged as indirect predictors of SMU via social support. Conclusions: Our findings suggest that the operational definition of passive-active SMU requires further analysis and refinement. In contrast to theory, passive Facebook use appears positively associated with well-being among certain populations. Longitudinal data collection over multiple points is required to identify associations between BD symptoms, SMU, and well-being over time. ", doi="10.2196/39519", url="https://formative.jmir.org/2022/8/e39519", url="http://www.ncbi.nlm.nih.gov/pubmed/35980726" } @Article{info:doi/10.2196/37346, author="Ferrari, Manuela and Iyer, Srividya and LeBlanc, Annie and Roy, Marc-Andr{\'e} and Abdel-Baki, Amal", title="A Rapid-Learning Health System to Support Implementation of Early Intervention Services for Psychosis in Quebec, Canada: Protocol", journal="JMIR Res Protoc", year="2022", month="Jul", day="19", volume="11", number="7", pages="e37346", keywords="rapid-learning health system", keywords="early intervention for psychosis", keywords="measurement-based care", keywords="real-time electronic data capturing", keywords="patient-oriented research", keywords="knowledge translation", keywords="mobile phone", abstract="Background: Given the strong evidence of their effectiveness, early intervention services (EIS) for psychosis are being widely implemented. However, heterogeneity in the implementation of essential components remains an ongoing challenge. Rapid-learning health systems (RLHSs) that embed data collection in clinical settings for real-time learning and continuous quality improvement can address this challenge. Therefore, we implemented an RLHS in 11 EIS in Quebec, Canada. Objective: This project aims to determine the feasibility and acceptability of implementing an RLHS in EIS and assess its impact on compliance with standards for essential EIS components. Methods: Funding for this project was secured in July 2019, and ethics approval was received in December 2019. The implementation of this RLHS involves 6 iterative phases: external and internal scan, design, implementation, evaluation, adjustment, and dissemination. Multiple stakeholder groups (service users, families, clinicians, researchers, decision makers, and provincial EIS associations) are involved in all phases. Meaningful EIS quality indicators (eg, satisfaction and timeliness of response to referrals) were selected based on a literature review, provincial guidelines, and stakeholder consensus on prioritization of indicators. A digital infrastructure was designed and deployed comprising a user-friendly interface for routinely collecting data from programs; a digital terminal and mobile app to collect feedback from service users and families regarding care received, health, and quality of life; and data analytic, visualization, and reporting functionalities to provide participating programs with real-time feedback on their ongoing performance in relation to standards and to other programs, including tailored recommendations. Our community of practice conducts activities, leveraging insights from data to build program capacity while continuously aligning their practices with standards and best practices. Guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework, we are collecting quantitative and qualitative data on the reach, effectiveness, adoption, implementation, and maintenance of our RLHS for evaluating its impacts. Results: Phase 1 (identifying RLHS indicators for EIS based on a literature synthesis, a survey, and consensus meetings with all stakeholder groups) and phase 2 (developing and implementing the RLHS digital infrastructure) are completed (September 2019 to May 2020). Phases 3 to 5 have been ongoing (June 2020 to June 2022). Continuous data collection through the RLHS data capture platforms and real-time feedback to all stakeholders are deployed. Phase 6 will be implemented in 2022 to assess the impact of the RLHS using the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework with quantitative and qualitative data. Conclusions: This project will yield valuable insights into the implementation of RLHS in EIS, offering preliminary evidence of its acceptability, feasibility, and impacts on program-level outcomes. The findings will refine our RLHS further and advance approaches that use data, stakeholder voices, and collaborative learning to improve outcomes and quality in services for psychosis. International Registered Report Identifier (IRRID): DERR1-10.2196/37346 ", doi="10.2196/37346", url="https://www.researchprotocols.org/2022/7/e37346", url="http://www.ncbi.nlm.nih.gov/pubmed/35852849" } @Article{info:doi/10.2196/30230, author="Franco, H. Olivia and Calkins, E. Monica and Giorgi, Salvatore and Ungar, H. Lyle and Gur, E. Raquel and Kohler, G. Christian and Tang, X. Sunny", title="Feasibility of Mobile Health and Social Media--Based Interventions for Young Adults With Early Psychosis and Clinical Risk for Psychosis: Survey Study", journal="JMIR Form Res", year="2022", month="Jul", day="8", volume="6", number="7", pages="e30230", keywords="social media", keywords="psychosis", keywords="clinical high risk", keywords="technology", keywords="digital health", abstract="Background: Digital technology, the internet, and social media are increasingly investigated as promising means for monitoring symptoms and delivering mental health treatment. These apps and interventions have demonstrated preliminary acceptability and feasibility, but previous reports suggest that access to technology may still be limited among individuals with psychotic disorders relative to the general population. Objective: We evaluated and compared access to and use of technology and social media in young adults with psychotic disorders (PD), young adults with clinical risk for psychosis (CR), and psychosis-free youths (PF). Methods: Participants were recruited through a coordinated specialty care clinic dedicated toward early psychosis as well as ongoing studies. We surveyed 21 PD, 23 CR, and 15 PF participants regarding access to technology and use of social media, specifically Facebook and Twitter. Statistical analyses were conducted in R. Categorical variables were compared among groups using Fisher exact test, continuous variables were compared using 1-way ANOVA, and multiple linear regressions were used to evaluate for covariates. Results: Access to technology and social media were similar among PD, CR, and PF participants. Individuals with PD, but not CR, were less likely to post at a weekly or higher frequency compared to PF individuals. We found that decreased active social media posting was unique to psychotic disorders and did not occur with other psychiatric diagnoses or demographic variables. Additionally, variation in age, sex, and White versus non-White race did not affect posting frequency. Conclusions: For young people with psychosis spectrum disorders, there appears to be no ``technology gap'' limiting the implementation of digital and mobile health interventions. Active posting to social media was reduced for individuals with psychosis, which may be related to negative symptoms or impairment in social functioning. ", doi="10.2196/30230", url="https://formative.jmir.org/2022/7/e30230", url="http://www.ncbi.nlm.nih.gov/pubmed/35802420" } @Article{info:doi/10.2196/29725, author="Hardy, Amy and Ward, Thomas and Emsley, Richard and Greenwood, Kathryn and Freeman, Daniel and Fowler, David and Kuipers, Elizabeth and Bebbington, Paul and Garety, Philippa", title="Bridging the Digital Divide in Psychological Therapies: Observational Study of Engagement With the SlowMo Mobile App for Paranoia in Psychosis", journal="JMIR Hum Factors", year="2022", month="Jul", day="1", volume="9", number="3", pages="e29725", keywords="paranoia", keywords="psychosis", keywords="digital health", keywords="apps", keywords="human-centered design", keywords="user experience", keywords="adherence", keywords="engagement", keywords="therapy", abstract="Background: Marginalized groups are more likely to experience problems with technology-related access, motivation, and skills. This is known as the ``digital divide.'' Technology-related exclusion is a potential barrier to the equitable implementation of digital health. SlowMo therapy was developed with an inclusive, human-centered design to optimize accessibility and bridge the ``digital divide.'' SlowMo is an effective, blended digital psychological therapy for paranoia in psychosis. Objective: This study explores the ``digital divide'' and mobile app engagement in the SlowMo randomized controlled trial. Methods: Digital literacy was assessed at baseline, and a multidimensional assessment of engagement (ie, adherence [via system analytics and self-report] and self-reported user experience) was conducted at 12 weeks after therapy. Engagement was investigated in relation to demographics (ie, gender, age, ethnicity, and paranoia severity). Results: Digital literacy data demonstrated that technology use and confidence were lower in Black people and older people (n=168). The engagement findings indicated that 80.7\% (96/119) of therapy completers met the a priori analytics adherence criteria. However, analytics adherence did not differ by demographics. High rates of user experience were reported overall (overall score: mean 75\%, SD 17.1\%; n=82). No differences in user experience were found for ethnicity, age, or paranoia severity, although self-reported app use, enjoyment, and usefulness were higher in women than in men. Conclusions: This study identified technology-related inequalities related to age and ethnicity, which did not influence engagement with SlowMo, suggesting that the therapy design bridged the ``digital divide.'' Intervention design may moderate the influence of individual differences on engagement. We recommend the adoption of inclusive, human-centered design to reduce the impact of the ``digital divide'' on therapy outcomes. Trial Registration: ISRCTN Registry ISRCTN32448671; https://www.isrctn.com/ISRCTN32448671 ", doi="10.2196/29725", url="https://humanfactors.jmir.org/2022/3/e29725", url="http://www.ncbi.nlm.nih.gov/pubmed/35776506" } @Article{info:doi/10.2196/40147, author="Eckardt, Peter Jens", title="Urgency for Digital Technologies to Support Caregivers. Comment on ``Telehealth-Based Psychoeducation for Caregivers: The Family Intervention in Recent-Onset Schizophrenia Treatment Study''", journal="JMIR Ment Health", year="2022", month="Jun", day="30", volume="9", number="6", pages="e40147", keywords="schizophrenia", keywords="family psychoeducation", keywords="caregiver burden", keywords="recent-onset schizophrenia", keywords="telehealth", doi="10.2196/40147", url="https://mental.jmir.org/2022/6/e40147", url="http://www.ncbi.nlm.nih.gov/pubmed/35771612" } @Article{info:doi/10.2196/35336, author="Jongkind, Amy and Hendriks, Michelle and Grootens, Koen and Beekman, F. Aartjan T. and van Meijel, Berno", title="Evaluation of a Collaborative Care Program for Patients With Treatment-Resistant Schizophrenia: Protocol for a Multiple Case Study", journal="JMIR Res Protoc", year="2022", month="Jun", day="13", volume="11", number="6", pages="e35336", keywords="treatment-resistant schizophrenia", keywords="collaborative care", keywords="recovery", keywords="personalized care", keywords="clozapine", keywords="lifestyle", keywords="peer support", keywords="shared decision-making", keywords="motivational interviewing", keywords="nurse-led intervention", abstract="Background: Approximately one-third of all patients with schizophrenia are treatment resistant. Worldwide, undertreatment with clozapine and other effective treatment options exist for people with treatment-resistant schizophrenia (TRS). In this respect, it appears that regular health care models do not optimally fit this patient group. The Collaborative Care (CC) model has proven to be effective for patients with severe mental illness, both in primary care and in specialized mental health care facilities. The key principles of the CC model are that both patients and informal caregivers are part of the treatment team, that a structured treatment plan is put in place with planned evaluations by the team, and that the treatment approach is multidisciplinary in nature and uses evidence-based interventions. We developed a tailored CC program for patients with TRS. Objective: In this paper, we provide an overview of the research design for a potential study that seeks to gain insight into both the process of implementation and the preliminary effects of the CC program for patients with TRS. Moreover, we aim to gain insight into the experiences of professionals, patients, and informal caregivers with the program. Methods: This study will be underpinned by a multiple case study design (N=20) that uses a mixed methods approach. These case studies will focus on an Early Psychosis Intervention Team and 2 Flexible Assertive Community treatment teams in the Netherlands. Data will be collected from patient records as well as through questionnaires, individual interviews, and focus groups. Patient recruitment commenced from October 2020. Results: Recruitment of participants commenced from October 2020, with the aim of enrolling 20 patients over 2 years. Data collection will be completed by the end of 2023, and the results will be published once all data are available for reporting. Conclusions: The research design, framed within the process of developing and testing innovative interventions, is discussed in line with the aims of the study. The limitations in clinical practice and specific consequences of this study are explained. International Registered Report Identifier (IRRID): DERR1-10.2196/35336 ", doi="10.2196/35336", url="https://www.researchprotocols.org/2022/6/e35336", url="http://www.ncbi.nlm.nih.gov/pubmed/35700002" } @Article{info:doi/10.2196/36758, author="Archie, Suzanne and Palaniyappan, Lena and Olagunju, T. Andrew and Johnson, Natasha and Kozloff, Nicole and Sadeh, Elham and Bardell, Andrea and Baines, Alexandra and Anderson, K. Kelly and Ayonrinde, Oyedeji and Ferrari, Manuela", title="Insights About Cannabis and Psychosis Using Video Games for Young People With a First Episode of Psychosis, Particularly Those From Black Racialized Communities: Protocol for a Mixed Methods Study", journal="JMIR Res Protoc", year="2022", month="May", day="20", volume="11", number="5", pages="e36758", keywords="first-episode psychosis", keywords="cannabis use", keywords="knowledge translation", keywords="Black youth", keywords="video games", abstract="Background: Cannabis use disorder among young people with a first episode of psychosis contributes to relapse, hospitalization, and impaired functioning. However, few studies have examined what young people with early phase psychosis, particularly those from Black racialized communities, understand or appreciate about this relationship, even though they may be at risk. There are no formally tested knowledge translation strategies that disseminate these research findings for young people with emerging psychosis from Black racialized communities. Objective: This study aims to conceptualize what young people with early phase psychosis/cannabis use disorder understand about the relationship between cannabis and psychosis, focusing on people from racialized backgrounds. This study also aims to assess whether the knowledge translation product, the ``Back to Reality Series,'' increases awareness of the impact of cannabis use on psychosis from the perspectives of young people with emerging psychosis and cannabis use disorder from Black African and Caribbean communities. Methods: Qualitative analysis will reveal themes from qualitative interviews about cannabis and psychosis from the perspectives of young people with emerging psychosis and cannabis use disorder from Black African and Caribbean communities. Perceptions before and after exposure to the Back to Reality Series will be qualitatively analyzed. A control game will be used for comparison, and scores on a quiz after playing the Back to Reality Series will be quantitatively analyzed to establish whether the Back to Reality Series raises awareness of the effects of cannabis on psychosis. An advisory council involving young people from Black communities, family members, and clinicians will bring community perspectives to this research. Results: We began recruiting participants for this study in September 2021. We will complete data collection on demographic and clinical factors, qualitative interviews, and quantitative assessments of the Back to Reality Series. Conclusions: The voices of young people from racialized backgrounds will generate preliminary data to inform early psychosis programs, addressing cannabis use in this population. The findings may advance the use of a new knowledge translation product that deals with gaps in knowledge about cannabis use for people experiencing early phase psychosis, particularly those from racialized communities. International Registered Report Identifier (IRRID): DERR1-10.2196/36758 ", doi="10.2196/36758", url="https://www.researchprotocols.org/2022/5/e36758", url="http://www.ncbi.nlm.nih.gov/pubmed/35389874" } @Article{info:doi/10.2196/36541, author="Arigo, Danielle and Torous, John", title="Development of a Mobile Assessment Tool for Understanding Social Comparison Processes Among Individuals With Schizophrenia: Two-Phase Survey Study", journal="JMIR Form Res", year="2022", month="May", day="2", volume="6", number="5", pages="e36541", keywords="schizophrenia", keywords="social comparison", keywords="mobile assessment", keywords="smartphone app", keywords="variability", abstract="Background: Digital tools may help to address social deficits in schizophrenia, particularly those that engage social comparison processes (ie, evaluating oneself relative to others). Yet, little is known about social comparison processes in schizophrenia or how best to capture between- versus within-person variability, which is critical to engaging comparisons in digital interventions. Objective: The goals of this pilot study were to (1) better understand affective responses to social comparisons among individuals with schizophrenia, relative to healthy controls, using a validated global self-report measure; and (2) test a new brief, mobile assessment of affective responses to social comparison among individuals with schizophrenia, relative to the full measure. This study was conducted in 2 phases. Methods: We first compared self-reported affective responses to social comparisons between individuals with schizophrenia (n=39) and healthy controls (n=38) using a traditional self-report measure, at 2 time points. We examined the temporal stability in responses and differences between groups. We then evaluated the performance of brief, mobile assessment of comparison responses among individuals with schizophrenia, completed over 12 weeks (n=31). Results: Individuals with schizophrenia showed greater variability in affective responses to social comparison than controls on traditional measures and completed an average of 7.46 mobile assessments over 12 weeks. Mobile assessments captured within-person variability in affective responses in the natural environment (intraclass correlation coefficients of 0.40-0.60). Average scores for mobile assessments were positively correlated with responses to traditional measures. Conclusions: Affective responses to social comparison vary both between and within individuals with schizophrenia and capturing this variability via smartphone surveys shows some evidence of feasibility. As affective variability is a potential indicator of poor outcomes among individuals with mental health conditions, in the future, a brief, mobile assessment of affective responses to social comparisons may be useful for screening among individuals with schizophrenia. Further research on this process is needed to identify when specific comparison messaging may be most effective in digital interventions and could suggest new therapeutic targets for illnesses such as schizophrenia. ", doi="10.2196/36541", url="https://formative.jmir.org/2022/5/e36541", url="http://www.ncbi.nlm.nih.gov/pubmed/35499856" } @Article{info:doi/10.2196/32492, author="Mueser, T. Kim and Achtyes, D. Eric and Gogate, Jagadish and Mancevski, Branislav and Kim, Edward and Starr, Lynn H.", title="Telehealth-Based Psychoeducation for Caregivers: The Family Intervention in Recent-Onset Schizophrenia Treatment Study", journal="JMIR Ment Health", year="2022", month="Apr", day="15", volume="9", number="4", pages="e32492", keywords="schizophrenia", keywords="family psychoeducation", keywords="caregiver burden", keywords="recent-onset schizophrenia", keywords="telehealth", abstract="Background: Schizophrenia is a lifelong illness that requires long-term treatment and caregiving. Family psychoeducation (FP) has been shown to lessen caregiver burden, improve caregiver functioning, and improve outcomes in patients. However, the impact of FP delivered specifically to caregivers on patient outcomes has not been well explored, particularly for early schizophrenia. Furthermore, there is a lack of research examining the benefits of telehealth-based psychoeducation for caregivers on either patient or caregiver outcomes. Objective: The Family Intervention in Recent-Onset Schizophrenia Treatment (FIRST) study is a randomized controlled trial of patients with schizophrenia spectrum disorders and their caregivers, which is designed to evaluate the effect of telehealth-based, caregiver-focused, study-provided psychoeducation versus usual care (UC) on patient treatment failure (TF). The impact of study-provided psychoeducation on caregiver burden is also investigated. Methods: Eligible patients and their designated caregivers were randomly assigned to either the study-provided psychoeducation (?16 sessions of telehealth-based psychoeducation over 6 months) or UC group, stratified by antipsychotic treatment (paliperidone palmitate or oral antipsychotic). The major TF events (ie, psychiatric hospitalization or intervention, arrest or incarceration, and suicide attempts) were assessed at 3, 6, and 12 months after baseline. A proportional means model using mean cumulative function was used to assess between-group differences in the mean cumulative number of TF events over 12 months. Caregiver burden was assessed using the Involvement Evaluation Questionnaire and 12-item Short Form Health Survey. Results: A total of 148 pairs of participants were enrolled in the study, of whom 96 (64.9\%) patients and 94 (63.5\%) caregivers completed the 12-month follow-up. The mean number of sessions in the study-provided psychoeducation group was 7.7 (SD 5.9). No differences were observed between the study-provided psychoeducation and UC groups in patient outcomes (rates of TF: 70\% vs 67\%; P=.90) or measures of caregiver burden (assessment of caregiver distress and physical and mental health). However, post hoc analyses revealed lower relapse rates in patients who received paliperidone palmitate than in those who received oral antipsychotics at all time points. Although the FIRST study did not meet the primary end point, several key lessons were identified to inform future caregiver-focused, telehealth-based FP interventions. Lack of study-provided psychoeducation, focus on caregiver-only intervention, difficulties with enrollment, and caregiver--treatment team coordination may have affected the outcomes of the FIRST study. Conclusions: Key insights from the FIRST study suggest the potential importance of supporting sufficient caregiver engagement; communication between clinicians, patients, and family members regarding treatment plans; and solidifying the relationship between clinicians providing psychoeducation to the caregiver and patient treatment team. Trial Registration: ClinicalTrials.gov NCT02600741; http://clinicaltrials.gov/ct2/show/NCT02600741 ", doi="10.2196/32492", url="https://mental.jmir.org/2022/4/e32492", url="http://www.ncbi.nlm.nih.gov/pubmed/35436231" } @Article{info:doi/10.2196/28135, author="Wilhelm, Kay and Handley, Tonelle and McHugh, Catherine and Lowenstein, David and Arrold, Kristy", title="The Quality of Internet Websites for People Experiencing Psychosis: Pilot Expert Assessment", journal="JMIR Form Res", year="2022", month="Apr", day="15", volume="6", number="4", pages="e28135", keywords="psychosis", keywords="schizophrenia", keywords="DISCERN", keywords="quality", keywords="websites", keywords="mental health", keywords="Australia", keywords="health information", keywords="patients", keywords="consumers", keywords="accessibility", keywords="patient empowerment", keywords="reliability", keywords="eHealth", keywords="electronic health", keywords="website", abstract="Background: Clinicians need to be able to assess the quality of the available information to aid clinical decision-making. The internet has become an important source of health information for consumers and their families. Objective: This study aimed to rate the quality of websites with psychosis-related information (to provide clinicians with a basis for recommending material to guide clinical decision-making with consumers and their families), using a validated instrument as well as a purpose-developed checklist, and consider improvement in quality over a 4-year period. Methods: Two measures of website quality were used: the DISCERN scale and the Psychosis Website Quality Checklist (PWQC). Terms related to psychosis, including ``psychotic,'' ``psychosis,'' ``schizophrenia,'' ``delusion,'' and ``hallucination,'' were entered into Google, and the first 25 results were analyzed. In total, 6 raters with varying health professional backgrounds were used to evaluate the websites across two time points: January-March 2014 and January-March 2018. Results: Of the 25 websites rated, only the 6 highest ranked websites achieved a DISCERN score, indicating that they were of ``good'' quality (51-62 out of a possible 75), while the mean score of the websites (mean 43.96, SD 12.08) indicated an overall ``fair'' quality. The PWQC revealed that websites scored highly on ``availability and usability'' (mean 16.82, SD 3.96) but poorly on ``credibility'' (mean 20.99, SD 6.68), ``currency'' (mean 5.16, SD 2.62), and ``breadth and accuracy'' (mean 77.87, SD 23.20). Most sites lacked information about early intervention, recreational drug use and suicide risk, with little change in content over time. Stating an editorial or review process on the website (found in 56\% of websites) was significantly associated with a higher quality score on both scales (the DISCERN scale, P=.002; the PWQC, P=.006). Conclusions: The information on the internet available for clinicians to recommend to people affected by psychosis tended to be of ``fair'' quality. While higher-quality websites exist, it is generally not easy way to assess this on face value. Evidence of an editorial or review process was one indicator of website quality. While sites generally provided basic clinical information, most lacked material addressing weighing up risks and benefits of medication and alternatives, the role of coercive treatment and other more contentious issues. Insufficient emphasis is placed on detailed information on early intervention and importance of lifestyle modifications or how families and friends can contribute. These are likely to be the very answers that consumers and carers are seeking and this gap contributes to unmet needs among this group. We suggest that clinicians should be aware of what is available and where there are gaps. ", doi="10.2196/28135", url="https://formative.jmir.org/2022/4/e28135", url="http://www.ncbi.nlm.nih.gov/pubmed/35436206" } @Article{info:doi/10.2196/31006, author="Zhou, Joanne and Lamichhane, Bishal and Ben-Zeev, Dror and Campbell, Andrew and Sano, Akane", title="Predicting Psychotic Relapse in Schizophrenia With Mobile Sensor Data: Routine Cluster Analysis", journal="JMIR Mhealth Uhealth", year="2022", month="Apr", day="11", volume="10", number="4", pages="e31006", keywords="schizophrenia", keywords="psychotic relapse", keywords="machine learning", keywords="clustering", keywords="mobile phone", keywords="routine", keywords="Gaussian mixture models", keywords="partition around medoids", keywords="dynamic time warping", keywords="balanced random forest", abstract="Background: Behavioral representations obtained from mobile sensing data can be helpful for the prediction of an oncoming psychotic relapse in patients with schizophrenia and the delivery of timely interventions to mitigate such relapse. Objective: In this study, we aim to develop clustering models to obtain behavioral representations from continuous multimodal mobile sensing data for relapse prediction tasks. The identified clusters can represent different routine behavioral trends related to daily living of patients and atypical behavioral trends associated with impending relapse. Methods: We used the mobile sensing data obtained from the CrossCheck project for our analysis. Continuous data from six different mobile sensing-based modalities (ambient light, sound, conversation, acceleration, etc) obtained from 63 patients with schizophrenia, each monitored for up to a year, were used for the clustering models and relapse prediction evaluation. Two clustering models, Gaussian mixture model (GMM) and partition around medoids (PAM), were used to obtain behavioral representations from the mobile sensing data. These models have different notions of similarity between behaviors as represented by the mobile sensing data, and thus, provide different behavioral characterizations. The features obtained from the clustering models were used to train and evaluate a personalized relapse prediction model using balanced random forest. The personalization was performed by identifying optimal features for a given patient based on a personalization subset consisting of other patients of similar age. Results: The clusters identified using the GMM and PAM models were found to represent different behavioral patterns (such as clusters representing sedentary days, active days but with low communication, etc). Although GMM-based models better characterized routine behaviors by discovering dense clusters with low cluster spread, some other identified clusters had a larger cluster spread, likely indicating heterogeneous behavioral characterizations. On the other hand, PAM model-based clusters had lower variability of cluster spread, indicating more homogeneous behavioral characterization in the obtained clusters. Significant changes near the relapse periods were observed in the obtained behavioral representation features from the clustering models. The clustering model-based features, together with other features characterizing the mobile sensing data, resulted in an F2 score of 0.23 for the relapse prediction task in a leave-one-patient-out evaluation setting. The obtained F2 score was significantly higher than that of a random classification baseline with an average F2 score of 0.042. Conclusions: Mobile sensing can capture behavioral trends using different sensing modalities. Clustering of the daily mobile sensing data may help discover routine and atypical behavioral trends. In this study, we used GMM-based and PAM-based cluster models to obtain behavioral trends in patients with schizophrenia. The features derived from the cluster models were found to be predictive for detecting an oncoming psychotic relapse. Such relapse prediction models can be helpful in enabling timely interventions. ", doi="10.2196/31006", url="https://mhealth.jmir.org/2022/4/e31006", url="http://www.ncbi.nlm.nih.gov/pubmed/35404256" } @Article{info:doi/10.2196/35600, author="Fonseka, N. Lakshan and Woo, P. Benjamin K.", title="Wearables in Schizophrenia: Update on Current and Future Clinical Applications", journal="JMIR Mhealth Uhealth", year="2022", month="Apr", day="7", volume="10", number="4", pages="e35600", keywords="wearables", keywords="smartwatch", keywords="schizophrenia", keywords="digital phenotype", keywords="wearable", keywords="mHealth", keywords="mobile health", keywords="review", keywords="clinical application", keywords="clinical utility", keywords="clinical use", keywords="literature search", keywords="diagnosis", keywords="prevention", doi="10.2196/35600", url="https://mhealth.jmir.org/2022/4/e35600", url="http://www.ncbi.nlm.nih.gov/pubmed/35389361" } @Article{info:doi/10.2196/29211, author="O'Sullivan, Shaunagh and Schmaal, Lianne and D'Alfonso, Simon and Toenders, Jo Yara and Valentine, Lee and McEnery, Carla and Bendall, Sarah and Nelson, Barnaby and Gleeson, F. John and Alvarez-Jimenez, Mario", title="Characterizing Use of a Multicomponent Digital Intervention to Predict Treatment Outcomes in First-Episode Psychosis: Cluster Analysis", journal="JMIR Ment Health", year="2022", month="Apr", day="7", volume="9", number="4", pages="e29211", keywords="digital intervention", keywords="digital health", keywords="youth mental health", keywords="psychotic disorders", keywords="clustering", keywords="usage metrics", keywords="log data", keywords="social networking", abstract="Background: Multicomponent digital interventions offer the potential for tailored and flexible interventions that aim to address high attrition rates and increase engagement, an area of concern in digital mental health. However, increased flexibility in use makes it difficult to determine which components lead to improved treatment outcomes. Objective: This study aims to identify user profiles on Horyzons, an 18-month digital relapse prevention intervention for first-episode psychosis that incorporates therapeutic content and social networking, along with clinical, vocational, and peer support, and to examine the predictive value of these user profiles for treatment outcomes. A secondary objective is to compare each user profile with young people receiving treatment as usual (TAU). Methods: Participants comprised 82 young people (aged 16-27 years) with access to Horyzons and 84 receiving TAU, recovering from first-episode psychosis. In addition, 6-month use data from the therapy and social networking components of Horyzons were used as features for K-means clustering for joint trajectories to identify user profiles. Social functioning, psychotic symptoms, depression, and anxiety were assessed at baseline and 6-month follow-up. General linear mixed models were used to examine the predictive value of user profiles for treatment outcomes and between each user profile with TAU. Results: A total of 3 user profiles were identified based on the following system use metrics: low use, maintained use of social components, and maintained use of both therapy and social components. The maintained therapy and social group showed improvements in social functioning (F2,51=3.58; P=.04), negative symptoms (F2,51=4.45; P=.02), and overall psychiatric symptom severity (F2,50=3.23; P=.048) compared with the other user profiles. This group also showed improvements in social functioning (F1,62=4.68; P=.03), negative symptoms (F1,62=14.61; P<.001), and overall psychiatric symptom severity (F1,63=5.66; P=.02) compared with the TAU group. Conversely, the maintained social group showed increases in anxiety compared with the TAU group (F1,57=7.65; P=.008). No differences were found between the low use group and the TAU group on treatment outcomes. Conclusions: Continued engagement with both therapy and social components might be key in achieving long-term recovery. Maintained social use and low use outcomes were broadly comparable with TAU, emphasizing the importance of maintaining engagement for improved treatment outcomes. Although the social network may be a key ingredient to increase sustained engagement, as users engaged with this more consistently, it should be leveraged as a tool to engage young people with therapeutic content to bring about social and clinical benefits. ", doi="10.2196/29211", url="https://mental.jmir.org/2022/4/e29211", url="http://www.ncbi.nlm.nih.gov/pubmed/35389351" } @Article{info:doi/10.2196/33526, author="Jankowski, Samantha and Ferreira, Kathleen and Mascayano, Franco and Donovan, Effy and Rahim, Reanne and Birnbaum, L. Michael and Yum-Chan, Sabrina and Medoff, Deborah and Marcogliese, Bethany and Fang, Lijuan and Nicholson, Terriann and Dixon, Lisa", title="A Serious Game for Young People With First Episode Psychosis (OnTrack>The Game): Qualitative Findings of a Randomized Controlled Trial", journal="JMIR Ment Health", year="2022", month="Apr", day="6", volume="9", number="4", pages="e33526", keywords="video gaming", keywords="internet", keywords="recovery", keywords="schizophrenia", keywords="psychosis", keywords="clinicians", keywords="mobile phone", abstract="Background: Several studies have shown the benefits of coordinated specialty care (CSC) for individuals with first episode psychosis; however, pathways to care are marred by lack of knowledge, stigma, and difficulties with treatment engagement. Serious games or video interventions may provide a way to address these factors. Objective: This study focuses on qualitative results of a randomized controlled trial comparing OnTrack>The Game (OTG) with recovery videos (RVs) on engagement, stigma, empowerment, hope, recovery, and understanding of psychosis in clients receiving CSC. Clinicians are also interviewed regarding their perceptions of the interventions and suggestions for improvement. Methods: A total of 16 clients aged 16-30 years, with first episode psychosis attending a CSC program in New York State, and 9 clinicians participated in the qualitative interviews. Interviews were analyzed using the rapid identification of themes from audio recordings method. Results: For clients, themes included relatability of game content, an increased sense of hope and the possibility of recovery, decreased self-stigma and public stigma, increased understanding of the importance of social support, and increased empowerment in the OTG group. Clinicians had a preference for RV and provided suggestions for dissemination and implementation. Conclusions: Themes that may help inform future research in this area, particularly regarding dissemination and implementation of OTG and RV, emerged. Trial Registration: ClinicalTrials.gov NCT03390491; https://clinicaltrials.gov/ct2/show/NCT03390491 ", doi="10.2196/33526", url="https://mental.jmir.org/2022/4/e33526", url="http://www.ncbi.nlm.nih.gov/pubmed/35384847" } @Article{info:doi/10.2196/34323, author="Lu, Di Justin and Gotesman, D. Ryan and Varghese, Shawn and Fleming, Patrick and Lynde, W. Charles", title="Treatments for Primary Delusional Infestation: Systematic Review", journal="JMIR Dermatol", year="2022", month="Mar", day="30", volume="5", number="1", pages="e34323", keywords="delusional infestation", keywords="Morgellons disease", keywords="treatment", keywords="delusional parasitosis", keywords="atypical", keywords="typical", keywords="antipsychotic", keywords="SSRI", keywords="delusion", keywords="rare disorder", keywords="systematic review", keywords="pharmacology", keywords="pharmacological", keywords="psychiatric", keywords="dermatology", keywords="dermatologist", keywords="drug", abstract="Background: Delusional infestation, also known as Ekbom syndrome, is a rare delusional disorder characterized by the fixed belief that one is infested with parasites, worms, insects, or other organisms. Although delusional infestation is a psychiatric condition, patients often consult dermatologists with skin findings, and it is currently unclear what treatments are recommended for this disorder. Objective: We aimed to systematically review and describe the treatment and management of patients presenting with primary delusional infestation. Methods: A systematic search was conducted using Ovid on MEDLINE, Embase, PsycINFO, and the Cochrane Register of Clinical Trials. Relevant data, including treatment, dosage, response, adherence, and side effects, were extracted and analyzed. Results: A total of 15 case series were included, comprising 280 patients (mean age 53.3 years, 65.4\% female) with delusional infestation. Overall, aripiprazole had the highest complete remission rate at 79\% (11/14), although this was limited to 14 patients. Among drug classes, selective serotonin reuptake inhibitors were the most effective with a 79\% (11/14) complete remission rate and 43\% (9/21) partial remission rate in patients with comorbid depression, anxiety, or trichotillomania. First-generation antipsychotics and second-generation antipsychotics had similar complete remission rates (56/103, 54.4\% vs 56/117, 47.9\%, respectively) and partial remission rates (36/103, 35\% vs 41/117, 35\%, respectively). Conclusions: Due to the rarity of delusional infestation, we only found 15 case series. However, we found that first-generation antipsychotics appear to be similar in effectiveness to second-generation antipsychotics for the treatment of primary delusional infestation. Larger studies and randomized controlled trials are needed to evaluate the efficacy of pharmacological therapy for delusional infestation. Trial Registration: PROSPERO CRD42020198161; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=198161 ", doi="10.2196/34323", url="https://derma.jmir.org/2022/1/e34323", url="http://www.ncbi.nlm.nih.gov/pubmed/37632851" } @Article{info:doi/10.2196/28502, author="Schroeder, H. Alexandra and Bogie, M. Bryce J. and Rahman, T. Tabassum and Th{\'e}rond, Alexandra and Matheson, Hannah and Guimond, Synthia", title="Feasibility and Efficacy of Virtual Reality Interventions to Improve Psychosocial Functioning in Psychosis: Systematic Review", journal="JMIR Ment Health", year="2022", month="Feb", day="18", volume="9", number="2", pages="e28502", keywords="auditory verbal hallucinations", keywords="cognitive remediation", keywords="functional outcomes", keywords="neurocognition", keywords="paranoia", keywords="psychosis", keywords="schizophrenia", keywords="social skills", keywords="virtual reality (VR)", keywords="vocational skills", abstract="Background: Functional recovery in psychosis remains a challenge despite current evidence-based treatment approaches. To address this problem, innovative interventions using virtual reality (VR) have recently been developed. VR technologies have enabled the development of realistic environments in which individuals with psychosis can receive psychosocial treatment interventions in more ecological settings than traditional clinics. These interventions may therefore increase the transfer of learned psychosocial skills to real-world environments, thereby promoting long-term functional recovery. However, the overall feasibility and efficacy of such interventions within the psychosis population remain unclear. Objective: This systematic review aims to investigate whether VR-based psychosocial interventions are feasible and enjoyable for individuals with psychosis, synthesize current evidence on the efficacy of VR-based psychosocial interventions for psychosis, and identify the limitations in the current literature to guide future research. Methods: This research followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Literature searches were conducted in PubMed and PsycINFO in May 2021. We searched for peer-reviewed English articles that used a psychosocial intervention with a VR component. Participants in the included studies were diagnosed with schizophrenia, schizoaffective disorder, or another psychotic disorder. The included studies were divided into four categories as follows: cognitive remediation interventions, social skills interventions, vocational skills interventions, and auditory verbal hallucinations and paranoia interventions. The risk of bias assessment was performed for each study. Results: A total of 18 studies were included in this systematic review. Of these 18 studies, 4 (22\%) studies used a cognitive remediation intervention, 4 (22\%) studies used a social skills intervention, 3 (17\%) studies used a vocational skills intervention, and 7 (39\%) studies implemented an intervention aimed at improving auditory verbal hallucinations or paranoia. A total of 745 individuals with psychosis were included in the study. All the studies that evaluated feasibility showed that VR-based psychosocial interventions were feasible and enjoyable for individuals with psychosis. The preliminary evidence on efficacy included in this review suggests that VR-based psychosocial interventions can improve cognitive, social, and vocational skills in individuals with psychosis. VR-based interventions may also improve the symptoms of auditory verbal hallucinations and paranoia. The skills that participants learned through these interventions were durable, transferred into real-world environments, and led to improved functional outcomes, such as autonomy, managing housework, and work performance. Conclusions: VR-based interventions may represent a novel and efficacious approach for improving psychosocial functioning in psychosis. Therefore, VR-based psychosocial interventions represent a promising adjunctive therapy for the treatment of psychosis, which may be used to improve psychosocial skills, community functioning, and quality of life. ", doi="10.2196/28502", url="https://mental.jmir.org/2022/2/e28502", url="http://www.ncbi.nlm.nih.gov/pubmed/35179501" } @Article{info:doi/10.2196/31565, author="Garc{\'i}a-Estela, Aitana and Cantillo, Jordi and Angarita-Osorio, Natalia and Mur-Mil{\`a}, Estanislao and Anmella, Gerard and P{\'e}rez, V{\'i}ctor and Vieta, Eduard and Hidalgo-Mazzei, Diego and Colom, Francesc", title="Real-world Implementation of a Smartphone-Based Psychoeducation Program for Bipolar Disorder: Observational Ecological Study", journal="J Med Internet Res", year="2022", month="Feb", day="2", volume="24", number="2", pages="e31565", keywords="bipolar disorder", keywords="psychoeducation", keywords="smartphone", keywords="app", keywords="SIMPLe", keywords="Intervention", keywords="mobile phone", abstract="Background: SIMPLe is an internet?delivered self?management mobile app for bipolar disorder (BD) designed to combine technology with evidence-based interventions and facilitate access to psychoeducational content. The SIMPLe app was launched to the real world to make it available worldwide within the context of BD treatment. Objective: The main aims of this study are as follows: to describe app use, engagement, and retention rates based on server data; to identify patterns of user retention over the first 6-month follow-up of use; and to explore potential factors contributing to discontinuation of app use. Methods: This was an observational ecological study in which we pooled available data from a real-world implementation of the SIMPLe app. Participation was open on the project website, and the data-collection sources were a web-based questionnaire on clinical data and treatment history administered at inclusion and at 6 months, subjective data gathered through continuous app use, and the use patterns captured by the app server. Characteristics and engagement of regular users, occasional users, and no users were compared using 2-tailed t tests or analysis of variance or their nonparametric equivalent. Survival analysis and risk functions were applied to regular users' data to examine and compare use and user retention. In addition, a user evaluation analysis was performed based on satisfaction, perceived usefulness, and reasons to discontinue app use. Results: We included 503 participants with data collected between 2016 and 2018, of whom 77.5\% (n=390) used the app. Among the app users, 44.4\% (173/390) completed the follow-up assessment, and data from these participants were used in our analyses. Engagement declined gradually over the first 6 months of use. The probability of retention of the regular users after 1 month of app use was 67.4\% (263/390; 95\% CI 62.7\%-72.4\%). Age (P=.002), time passed since illness onset (P<.001), and years since diagnosis of BD (P=.048) correlate with retention duration. In addition, participants who had been diagnosed with BD for longer used the app on more days (mean 97.73, SD 69.15 days; P=.002) than those who had had a more recent onset (mean 66.49, SD 66.18 days; P=.002) or those who had been diagnosed more recently (mean 73.45, SD 66 days; P=.01). Conclusions: The user retention rate of the app decreased rapidly after each month until reaching only one-third of the users at 6 months. There exists a strong association between age and app engagement of individuals with BD. Other variables such as years lived with BD, diagnosis of an anxiety disorder, and taking antipsychotics seem relevant as well. Understanding these associations can help in the definition of the most suitable user profiles for predicting trends of engagement, optimization of app prescription, and management. ", doi="10.2196/31565", url="https://www.jmir.org/2022/2/e31565", url="http://www.ncbi.nlm.nih.gov/pubmed/35107440" } @Article{info:doi/10.2196/27781, author="Batchelor, Rachel and Gulshan, Sarah and Shritharan, Halpana and Williams, Elen and Henderson, Claire and Gillard, Steve and Woodham, A. Luke and Cornelius, Victoria and Elkes, Jack and Sin, Jacqueline", title="Perceived Acceptability and Experiences of a Digital Psychoeducation and Peer Support Intervention (COPe-support): Interview Study With Carers Supporting Individuals With Psychosis", journal="J Med Internet Res", year="2022", month="Feb", day="2", volume="24", number="2", pages="e27781", keywords="eHealth", keywords="family carers", keywords="qualitative research", keywords="psychosis", keywords="peer support", keywords="web-based psychoeducation", keywords="mobile phone", abstract="Background: Web-based mental health interventions offer a novel, accessible, and self-paced approach to care delivery to family carers (ie, relatives and close friends who support a loved one with psychosis). We coproduced COPe-support (Carers fOr People with Psychosis e-support), a psychoeducational intervention delivered via an enriched web-based learning environment with network support from professionals and peers. In addition to the rigorous investigation of the effectiveness of COPe-support on the well-being of carers and mental health outcomes, it is imperative to understand the experiences of using the web-based intervention by carers and its associated web-based implementation and facilitation strategies. Objective: This study aims to explore the experiences of carers and perceived acceptability of COPe-support and its different components, how carers found engagement with COPe-support affected their own well-being and caregiving, and the ideas of carers for improving COPe-support and its delivery to inform any future wider implementation. Methods: We conducted a qualitative study, individually interviewing 35 carers, following their use of COPe-support for 8 months through a web-based, randomized controlled trial across England. A semistructured guide with open-ended questions was used to explore the experiences of carers and perceived acceptability of the intervention and their ideas to improve the provision. All interviews were conducted remotely through mobile phones or internet communication media, audio recorded and transcribed verbatim. We used a thematic analysis framework to analyze the data. Results: Three key themes were identified: remote, flexible, and personalized support; impacts on well-being and outlook on caregiving; and future implementation and integration with existing services. Overall, carers found COPe-support a flexible source of knowledge and support from professionals and peers that they could personalize to suit their own needs and convenience. Participants described gaining self-confidence, hope, and a sense of connectivity with others in a similar situation, which helped ameliorate isolation and perceived stigma. Most importantly, COPe-support promoted self-care among the carers themselves. Participants' experiences, use, and activity on COPe-support varied greatly and differed among carers of various ages and levels of computer literacy. Conclusions: Nearly all participants had a positive experience with COPe-support and supported its wider implementation as a beneficial adjunctive support resource for carers in the future. Any future scale-up of such an intervention needs to consider feedback from carers and suggestions for further improvement. These included having more graphics and audiovisual content materials, improving the navigation, and building in more interactional and customization options to suit various user styles, such as emoji reactions, live web-based chat, opting in and out of updates, and choosing the frequency of reminders. To ensure successful implementation, we should also consider factors pertinent to reaching more carers and integrating the web-based resources with other conventional services. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN) 89563420; https://www.isrctn.com/ISRCTN89563420 International Registered Report Identifier (IRRID): RR2-10.1186/s12888-020-02528-w ", doi="10.2196/27781", url="https://www.jmir.org/2022/2/e27781", url="http://www.ncbi.nlm.nih.gov/pubmed/35107439" } @Article{info:doi/10.2196/27641, author="Porffy, Alexandra Lilla and Mehta, A. Mitul and Patchitt, Joel and Boussebaa, Celia and Brett, Jack and D'Oliveira, Teresa and Mouchlianitis, Elias and Shergill, S. Sukhi", title="A Novel Virtual Reality Assessment of Functional Cognition: Validation Study", journal="J Med Internet Res", year="2022", month="Jan", day="26", volume="24", number="1", pages="e27641", keywords="virtual reality", keywords="virtual reality assessment", keywords="cognition", keywords="functional cognition", keywords="functional capacity", keywords="neuropsychological testing", abstract="Background: Cognitive deficits are present in several neuropsychiatric disorders, including Alzheimer disease, schizophrenia, and depression. Assessments used to measure cognition in these disorders are time-consuming, burdensome, and have low ecological validity. To address these limitations, we developed a novel virtual reality shopping task---VStore. Objective: This study aims to establish the construct validity of VStore in relation to the established computerized cognitive battery, Cogstate, and explore its sensitivity to age-related cognitive decline. Methods: A total of 142 healthy volunteers aged 20-79 years participated in the study. The main VStore outcomes included verbal recall of 12 grocery items, time to collect items, time to select items on a self-checkout machine, time to make the payment, time to order coffee, and total completion time. Construct validity was examined through a series of backward elimination regression models to establish which Cogstate tasks, measuring attention, processing speed, verbal and visual learning, working memory, executive function, and paired associate learning, in addition to age and technological familiarity, best predicted VStore performance. In addition, 2 ridge regression and 2 logistic regression models supplemented with receiver operating characteristic curves were built, with VStore outcomes in the first model and Cogstate outcomes in the second model entered as predictors of age and age cohorts, respectively. Results: Overall VStore performance, as indexed by the total time spent completing the task, was best explained by Cogstate tasks measuring attention, working memory, paired associate learning, and age and technological familiarity, accounting for 47\% of the variance. In addition, with $\lambda$=5.16, the ridge regression model selected 5 parameters for VStore when predicting age (mean squared error 185.80, SE 19.34), and with $\lambda$=9.49 for Cogstate, the model selected all 8 tasks (mean squared error 226.80, SE 23.48). Finally, VStore was found to be highly sensitive (87\%) and specific (91.7\%) to age cohorts, with 94.6\% of the area under the receiver operating characteristic curve. Conclusions: Our findings suggest that VStore is a promising assessment that engages standard cognitive domains and is sensitive to age-related cognitive decline. ", doi="10.2196/27641", url="https://www.jmir.org/2022/1/e27641", url="http://www.ncbi.nlm.nih.gov/pubmed/35080501" } @Article{info:doi/10.2196/24699, author="Birnbaum, L. Michael and Abrami, Avner and Heisig, Stephen and Ali, Asra and Arenare, Elizabeth and Agurto, Carla and Lu, Nathaniel and Kane, M. John and Cecchi, Guillermo", title="Acoustic and Facial Features From Clinical Interviews for Machine Learning--Based Psychiatric Diagnosis: Algorithm Development", journal="JMIR Ment Health", year="2022", month="Jan", day="24", volume="9", number="1", pages="e24699", keywords="audiovisual patterns", keywords="speech analysis", keywords="facial analysis", keywords="psychiatry", keywords="schizophrenia spectrum disorders", keywords="bipolar disorder", keywords="symptom prediction", keywords="diagnostic prediction", keywords="machine learning", keywords="audiovisual", keywords="speech", keywords="schizophrenia", keywords="spectrum disorders", abstract="Background: In contrast to all other areas of medicine, psychiatry is still nearly entirely reliant on subjective assessments such as patient self-report and clinical observation. The lack of objective information on which to base clinical decisions can contribute to reduced quality of care. Behavioral health clinicians need objective and reliable patient data to support effective targeted interventions. Objective: We aimed to investigate whether reliable inferences---psychiatric signs, symptoms, and diagnoses---can be extracted from audiovisual patterns in recorded evaluation interviews of participants with schizophrenia spectrum disorders and bipolar disorder. Methods: We obtained audiovisual data from 89 participants (mean age 25.3 years; male: 48/89, 53.9\%; female: 41/89, 46.1\%): individuals with schizophrenia spectrum disorders (n=41), individuals with bipolar disorder (n=21), and healthy volunteers (n=27). We developed machine learning models based on acoustic and facial movement features extracted from participant interviews to predict diagnoses and detect clinician-coded neuropsychiatric symptoms, and we assessed model performance using area under the receiver operating characteristic curve (AUROC) in 5-fold cross-validation. Results: The model successfully differentiated between schizophrenia spectrum disorders and bipolar disorder (AUROC 0.73) when aggregating face and voice features. Facial action units including cheek-raising muscle (AUROC 0.64) and chin-raising muscle (AUROC 0.74) provided the strongest signal for men. Vocal features, such as energy in the frequency band 1 to 4 kHz (AUROC 0.80) and spectral harmonicity (AUROC 0.78), provided the strongest signal for women. Lip corner--pulling muscle signal discriminated between diagnoses for both men (AUROC 0.61) and women (AUROC 0.62). Several psychiatric signs and symptoms were successfully inferred: blunted affect (AUROC 0.81), avolition (AUROC 0.72), lack of vocal inflection (AUROC 0.71), asociality (AUROC 0.63), and worthlessness (AUROC 0.61). Conclusions: This study represents advancement in efforts to capitalize on digital data to improve diagnostic assessment and supports the development of a new generation of innovative clinical tools by employing acoustic and facial data analysis. ", doi="10.2196/24699", url="https://mental.jmir.org/2022/1/e24699", url="http://www.ncbi.nlm.nih.gov/pubmed/35072648" } @Article{info:doi/10.2196/26276, author="Abbas, Anzar and Hansen, J. Bryan and Koesmahargyo, Vidya and Yadav, Vijay and Rosenfield, J. Paul and Patil, Omkar and Dockendorf, F. Marissa and Moyer, Matthew and Shipley, A. Lisa and Perez-Rodriguez, Mercedez M. and Galatzer-Levy, R. Isaac", title="Facial and Vocal Markers of Schizophrenia Measured Using Remote Smartphone Assessments: Observational Study", journal="JMIR Form Res", year="2022", month="Jan", day="21", volume="6", number="1", pages="e26276", keywords="digital biomarkers", keywords="phenotyping", keywords="computer vision", keywords="facial expressivity", keywords="negative symptoms", keywords="vocal acoustics", abstract="Background: Machine learning--based facial and vocal measurements have demonstrated relationships with schizophrenia diagnosis and severity. Demonstrating utility and validity of remote and automated assessments conducted outside of controlled experimental or clinical settings can facilitate scaling such measurement tools to aid in risk assessment and tracking of treatment response in populations that are difficult to engage. Objective: This study aimed to determine the accuracy of machine learning--based facial and vocal measurements acquired through automated assessments conducted remotely through smartphones. Methods: Measurements of facial and vocal characteristics including facial expressivity, vocal acoustics, and speech prevalence were assessed in 20 patients with schizophrenia over the course of 2 weeks in response to two classes of prompts previously utilized in experimental laboratory assessments: evoked prompts, where subjects are guided to produce specific facial expressions and speech; and spontaneous prompts, where subjects are presented stimuli in the form of emotionally evocative imagery and asked to freely respond. Facial and vocal measurements were assessed in relation to schizophrenia symptom severity using the Positive and Negative Syndrome Scale. Results: Vocal markers including speech prevalence, vocal jitter, fundamental frequency, and vocal intensity demonstrated specificity as markers of negative symptom severity, while measurement of facial expressivity demonstrated itself as a robust marker of overall schizophrenia symptom severity. Conclusions: Established facial and vocal measurements, collected remotely in schizophrenia patients via smartphones in response to automated task prompts, demonstrated accuracy as markers of schizophrenia symptom severity. Clinical implications are discussed. ", doi="10.2196/26276", url="https://formative.jmir.org/2022/1/e26276", url="http://www.ncbi.nlm.nih.gov/pubmed/35060906" } @Article{info:doi/10.2196/32932, author="Goulding, H. Evan and Dopke, A. Cynthia and Michaels, Tania and Martin, R. Clair and Khiani, A. Monika and Garborg, Christopher and Karr, Chris and Begale, Mark", title="A Smartphone-Based Self-management Intervention for Individuals With Bipolar Disorder (LiveWell): Protocol Development for an Expert System to Provide Adaptive User Feedback", journal="JMIR Form Res", year="2021", month="Dec", day="24", volume="5", number="12", pages="e32932", keywords="adaptive", keywords="personalized", keywords="self-management", keywords="smartphone", keywords="behavioral intervention technology", keywords="mHealth", keywords="bipolar disorder", keywords="depression", keywords="mania", abstract="Background: Bipolar disorder is a severe mental illness that results in significant morbidity and mortality. While pharmacotherapy is the primary treatment, adjunctive psychotherapy can improve outcomes. However, access to therapy is limited. Smartphones and other technologies can increase access to therapeutic strategies that enhance self-management while simultaneously augmenting care by providing adaptive delivery of content to users as well as alerts to providers to facilitate clinical care communication. Unfortunately, while adaptive interventions are being developed and tested to improve care, information describing the components of adaptive interventions is often not published in sufficient detail to facilitate replication and improvement of these interventions. Objective: To contribute to and support the improvement and dissemination of technology-based mental health interventions, we provide a detailed description of the expert system for adaptively delivering content and facilitating clinical care communication for LiveWell, a smartphone-based self-management intervention for individuals with bipolar disorder. Methods: Information from empirically supported psychotherapies for bipolar disorder, health psychology behavior change theories, and chronic disease self-management models was combined with user-centered design data and psychiatrist feedback to guide the development of the expert system. Results: Decision points determining the timing of intervention option adaptation were selected to occur daily and weekly based on self-report data for medication adherence, sleep duration, routine, and wellness levels. These data were selected for use as the tailoring variables determining which intervention options to deliver when and to whom. Decision rules linking delivery of options and tailoring variable thresholds were developed based on existing literature regarding bipolar disorder clinical status and psychiatrist feedback. To address the need for treatment adaptation with varying clinical statuses, decision rules for a clinical status state machine were developed using self-reported wellness rating data. Clinical status from this state machine was incorporated into hierarchal decision tables that select content for delivery to users and alerts to providers. The majority of the adaptive content addresses sleep duration, medication adherence, managing signs and symptoms, building and utilizing support, and keeping a regular routine, as well as determinants underlying engagement in these target behaviors as follows: attitudes and perceptions, knowledge, support, evaluation, and planning. However, when problems with early warning signs, symptoms, and transitions to more acute clinical states are detected, the decision rules shift the adaptive content to focus on managing signs and symptoms, and engaging with psychiatric providers. Conclusions: Adaptive mental health technologies have the potential to enhance the self-management of mental health disorders. The need for individuals with bipolar disorder to engage in the management of multiple target behaviors and to address changes in clinical status highlights the importance of detailed reporting of adaptive intervention components to allow replication and improvement of adaptive mental health technologies for complex mental health problems. ", doi="10.2196/32932", url="https://formative.jmir.org/2021/12/e32932", url="http://www.ncbi.nlm.nih.gov/pubmed/34951598" } @Article{info:doi/10.2196/34591, author="Tempelaar, Wanda and Barwick, Melanie and Crawford, Allison and Voineskos, Aristotle and Addington, Donald and Addington, Jean and Alexander, Tallan and Baluyut, Crystal and Bromley, Sarah and Durbin, Janet and Foussias, George and Ford, Catherine and de Freitas, Lauren and Jindani, Seharish and Kirvan, Anne and Kurdyak, Paul and Pauly, Kirstin and Polillo, Alexia and Roby, Rachel and Sockalingam, Sanjeev and Sosnowski, Alexandra and Villanueva, Victoria and Wang, Wei and Kozloff, Nicole", title="Adapting Evidence-Based Early Psychosis Intervention Services for Virtual Delivery: Protocol for a Pragmatic Mixed Methods Implementation and Evaluation Study", journal="JMIR Res Protoc", year="2021", month="Dec", day="7", volume="10", number="12", pages="e34591", keywords="virtual care delivery", keywords="early psychosis intervention", keywords="mixed methods implementation", abstract="Background: Timely and comprehensive treatment in the form of early psychosis intervention (EPI) has become the standard of care for youth with psychosis. While EPI services were designed to be delivered in person, the COVID-19 pandemic required many EPI programs to rapidly transition to virtual delivery, with little evidence to guide intervention adaptations or to support the effectiveness and satisfaction with virtual EPI services. Objective: This study aims to explore the adaptations required to deliver NAVIGATE, a model of coordinated specialty care used in EPI, in a virtual format. This study will evaluate implementation of the NAVIGATE model delivered virtually by describing the nature of the adaptations to the intervention, assessing fidelity to the EPI model and the satisfaction of clients, family members, and care providers. We will investigate barriers and facilitators to virtual NAVIGATE implementation, service engagement, and health equity impacts of this work. Methods: The Centre for Addiction and Mental Health (Toronto, Ontario, Canada) transitioned to delivering NAVIGATE virtually early in the COVID-19 pandemic. The Framework for Reporting Adaptations and Modifications for Evidence-Based Interventions will be used to describe the adaptations required to deliver NAVIGATE virtually. Fidelity to the EPI model will be measured using the First Episode Psychosis Services Fidelity Scale and fidelity to NAVIGATE will be assessed by investigating adherence to its core components. Implementation facilitators and barriers will be explored using semistructured interviews with providers informed by the Consolidated Framework for Implementation Research. Satisfaction with virtually delivered NAVIGATE will be assessed with virtual client and provider experience surveys and qualitative interviews with clients, family members, and providers. Service engagement data will be collected through review of medical records, and potential impacts of virtually delivered NAVIGATE on different population groups will be assessed with the Health Equity Impact Assessment. Results: Virtual clinical delivery of NAVIGATE started in March 2020 with additional adaptations and data collection is ongoing. Data will be analyzed using descriptive statistics and survival analysis for quantitative data. Qualitative data will be analyzed using thematic content analysis. Integration of qualitative and quantitative data will occur at the data collection, interpretation, and reporting levels following a convergent design. Conclusions: This study will provide information regarding the type of intervention adaptations required for virtual delivery of NAVIGATE for youth with early psychosis, ensuring access to high-quality care for this population during the pandemic and beyond by guiding future implementation in similar contexts. International Registered Report Identifier (IRRID): DERR1-10.2196/34591 ", doi="10.2196/34591", url="https://www.researchprotocols.org/2021/12/e34591", url="http://www.ncbi.nlm.nih.gov/pubmed/34806990" } @Article{info:doi/10.2196/28141, author="Lal, Shalini and Gleeson, F. John and D'Alfonso, Simon and Etienne, Geraldine and Joober, Ridha and Lepage, Martin and Lee, Hajin and Alvarez-Jimenez, Mario", title="A Digital Health Innovation to Prevent Relapse and Support Recovery in Youth Receiving Specialized Services for First-Episode Psychosis: Protocol for a Pilot Pre-Post, Mixed Methods Study of Horyzons-Canada (Phase 2)", journal="JMIR Res Protoc", year="2021", month="Dec", day="7", volume="10", number="12", pages="e28141", keywords="psychotic disorders", keywords="mental health", keywords="telemedicine", keywords="young adult", keywords="mental health services", keywords="e--mental health", keywords="virtual care", keywords="schizophrenia", keywords="eHealth", keywords="social support", keywords="therapy", keywords="psychiatry", keywords="psychology", abstract="Background: Psychotic disorders are among the most disabling of all mental disorders. The first-episode psychosis (FEP) often occurs during adolescence or young adulthood. Young people experiencing FEP often face multiple barriers in accessing a comprehensive range of psychosocial services, which have predominantly been delivered in person. New models of service delivery that are accessible, sustainable, and engaging are needed to support recovery in youth diagnosed with FEP. Objective: In this paper, we describe a protocol to implement and evaluate the acceptability, safety, and potential efficacy of an online psychosocial therapeutic intervention designed to sustain recovery and prevent relapses in young adults diagnosed with FEP. This intervention was originally developed and tested in Australia and has been adapted for implementation and evaluation in Canada and is called Horyzons-Canada (HoryzonsCa). Methods: This cohort study is implemented in a single-center and applies a pre-post mixed methods (qualitative-quantitative convergent) design. The study involves recruiting 20 participants from a specialized early intervention program for psychosis located in Montreal, Canada and providing them with access to the HoryzonsCa intervention for 8 weeks. Data collection includes interview-based psychometric measures, self-reports, focus groups, and interviews. Results: This study received funding from the Brain and Behavior Research Foundation (United States), the Quebec Health Research Funding Agency (Canada), and the Canada Research Chairs Program. The study was approved by the Research Ethics Board of the Centre int{\'e}gr{\'e} universitaire de sant{\'e} et de services sociaux de l'Ouest-de-l'{\^I}le-de-Montr{\'e}al on April 11, 2018 (\#IUSMD 17-54). Data were collected from August 16, 2018, to April 29, 2019, and a final sample of 20 individuals participated in the baseline and follow-up interviews, among which 9 participated in the focus groups. Data analysis and reporting are in process. The results of the study will be submitted for publication in 2021. Conclusions: This study will provide preliminary evidence on the acceptability, safety, and potential efficacy of using a digital health innovation adapted for the Canadian context to deliver specialized mental health services to youth diagnosed with FEP. Trial Registration: ISRCTN Registry ISRCTN43182105; https://www.isrctn.com/ISRCTN43182105 International Registered Report Identifier (IRRID): RR1-10.2196/28141 ", doi="10.2196/28141", url="https://www.researchprotocols.org/2021/12/e28141", url="http://www.ncbi.nlm.nih.gov/pubmed/34879000" } @Article{info:doi/10.2196/29749, author="Jan, Zainab and AI-Ansari, Noor and Mousa, Osama and Abd-alrazaq, Alaa and Ahmed, Arfan and Alam, Tanvir and Househ, Mowafa", title="The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review", journal="J Med Internet Res", year="2021", month="Nov", day="19", volume="23", number="11", pages="e29749", keywords="machine learning", keywords="bipolar disorder", keywords="diagnosis", keywords="support vector machine", keywords="clinical data", keywords="mental health", keywords="scoping review", abstract="Background: Bipolar disorder (BD) is the 10th most common cause of frailty in young individuals and has triggered morbidity and mortality worldwide. Patients with BD have a life expectancy 9 to 17 years lower than that of normal people. BD is a predominant mental disorder, but it can be misdiagnosed as depressive disorder, which leads to difficulties in treating affected patients. Approximately 60\% of patients with BD are treated for depression. However, machine learning provides advanced skills and techniques for better diagnosis of BD. Objective: This review aims to explore the machine learning algorithms used for the detection and diagnosis of bipolar disorder and its subtypes. Methods: The study protocol adopted the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. We explored 3 databases, namely Google Scholar, ScienceDirect, and PubMed. To enhance the search, we performed backward screening of all the references of the included studies. Based on the predefined selection criteria, 2 levels of screening were performed: title and abstract review, and full review of the articles that met the inclusion criteria. Data extraction was performed independently by all investigators. To synthesize the extracted data, a narrative synthesis approach was followed. Results: We retrieved 573 potential articles were from the 3 databases. After preprocessing and screening, only 33 articles that met our inclusion criteria were identified. The most commonly used data belonged to the clinical category (19, 58\%). We identified different machine learning models used in the selected studies, including classification models (18, 55\%), regression models (5, 16\%), model-based clustering methods (2, 6\%), natural language processing (1, 3\%), clustering algorithms (1, 3\%), and deep learning--based models (3, 9\%). Magnetic resonance imaging data were most commonly used for classifying bipolar patients compared to other groups (11, 34\%), whereas microarray expression data sets and genomic data were the least commonly used. The maximum ratio of accuracy was 98\%, whereas the minimum accuracy range was 64\%. Conclusions: This scoping review provides an overview of recent studies based on machine learning models used to diagnose patients with BD regardless of their demographics or if they were compared to patients with psychiatric diagnoses. Further research can be conducted to provide clinical decision support in the health industry. ", doi="10.2196/29749", url="https://www.jmir.org/2021/11/e29749", url="http://www.ncbi.nlm.nih.gov/pubmed/34806996" } @Article{info:doi/10.2196/30309, author="Paetzold, Isabell and Hermans, M. Karlijn S. F. and Schick, Anita and Nelson, Barnaby and Velthorst, Eva and Schirmbeck, Frederike and and van Os, Jim and Morgan, Craig and van der Gaag, Mark and de Haan, Lieuwe and Valmaggia, Lucia and McGuire, Philip and Kempton, Matthew and Myin-Germeys, Inez and Reininghaus, Ulrich", title="Momentary Manifestations of Negative Symptoms as Predictors of Clinical Outcomes in People at High Risk for Psychosis: Experience Sampling Study", journal="JMIR Ment Health", year="2021", month="Nov", day="19", volume="8", number="11", pages="e30309", keywords="ecological momentary assessment", keywords="psychotic disorder", keywords="psychopathology", abstract="Background: Negative symptoms occur in individuals at ultrahigh risk (UHR) for psychosis. Although there is evidence that observer ratings of negative symptoms are associated with level of functioning, the predictive value of subjective experience in daily life for individuals at UHR has not been studied yet. Objective: This study therefore aims to investigate the predictive value of momentary manifestations of negative symptoms for clinical outcomes in individuals at UHR. Methods: Experience sampling methodology was used to measure momentary manifestations of negative symptoms (blunted affective experience, lack of social drive, anhedonia, and social anhedonia) in the daily lives of 79 individuals at UHR. Clinical outcomes (level of functioning, illness severity, UHR status, and transition status) were assessed at baseline and at 1- and 2-year follow-ups. Results: Lack of social drive, operationalized as greater experienced pleasantness of being alone, was associated with poorer functioning at the 2-year follow-up (b=?4.62, P=.01). Higher levels of anhedonia were associated with poorer functioning at the 1-year follow-up (b=5.61, P=.02). Higher levels of social anhedonia were associated with poorer functioning (eg, disability subscale: b=6.36, P=.006) and greater illness severity (b=?0.38, P=.045) at the 1-year follow-up. In exploratory analyses, there was evidence that individuals with greater variability of positive affect (used as a measure of blunted affective experience) experienced a shorter time to remission from UHR status at follow-up (hazard ratio=4.93, P=.005). Conclusions: Targeting negative symptoms in individuals at UHR may help to predict clinical outcomes and may be a promising target for interventions in the early stages of psychosis. ", doi="10.2196/30309", url="https://mental.jmir.org/2021/11/e30309", url="http://www.ncbi.nlm.nih.gov/pubmed/34807831" } @Article{info:doi/10.2196/29201, author="Ben-Zeev, Dror and Chander, Ayesha and Tauscher, Justin and Buck, Benjamin and Nepal, Subigya and Campbell, Andrew and Doron, Guy", title="A Smartphone Intervention for People With Serious Mental Illness: Fully Remote Randomized Controlled Trial of CORE", journal="J Med Internet Res", year="2021", month="Nov", day="12", volume="23", number="11", pages="e29201", keywords="mobile health", keywords="schizophrenia", keywords="bipolar disorder", keywords="depression", keywords="mobile phone", abstract="Background: People with serious mental illness (SMI) have significant unmet mental health needs. Development and testing of digital interventions that can alleviate the suffering of people with SMI is a public health priority. Objective: The aim of this study is to conduct a fully remote randomized waitlist-controlled trial of CORE, a smartphone intervention that comprises daily exercises designed to promote reassessment of dysfunctional beliefs in multiple domains. Methods: Individuals were recruited via the web using Google and Facebook advertisements. Enrolled participants were randomized into either active intervention or waitlist control groups. Participants completed the Beck Depression Inventory-Second Edition (BDI-II), Generalized Anxiety Disorder-7 (GAD-7), Hamilton Program for Schizophrenia Voices, Green Paranoid Thought Scale, Recovery Assessment Scale (RAS), Rosenberg Self-Esteem Scale (RSES), Friendship Scale, and Sheehan Disability Scale (SDS) at baseline (T1), 30-day (T2), and 60-day (T3) assessment points. Participants in the active group used CORE from T1 to T2, and participants in the waitlist group used CORE from T2 to T3. Both groups completed usability and accessibility measures after they concluded their intervention periods. Results: Overall, 315 individuals from 45 states participated in this study. The sample comprised individuals with self-reported bipolar disorder (111/315, 35.2\%), major depressive disorder (136/315, 43.2\%), and schizophrenia or schizoaffective disorder (68/315, 21.6\%) who displayed moderate to severe symptoms and disability levels at baseline. Participants rated CORE as highly usable and acceptable. Intent-to-treat analyses showed significant treatment{\texttimes}time interactions for the BDI-II (F1,313=13.38; P<.001), GAD-7 (F1,313=5.87; P=.01), RAS (F1,313=23.42; P<.001), RSES (F1,313=19.28; P<.001), and SDS (F1,313=10.73; P=.001). Large effects were observed for the BDI-II (d=0.58), RAS (d=0.61), and RSES (d=0.64); a moderate effect size was observed for the SDS (d=0.44), and a small effect size was observed for the GAD-7 (d=0.20). Similar changes in outcome measures were later observed in the waitlist control group participants following crossover after they received CORE (T2 to T3). Approximately 41.5\% (64/154) of participants in the active group and 60.2\% (97/161) of participants in the waitlist group were retained at T2, and 33.1\% (51/154) of participants in the active group and 40.3\% (65/161) of participants in the waitlist group were retained at T3. Conclusions: We successfully recruited, screened, randomized, treated, and assessed a geographically dispersed sample of participants with SMI entirely via the web, demonstrating that fully remote clinical trials are feasible in this population; however, study retention remains challenging. CORE showed promise as a usable, acceptable, and effective tool for reducing the severity of psychiatric symptoms and disability while improving recovery and self-esteem. Rapid adoption and real-world dissemination of evidence-based mobile health interventions such as CORE are needed if we are to shorten the science-to-service gap and address the significant unmet mental health needs of people with SMI during the COVID-19 pandemic and beyond. Trial Registration: ClinicalTrials.gov NCT04068467; https://clinicaltrials.gov/ct2/show/NCT04068467 ", doi="10.2196/29201", url="https://www.jmir.org/2021/11/e29201", url="http://www.ncbi.nlm.nih.gov/pubmed/34766913" } @Article{info:doi/10.2196/31742, author="Bond, Jessica and Robotham, Dan and Kenny, Alexandra and Pinfold, Vanessa and Kabir, Thomas and Andleeb, Humma and Larkin, Michael and Martin, L. Jennifer and Brown, Susan and Bergin, D. Aislinn and Petit, Ariane and Rosebrock, Laina and Lambe, Sin{\'e}ad and Freeman, Daniel and Waite, Felicity", title="Automated Virtual Reality Cognitive Therapy for People With Psychosis: Protocol for a Qualitative Investigation Using Peer Research Methods", journal="JMIR Res Protoc", year="2021", month="Oct", day="25", volume="10", number="10", pages="e31742", keywords="virtual reality", keywords="therapy", keywords="schizophrenia", keywords="agoraphobia", keywords="peer research", keywords="qualitative methods", keywords="implementation", keywords="mental health", keywords="psychosis", keywords="cognitive therapy", abstract="Background: Many people with psychosis experience difficulties in everyday social situations. Anxiety can make life challenging, leading to withdrawal. Cognitive therapy, using active in vivo learning, enables people to overcome fears. These treatments are not readily available to people with psychosis. Automated virtual reality (VR) therapy is a potential route to increase accessibility. The gameChange automated VR cognitive therapy is designed to help people overcome anxious avoidance and build confidence in everyday social situations. A virtual coach guides the person through the treatment. Understanding user experience is key to facilitating future implementation. Peer research methods, in which people with lived experience of the issues being studied are involved in collecting and analyzing data, may be useful in developing this understanding. This encourages researchers to draw on their lived experience to explore participant perspectives and co-create knowledge. Objective: The primary objective is to use a peer research approach to explore the participant experience of a novel automated VR therapy for anxious social avoidance. This includes understanding (1) the experience of anxious social avoidance in people with psychosis, (2) the experience of the gameChange automated VR cognitive therapy, and (3) any potential impact of the therapy in people's lives. This will inform future implementation strategies. The secondary objective is to explore how peer research can be used to co-create knowledge. Methods: Semistructured interviews will be conducted with approximately 25 people with psychosis participating in the gameChange trial (ISRCTN17308399). Participants will be recruited from the five trial centers based in National Health Service mental health trusts across England. Interviews will be conducted by two researchers. One is a peer researcher with similar lived experience to the trial participants. The other has lived experiences of mental health issues that do not directly overlap with those of the trial participants. Interview questions will focus on an individual's experience of anxious social avoidance, experiences of participating in the gameChange VR therapy, and any changes or impact following therapy. The interview schedule was developed in collaboration with the gameChange Lived Experience Advisory Panel (LEAP), comprising 10 project advisors with lived experience of psychosis. Interpretative phenomenological analysis and template analysis will be used to explore individual accounts. The LEAP will contribute to the analysis. Results: Data collection will be conducted from April to September 2021, and analysis will be conducted from June to October 2021. As of September 28, 2021, 20 participants had been interviewed, and coding is underway. Conclusions: The study, employing a peer research approach, may provide a unique insight into the experiences of anxious social avoidance in people with psychosis and its treatment using automated VR therapy. This will inform potential future implementation of VR automated therapies in mental health services. International Registered Report Identifier (IRRID): DERR1-10.2196/31742 ", doi="10.2196/31742", url="https://www.researchprotocols.org/2021/10/e31742", url="http://www.ncbi.nlm.nih.gov/pubmed/34694236" } @Article{info:doi/10.2196/30311, author="Lustig, Andrew and Brookes, Gavin and Hunt, Daniel", title="Social Semiotics of Gangstalking Evidence Videos on YouTube: Multimodal Discourse Analysis of a Novel Persecutory Belief System", journal="JMIR Ment Health", year="2021", month="Oct", day="21", volume="8", number="10", pages="e30311", keywords="internet", keywords="discourse analysis", keywords="psychosis", keywords="delusion", keywords="semiotics", keywords="linguistics", keywords="computer-mediated communication", keywords="schizophrenia", keywords="eHealth", keywords="video", keywords="communication", keywords="YouTube", keywords="social media", keywords="discourse", keywords="mental health", abstract="Background: Gangstalking refers to a novel persecutory belief system wherein sufferers believe that they are being followed, watched, and harassed by a vast network of people in their community who have been recruited as complicit perpetrators. They are frequently diagnosed as mentally ill, although they reject this formulation. Those affected by this belief system self-identify as targeted individuals (TIs). They seek to prove the veracity of their persecution and dispute the notion that they are mentally ill by posting videos online that purport to provide evidence of their claims. Objective: The objective of the study was to characterize the multimodal social semiotic practices used in gangstalking evidence videos. Methods: We assembled a group of 50 evidence videos posted on YouTube by self-identified TIs and performed a multimodal social semiotic discourse analysis using a grounded theory approach to data analysis. Results: TIs accomplished several social and interpersonal tasks in the videos. They constructed their own identity as subjects of persecution and refuted the notion that they suffered from mental illness. They also cultivated positive ambient affiliation with viewers of the videos but manifested hostility toward people who appeared in the videos. They made extensive use of multimodal deixis to generate salience and construe the gangstalking belief system. The act of filming itself was a source of conflict and served as a self-fulfilling prophecy; filming was undertaken to neutrally record hostility directed toward video bloggers (vloggers). However, the act of filming precipitated the very behaviors that they set out to document. Finally, the act of filming was also regarded as an act of resistance and empowerment by vloggers. Conclusions: These data provide insight into a novel persecutory belief system. Interpersonal concerns are important for people affected, and they construe others as either sympathetic or hostile. They create positive ambient affiliation with viewers. We found that vloggers use multimodal deixis to illustrate the salience of the belief system. The videos highlighted the Derridean concept of diff{\'e}rance, wherein the meaning of polysemous signifiers is deferred without definitive resolution. This may be important in communicating with people and patients with persecutory belief systems. Clinicians may consider stepping away from the traditional true/false dichotomy endorsed by psychiatric classification systems and focus on the ambiguity in semiotic systems generally and in persecutory belief systems specifically. ", doi="10.2196/30311", url="https://mental.jmir.org/2021/10/e30311", url="http://www.ncbi.nlm.nih.gov/pubmed/34673523" } @Article{info:doi/10.2196/25168, author="Hatzioannou, Anna and Chatzittofis, Andreas and Koutroubas, Sunday Virginia and Papastavrou, Evridiki and Karanikola, Maria", title="Combined Use of Web-Based and In-Person Education on Ill Health Self-management Skills in Adults With Bipolar Disorder: Protocol for a Mixed Methods Study", journal="JMIR Res Protoc", year="2021", month="Sep", day="8", volume="10", number="9", pages="e25168", keywords="education", keywords="empowerment", keywords="bipolar disorders", keywords="self-management", keywords="bipolar", keywords="mental health", abstract="Background: Addressing the enhancement of ill health self-management skills in adults diagnosed with bipolar disorder may be considered an important intervention for health care systems worldwide. Objective: This protocol describes the study ``Management of my Bipolarity'' (MoB), which aims to develop an educational intervention for adults with bipolar disorder and assess its effectiveness. The objectives include (a) a literature review on bipolar disorder educational interventions; (b) a qualitative exploration of the educational needs of people with bipolar disorder; (c) development of an educational intervention based on objectives (a) and (b) (ie, the MoB educational intervention); and (d) exploration of the effectiveness of the intervention regarding participants' knowledge of their mental health condition and enhancement of their ill health self-management skills. The MoB educational intervention will consist of an in-person and a web-based intervention in the form of a digital platform. Methods: The proposed interventional study is a combination of a qualitative and a quantitative design (mixed methods study). A focus group and content analysis will be implemented for the qualitative assessment of the educational needs of adults with bipolar disorder. The intervention will be developed based on the qualitative data of the study and relevant literature. The effectiveness of the acquired knowledge and self-management skills will be assessed according to (a) substance use behavior, (b) health locus of control, (c) impulse control, (d) adherence to pharmacotherapy, (e) relapse prevention, (f) improvement of quality of life, and (g) bipolar disorder knowledge level via structured instruments in the quantitative part of the study using descriptive and inferential statistics (SPSS version 24.0). Results: A total of 13 patients with bipolar disorder have been interviewed (8 women, 5 men) to identify educational needs to be covered through the intervention. Moreover, a literature review on bipolar disorder educational interventions has been completed. These data have been incorporated in the design of the MoB in-person intervention and the digital platform. The digital platform is live, and the development of the MoB in-person intervention was completed at the end of 2020. The recruitment of the participants for the intervention (40 patients) and the control group (40 patients) began during the first semester of 2021. Moreover, by tracking the platform for 1.5 years, we have recorded that 2180 users have visited the platform with an average session duration of almost 2 minutes. Mobile and tablet devices are being used by 70\% of the visitors. Conclusions: Since new parameters regarding educational interventions will be explored, these findings are expected to provide evidence that participation in structured educational interventions offers patients the opportunity to improve adherence to pharmacotherapy and increase their quality of life. Trial Registration: ClinicalTrials.gov NCT04643210; https://clinicaltrials.gov/ct2/show/NCT04643210 International Registered Report Identifier (IRRID): DERR1-10.2196/25168 ", doi="10.2196/25168", url="https://www.researchprotocols.org/2021/9/e25168", url="http://www.ncbi.nlm.nih.gov/pubmed/34494969" } @Article{info:doi/10.2196/30827, author="Lee, Yun Dong and Park, Jimyung and Noh, Sung Jai and Roh, Woong Hyun and Ha, Ho Jae and Lee, Young Eun and Son, Joon Sang and Park, Woong Rae", title="Characteristics of Dimensional Psychopathology in Suicidal Patients With Major Psychiatric Disorders and Its Association With the Length of Hospital Stay: Algorithm Validation Study", journal="JMIR Ment Health", year="2021", month="Sep", day="3", volume="8", number="9", pages="e30827", keywords="suicide", keywords="computed phenotype", keywords="natural language processing", keywords="research domain criteria", keywords="electronic health record", abstract="Background: Suicide has emerged as a serious concern for public health; however, only few studies have revealed the differences between major psychiatric disorders and suicide. Recent studies have attempted to quantify research domain criteria (RDoC) into numeric scores to systematically use them in computerized methods. The RDoC scores were used to reveal the characteristics of suicide and its association with major psychiatric disorders. Objective: We intended to investigate the differences in the dimensional psychopathology among hospitalized suicidal patients and the association between the dimensional psychopathology of psychiatric disorders and length of hospital stay. Methods: This retrospective study enrolled hospitalized suicidal patients diagnosed with major psychiatric disorders (depression, schizophrenia, and bipolar disorder) between January 2010 and December 2020 at a tertiary hospital in South Korea. The RDoC scores were calculated using the patients' admission notes. To measure the differences between psychiatric disorder cohorts, analysis of variance and the Cochran Q test were conducted and post hoc analysis for RDoC domains was performed with the independent two-sample t test. A linear regression model was used to analyze the association between the RDoC scores and sociodemographic features and comorbidity index. To estimate the association between the RDoC scores and length of hospital stay, multiple logistic regression models were applied to each psychiatric disorder group. Results: We retrieved 732 admissions for 571 patients (465 with depression, 73 with schizophrenia, and 33 with bipolar disorder). We found significant differences in the dimensional psychopathology according to the psychiatric disorders. The patient group with depression showed the highest negative RDoC domain scores. In the cognitive and social RDoC domains, the groups with schizophrenia and bipolar disorder scored higher than the group with depression. In the arousal RDoC domain, the depression and bipolar disorder groups scored higher than the group with schizophrenia. We identified significant associations between the RDoC scores and length of stay for the depression and bipolar disorder groups. The odds ratios (ORs) of the length of stay were increased because of the higher negative RDoC domain scores in the group with depression (OR 1.058, 95\% CI 1.006-1.114) and decreased by higher arousal RDoC domain scores in the group with bipolar disorder (OR 0.537, 95\% CI 0.285-0.815). Conclusions: This study showed the association between the dimensional psychopathology of major psychiatric disorders related to suicide and the length of hospital stay and identified differences in the dimensional psychopathology of major psychiatric disorders. This may provide new perspectives for understanding suicidal patients. ", doi="10.2196/30827", url="https://mental.jmir.org/2021/9/e30827", url="http://www.ncbi.nlm.nih.gov/pubmed/34477555" } @Article{info:doi/10.2196/23360, author="Ashrafi, Agaah and Tabatabaee, Maryam and Sharifi, Vandad", title="Development and Evaluation of Acceptability and Feasibility of a Web-Based Intervention for Patients With Bipolar Disorder in Iran: Implementation Study", journal="JMIR Form Res", year="2021", month="Aug", day="17", volume="5", number="8", pages="e23360", keywords="bipolar disorder", keywords="psychoeducation", keywords="web-based intervention", keywords="feasibility", keywords="acceptability", abstract="Background: Psychoeducation for bipolar disorder has a significant impact on symptoms and treatment adherence. In Iran, as a low-resource setting, infrastructural barriers, such as inadequate mental health professionals, difficulties in transportation, and costs of care, may hinder optimum delivery of this evidence-based intervention to patients. Objective: This study sought to explore the acceptability and feasibility of a web-based intervention for bipolar patients in Iran. Methods: A website has been developed as a platform for providing psychoeducational content about bipolar disorder. Patients were chosen via a convenient sampling method in 2018-2019. The main component of the intervention included streaming 7 weekly video clips after attending a single in-person meeting, as well as a medication self-monitoring application. Information was collected about the feasibility and acceptability of the intervention. Results: We invited 45 patients from the day center and the outpatient clinic of Roozbeh psychiatric hospital and some private clinics in Tehran. Of the 23 patients (51\%) who attended the first in-person session and provided informed consent, 14 patients dropped out during the study. While 9 patients completed the course (attended 4 or more online sessions), only 5 watched all the video sessions. The rate of adherence to the intervention and frequency of exposure to the website were much higher for those recruited from the private and outpatient clinics. Conclusions: This web-based intervention can be feasible and acceptable only for a subgroup of patients with specific educational status and socioeconomic level. ", doi="10.2196/23360", url="https://formative.jmir.org/2021/8/e23360", url="http://www.ncbi.nlm.nih.gov/pubmed/34402794" } @Article{info:doi/10.2196/26348, author="An{\'y}?, Ji?{\'i} and Bak{\vs}tein, Eduard and Dally, Andrea and Koleni{\v c}, Mari{\'a}n and Hlinka, Jaroslav and Hartmannov{\'a}, Tereza and Urbanov{\'a}, Kate?ina and Correll, U. Christoph and Nov{\'a}k, Daniel and {\vS}paniel, Filip", title="Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study", journal="JMIR Ment Health", year="2021", month="Aug", day="9", volume="8", number="8", pages="e26348", keywords="bipolar disorder", keywords="symptom monitoring", keywords="ecological mood assessment", keywords="relapse detection", keywords="mobile application", keywords="mobile phone", abstract="Background: Self-reported mood is a valuable clinical data source regarding disease state and course in patients with mood disorders. However, validated, quick, and scalable digital self-report measures that can also detect relapse are still not available for clinical care. Objective: In this study, we aim to validate the newly developed ASERT (Aktibipo Self-rating) questionnaire---a 10-item, mobile app--based, self-report mood questionnaire consisting of 4 depression, 4 mania, and 2 nonspecific symptom items, each with 5 possible answers. The validation data set is a subset of the ongoing observational longitudinal AKTIBIPO400 study for the long-term monitoring of mood and activity (via actigraphy) in patients with bipolar disorder (BD). Patients with confirmed BD are included and monitored with weekly ASERT questionnaires and monthly clinical scales (Montgomery-{\AA}sberg Depression Rating Scale [MADRS] and Young Mania Rating Scale [YMRS]). Methods: The content validity of the ASERT questionnaire was assessed using principal component analysis, and the Cronbach $\alpha$ was used to assess the internal consistency of each factor. The convergent validity of the depressive or manic items of the ASERT questionnaire with the MADRS and YMRS, respectively, was assessed using a linear mixed-effects model and linear correlation analyses. In addition, we investigated the capability of the ASERT questionnaire to distinguish relapse (YMRS?15 and MADRS?15) from a nonrelapse (interepisode) state (YMRS<15 and MADRS<15) using a logistic mixed-effects model. Results: A total of 99 patients with BD were included in this study (follow-up: mean 754 days, SD 266) and completed an average of 78.1\% (SD 18.3\%) of the requested ASERT assessments (completion time for the 10 ASERT questions: median 24.0 seconds) across all patients in this study. The ASERT depression items were highly associated with MADRS total scores (P<.001; bootstrap). Similarly, ASERT mania items were highly associated with YMRS total scores (P<.001; bootstrap). Furthermore, the logistic mixed-effects regression model for scale-based relapse detection showed high detection accuracy in a repeated holdout validation for both depression (accuracy=85\%; sensitivity=69.9\%; specificity=88.4\%; area under the receiver operating characteristic curve=0.880) and mania (accuracy=87.5\%; sensitivity=64.9\%; specificity=89.9\%; area under the receiver operating characteristic curve=0.844). Conclusions: The ASERT questionnaire is a quick and acceptable mood monitoring tool that is administered via a smartphone app. The questionnaire has a good capability to detect the worsening of clinical symptoms in a long-term monitoring scenario. ", doi="10.2196/26348", url="https://mental.jmir.org/2021/8/e26348", url="http://www.ncbi.nlm.nih.gov/pubmed/34383689" } @Article{info:doi/10.2196/26234, author="Lahti, C. Adrienne and Wang, Dai and Pei, Huiling and Baker, Susan and Narayan, A. Vaibhav", title="Clinical Utility of Wearable Sensors and Patient-Reported Surveys in Patients With Schizophrenia: Noninterventional, Observational Study", journal="JMIR Ment Health", year="2021", month="Aug", day="9", volume="8", number="8", pages="e26234", keywords="activity", keywords="relapse", keywords="schizophrenia", keywords="sleep", keywords="wearable devices", keywords="mobile phone", abstract="Background: Relapse in schizophrenia may be preceded by early warning signs of biological, sensory, and clinical status. Early detection of warning signs may facilitate intervention and prevent relapses. Objective: This study aims to investigate the feasibility of using wearable devices and self-reported technologies to identify symptom exacerbation correlates and relapse in patients with schizophrenia. Methods: In this observational study, patients with schizophrenia were provided with remote sensing devices to continuously monitor activity (Garmin vivofit) and sleep (Philips Actiwatch), and smartphones were used to record patient-reported outcomes. Clinical assessments of symptoms (Positive and Negative Syndrome Scale and Brief Psychiatric Rating Scale) were performed biweekly, and other clinical scales on symptoms (Clinical Global Impression-Schizophrenia, Calgary Depression Scale), psychosocial functioning, physical activity (Yale Physical Activity Survey), and sleep (Pittsburgh Sleep Quality Index) were assessed every 4 weeks. Patients were observed for 4 months, and correlations between clinical assessments and aggregated device metrics data were assessed using a mixed-effect model. An elastic net model was used to predict the clinical symptoms based on the device features. Results: Of the 40 patients enrolled, 1 patient relapsed after being stable with evaluable postbaseline data. Weekly patient-reported outcomes were moderately correlated with psychiatric symptoms (Brief Psychiatric Rating Scale total score, r=0.29; Calgary Depression Scale total score, r=0.37; and Positive and Negative Syndrome Scale total score, r=0.3). In the elastic net model, sleep and activity features derived from Philips Actigraph and Garmin vivofit were predictive of the sitting index of the Yale Physical Activity Survey and sleep duration component of the Pittsburgh Sleep Quality Index. On the basis of the combined patient data, a high percentage of data coverage and compliance (>80\%) was observed for each device. Conclusions: This study demonstrated that wearable devices and smartphones could be effectively deployed and potentially used to monitor patients with schizophrenia. Furthermore, metrics-based prediction models can assist in detecting earlier signs of symptom changes. The operational learnings from this study may provide insights to conduct future studies. Trial Registration: ClinicalTrials.gov NCT02224430; https://www.clinicaltrials.gov/ct2/show/NCT02224430 ", doi="10.2196/26234", url="https://mental.jmir.org/2021/8/e26234", url="http://www.ncbi.nlm.nih.gov/pubmed/34383682" } @Article{info:doi/10.2196/26548, author="Lopez-Morinigo, Javier-David and Barrig{\'o}n, Luisa Mar{\'i}a and Porras-Segovia, Alejandro and Ruiz-Ruano, Gonz{\'a}lez Ver{\'o}nica and Escribano Mart{\'i}nez, S{\'a}nchez Adela and Escobedo-Aedo, Jhoana Paula and S{\'a}nchez Alonso, Sergio and Mata Iturralde, Laura and Mu{\~n}oz Lorenzo, Laura and Art{\'e}s-Rodr{\'i}guez, Antonio and David, S. Anthony and Baca-Garc{\'i}a, Enrique", title="Use of Ecological Momentary Assessment Through a Passive Smartphone-Based App (eB2) by Patients With Schizophrenia: Acceptability Study", journal="J Med Internet Res", year="2021", month="Jul", day="26", volume="23", number="7", pages="e26548", keywords="ecological momentary assessment", keywords="acceptability", keywords="schizophrenia spectrum disorders", keywords="eB2", keywords="digital tools", keywords="mental health", keywords="schizophrenia", keywords="real-time data", keywords="patients", keywords="digital health", keywords="internet", keywords="mobile apps", abstract="Background: Ecological momentary assessment (EMA) tools appear to be useful interventions for collecting real-time data on patients' behavior and functioning. However, concerns have been voiced regarding the acceptability of EMA among patients with schizophrenia and the factors influencing EMA acceptability. Objective: The aim of this study was to investigate the acceptability of a passive smartphone-based EMA app, evidence-based behavior (eB2), among patients with schizophrenia spectrum disorders and the putative variables underlying their acceptance. Methods: The participants in this study were from an ongoing randomized controlled trial (RCT) of metacognitive training, consisting of outpatients with schizophrenia spectrum disorders (F20-29 of 10th revision of the International Statistical Classification of Diseases and Related Health Problems), aged 18-64 years, none of whom received any financial compensation. Those who consented to installation of the eB2 app (users) were compared with those who did not (nonusers) in sociodemographic, clinical, premorbid adjustment, neurocognitive, psychopathological, insight, and metacognitive variables. A multivariable binary logistic regression tested the influence of the above (independent) variables on ``being user versus nonuser'' (acceptability), which was the main outcome measure. Results: Out of the 77 RCT participants, 24 (31\%) consented to installing eB2, which remained installed till the end of the study (median follow-up 14.50 weeks) in 14 participants (70\%). Users were younger and had a higher education level, better premorbid adjustment, better executive function (according to the Trail Making Test), and higher cognitive insight levels (measured with the Beck Cognitive Insight Scale) than nonusers (univariate analyses) although only age (OR 0.93, 95\% CI 0.86-0.99; P=.048) and early adolescence premorbid adjustment (OR 0.75, 95\% CI 0.61-0.93; P=.01) survived the multivariable regression model, thus predicting eB2 acceptability. Conclusions: Acceptability of a passive smartphone-based EMA app among participants with schizophrenia spectrum disorders in this RCT where no participant received financial compensation was, as expected, relatively low, and linked with being young and good premorbid adjustment. Further research should examine how to increase EMA acceptability in patients with schizophrenia spectrum disorders, in particular, older participants and those with poor premorbid adjustment. Trial Registration: ClinicalTrials.gov NCT04104347; https://clinicaltrials.gov/ct2/show/NCT04104347 ", doi="10.2196/26548", url="https://www.jmir.org/2021/7/e26548", url="http://www.ncbi.nlm.nih.gov/pubmed/34309576" } @Article{info:doi/10.2196/25998, author="Williams, Anne and Fossey, Ellie and Farhall, John and Foley, Fiona and Thomas, Neil", title="Impact of Jointly Using an e--Mental Health Resource (Self-Management And Recovery Technology) on Interactions Between Service Users Experiencing Severe Mental Illness and Community Mental Health Workers: Grounded Theory Study", journal="JMIR Ment Health", year="2021", month="Jun", day="16", volume="8", number="6", pages="e25998", keywords="digital mental health", keywords="tablet computers", keywords="therapeutic relationship", keywords="recovery narratives", keywords="lived experience video", keywords="personal recovery", keywords="schizophrenia", keywords="mobile phone", abstract="Background: e--Mental health resources are increasingly available for people who experience severe mental illness, including those who are users of community mental health services. However, the potential for service users (SUs) living with severe mental illness to use e--mental health resources together with their community mental health workers (MHWs) has received little attention. Objective: This study aims to identify how jointly using an interactive website called Self-Management And Recovery Technology (SMART) in a community mental health context influenced therapeutic processes and interactions between SUs and MHWs from their perspective. Methods: We conducted a qualitative study using a constructivist grounded theory methodology. Data were collected through individual semistructured interviews with 37 SUs and 15 MHWs who used the SMART website together for 2 to 6 months. Data analysis involved iterative phases of coding, constant comparison, memo writing, theoretical sampling, and consultation with stakeholders to support the study's credibility. Results: A substantive grounded theory, discovering ways to keep life on track, was developed, which portrays a shared discovery process arising from the SU-worker-SMART website interactions. The discovery process included choosing to use the website, revealing SUs' experiences, exploring these experiences, and gaining new perspectives on how SUs did and could keep their lives on track. SUs and MHWs perceived that their three-way interactions were enjoyable, beneficial, and recovery focused when using the website together. They experienced the shared discovery process as relationship building---their interactions when using the website together were more engaging and equal. Conclusions: Jointly using an e--mental health resource elicited recovery-oriented interactions and processes between SUs and MHWs that strengthened their therapeutic relationship in real-world community mental health services. Further work to develop and integrate this novel use of e--mental health in community mental health practice is warranted. ", doi="10.2196/25998", url="https://mental.jmir.org/2021/6/e25998", url="http://www.ncbi.nlm.nih.gov/pubmed/34132647" } @Article{info:doi/10.2196/27475, author="Fulford, Daniel and Gard, E. David and Mueser, T. Kim and Mote, Jasmine and Gill, Kathryn and Leung, Lawrence and Mow, Jessica", title="Preliminary Outcomes of an Ecological Momentary Intervention for Social Functioning in Schizophrenia: Pre-Post Study of the Motivation and Skills Support App", journal="JMIR Ment Health", year="2021", month="Jun", day="15", volume="8", number="6", pages="e27475", keywords="schizophrenia", keywords="psychosis", keywords="social functioning", keywords="social skills", keywords="motivation", keywords="mHealth", keywords="smartphone", keywords="mobile phone", abstract="Background: People with schizophrenia and other serious mental illnesses often lack access to evidence-based interventions, particularly interventions that target meaningful recovery outcomes such as social functioning and quality of life. Mobile technologies, including smartphone apps, have the potential to provide scalable support that places elements of evidence-based interventions at the palm of patients' hands. Objective: We aim to develop a smartphone app---called Motivation and Skills Support---to provide targeted social goal support (eg, making new friends and improving existing relationships) for people with schizophrenia enrolled in a stand-alone open trial. Methods: In this paper, we presented preliminary outcomes of 31 participants who used the Motivation and Skills Support app for 8 weeks, including social functioning pre- to postintervention, and momentary reports of treatment targets (eg, social motivation and appraisals) during the intervention. Results: The findings suggest that the intervention improved self-reported social functioning from baseline to treatment termination, particularly in female participants. Gains were not maintained at the 3-month follow-up. Furthermore, increased social functioning was predicted by momentary reports of social appraisals, including perceived social competence and the extent to which social interactions were worth the effort. Conclusions: The implications of these findings and future directions for addressing social functioning in schizophrenia using mobile technology have been discussed. Trial Registration: ClinicalTrials.gov NCT03404219; https://clinicaltrials.gov/ct2/show/NCT03404219 ", doi="10.2196/27475", url="https://mental.jmir.org/2021/6/e27475", url="http://www.ncbi.nlm.nih.gov/pubmed/34128812" } @Article{info:doi/10.2196/26820, author="Brander, Mischa and Egger, T. Stephan and H{\"u}rlimann, Noa and Seifritz, Erich and Sumner, W. Robert and Vetter, Stefan and Magnenat, St{\'e}phane", title="Virtual Reality Human--Human Interface to Deliver Psychotherapy to People Experiencing Auditory Verbal Hallucinations: Development and Usability Study", journal="JMIR Serious Games", year="2021", month="Jun", day="1", volume="9", number="2", pages="e26820", keywords="system usability", keywords="virtual reality psychotherapy", keywords="verbal auditory hallucinations", abstract="Background: Digital technologies have expanded the options for delivering psychotherapy, permitting for example, the treatment of schizophrenia using Avatar Therapy. Despite its considerable potential, this treatment method has not been widely disseminated. As a result, its operability and functionality remain largely unknown. Objective: We aimed to study the usability of a therapeutic virtual reality human--human interface, created in a game engine. Methods: Participants were psychiatric hospital staff who were introduced to the therapeutic platform in a hands-on session. The System Usability Scale (SUS) was employed for evaluation purposes. Statistical evaluation was conducted using descriptive statistics, the chi-square test, analysis of variance, and multilevel factor analysis. Results: In total, 109 staff members were introduced to the therapeutic tool and completed the SUS. The mean SUS global score was 81.49 (SD 11.1). Psychotherapists (mean 86.44, SD 8.79) scored significantly higher (F2,106=6.136; P=.003) than nursing staff (mean 79.01, SD 13.30) and administrative personnel (mean 77.98, SD 10.72). A multilevel factor analysis demonstrates a different factor structure for each profession. Conclusions: In all professional groups in this study, the usability of a digital psychotherapeutic tool developed using a game engine achieved the benchmark for an excellent system, scoring highest among the professional target group (psychotherapists). The usability of the system seems, to some extent, to be dependent on the professional background of the user. It is possible to create and customize novel psychotherapeutic approaches with gaming technologies and platforms. Trial Registration: Clinicaltrials.gov NCT04099940; http://clinicaltrials.gov/ct2/show/NCT04099940 ", doi="10.2196/26820", url="https://games.jmir.org/2021/2/e26820", url="http://www.ncbi.nlm.nih.gov/pubmed/33769295" } @Article{info:doi/10.2196/24567, author="Polillo, Alexia and Voineskos, N. Aristotle and Foussias, George and Kidd, A. Sean and Sav, Andreea and Hawley, Steve and Soklaridis, Sophie and Stergiopoulos, Vicky and Kozloff, Nicole", title="Using Digital Tools to Engage Patients With Psychosis and Their Families in Research: Survey Recruitment and Completion in an Early Psychosis Intervention Program", journal="JMIR Ment Health", year="2021", month="May", day="31", volume="8", number="5", pages="e24567", keywords="digital", keywords="online", keywords="psychosis", keywords="schizophrenia", keywords="early psychosis intervention", keywords="surveys", abstract="Background: Barriers to recruiting and retaining people with psychosis and their families in research are well-established, potentially biasing clinical research samples. Digital research tools, such as online platforms, mobile apps, and text messaging, have the potential to address barriers to research by facilitating remote participation. However, there has been limited research on leveraging these technologies to engage people with psychosis and their families in research. Objective: The objective of this study was to assess the uptake of digital tools to engage patients with provisional psychosis and their families in research and their preferences for different research administration methods. Methods: This study used Research Electronic Data Capture (REDCap)---a secure web-based platform with built-in tools for data collection and storage---to send web-based consent forms and surveys on service engagement via text message or email to patients and families referred to early psychosis intervention services; potential participants were also approached or reminded about the study in person. We calculated completion rates and timing using remote and in-person methods and compensation preferences. Results: A total of 447 patients with provisional psychosis and 187 of their family members agreed to receive the web-based consent form, and approximately half of the patients (216/447, 48.3\%) and family members (109/187, 58.3\%) consented to participate in the survey. Most patients (182/229, 79.5\%) and family members (75/116, 64.7\%) who completed the consent form did so remotely, with more family members (41/116, 35.3\%) than patients (47/229, 20.5\%) completing it in person. Of those who consented, 77.3\% (167/216) of patients and 72.5\% (79/109) of family members completed the survey, and most did the survey remotely. Almost all patients (418/462, 90.5\%) and family members (174/190, 91.6\%) requested to receive the consent form and survey by email, and only 4.1\% (19/462) and 3.2\% (6/190), respectively, preferred text message. Just over half of the patients (91/167, 54.5\%) and family members (42/79, 53.2\%) preferred to receive electronic gift cards from a coffee shop as study compensation. Most surveys were completed on weekdays between 12 PM and 6 PM. Conclusions: When offered the choice, most participants with psychosis and their families chose remote administration methods, suggesting that digital tools may enhance research recruitment and participation in this population, particularly in the context of the COVID-19 global pandemic. ", doi="10.2196/24567", url="https://mental.jmir.org/2021/5/e24567", url="http://www.ncbi.nlm.nih.gov/pubmed/34057421" } @Article{info:doi/10.2196/26562, author="Tatar, Ovidiu and Abdel-Baki, Amal and Tra, Christophe and Mongeau-P{\'e}russe, Violaine and Arruda, Nelson and Kaur, Navdeep and Landry, Vivianne and Coronado-Montoya, Stephanie and Jutras-Aswad, Didier", title="Technology-Based Psychological Interventions for Young Adults With Early Psychosis and Cannabis Use Disorder: Qualitative Study of Patient and Clinician Perspectives", journal="JMIR Form Res", year="2021", month="Apr", day="5", volume="5", number="4", pages="e26562", keywords="psychology", keywords="intervention", keywords="cannabis misuse", keywords="cannabis use disorder", keywords="young adult", keywords="clinician", keywords="psychosis", keywords="schizophrenia", keywords="dual diagnosis", keywords="qualitative", keywords="acceptability", keywords="technology-based", keywords="telemedicine", keywords="mHealth", keywords="digital health", keywords="eHealth", keywords="application", keywords="smartphone", keywords="mobile phone", abstract="Background: The persistence of cannabis use disorder (CUD) in young adults with first-episode psychosis (FEP) is associated with poor clinical and functional outcomes. Face-to-face psychological interventions are effective in treating CUD. However, their use in early intervention services (EISs) for psychosis is inconsistent because of barriers, including high workload and heterogeneity in training of clinicians and lack of motivation for treatment among patients. Tailoring new technology-based psychological interventions (TBPIs) to overcome these barriers is necessary to ensure their optimal acceptability. Objective: The aim of this study is twofold: to explore psychological intervention practices and intervention targets that are relevant for treating CUD in individuals with early psychosis and to explore factors related to the development and implementation of a technology-assisted psychological intervention. Methods: A total of 10 patients undergoing treatment for FEP and CUD in EISs participated in a focus group in June 2019. Semistructured individual interviews were conducted with 10 clinicians working in first-episode clinics in the province of Qu{\'e}bec, Canada. A hybrid inductive-deductive approach was used to analyze data. For the deductive analysis, we used categories of promoting strategies found in the literature shown to increase adherence to web-based interventions for substance use (ie, tailoring, reminders, delivery strategies, social support, and incentives). For the inductive analysis, we identified new themes through an iterative process of reviewing the data multiple times by two independent reviewers. Results: Data were synthesized into five categories of factors that emerged from data collection, and a narrative synthesis of commonalities and differences between patient and clinician perspectives was produced. The categories included attitudes and beliefs related to psychological interventions (eg, behavioral stage of change), strategies for psychological interventions (eg, motivational interviewing, cognitive behavioral therapy, psychoeducation, stress management), incentives (eg, contingency management), general interest in TBPIs (eg, facilitators and barriers of TBPIs), and tailoring of TBPIs (eg, application needs and preferences, outcome measures of interest for clinicians). Conclusions: This study provides a comprehensive portrait of the multifaceted needs and preferences of patients and clinicians related to TBPIs. Our results can inform the development of smartphone- or web-based psychological interventions for CUD in young adults with early psychosis. ", doi="10.2196/26562", url="https://formative.jmir.org/2021/4/e26562", url="http://www.ncbi.nlm.nih.gov/pubmed/33818397" } @Article{info:doi/10.2196/23144, author="Henson, Philip and Rodriguez-Villa, Elena and Torous, John", title="Investigating Associations Between Screen Time and Symptomatology in Individuals With Serious Mental Illness: Longitudinal Observational Study", journal="J Med Internet Res", year="2021", month="Mar", day="10", volume="23", number="3", pages="e23144", keywords="mHealth", keywords="schizophrenia", keywords="apps", keywords="mobile", keywords="screen time", abstract="Background: Increasing screen time exposure from digital devices like smartphones has shown a variety of mixed associations with cognition, behavior, and well-being in adults and children but little is known about its associations with symptomatology in individuals with serious mental illness. Objective: To determine the range of associations between screen time and symptoms of individuals with mental illness, we utilized a method called specification curve analysis. Methods: In this observational study, we recruited smartphone-owning adults (?18 years old) with schizophrenia and healthy controls. We installed 2 research-source smartphone apps, mindLAMP and Beiwe, to collect survey results, cognitive test results, and screen time metrics over a period of 3 months. Surveys were scheduled for twice a week, but participants were instructed to take the surveys naturally as much or as little as they wanted. Screen time was collected continuously in the background. A total of 140 participants was recruited from the outpatient clinic population as well as through general public advertising. Age-matched, smartphone-owning healthy controls were also part of the recruitment pool. A specification curve analysis was a priori designed to explore the relationship between every combination of independent variable and dependent variable in order to demonstrate to what degree screen time relates to symptoms in individuals with serious mental illness. Results: The sample consisted of 88 participants (54 with schizophrenia and 34 healthy controls) who completed both the initial and follow-up visits, completed at least one self-reported survey, and had a minimum passive data cutoff of 5 consecutive days. While we found an association between smartphone screen time metrics and cognition (adjusted R2=0.107, P<.001), specification curve analysis revealed a wide range of heterogenous associations with screen time from very negative to very positive. The effects differed based on diagnostic group, age bracket, type of regression model used, and the specific independent and dependent variables selected for analysis. Conclusions: The associations between screen time and mental health in patients with schizophrenia are heterogenous when examined with methods that reduce analytical bias. The heterogeneity in associations suggests that complex and personalized potential effects must be understood in the greater context of an individual. This analysis of longitudinally collected screen time data shows potential for future research that could benefit from high resolution metrics on smartphone use. ", doi="10.2196/23144", url="https://www.jmir.org/2021/3/e23144", url="http://www.ncbi.nlm.nih.gov/pubmed/33688835" } @Article{info:doi/10.2196/24055, author="Allan, Stephanie and Mcleod, Hamish and Bradstreet, Simon and Bell, Imogen and Whitehill, Helen and Wilson-Kay, Alison and Clark, Andrea and Matrunola, Claire and Morton, Emma and Farhall, John and Gleeson, John and Gumley, Andrew", title="Perspectives of Trial Staff on the Barriers to Recruitment in a Digital Intervention for Psychosis and How to Work Around Them: Qualitative Study Within a Trial", journal="JMIR Hum Factors", year="2021", month="Mar", day="5", volume="8", number="1", pages="e24055", keywords="recruitment", keywords="schizophrenia", keywords="mHealth", keywords="psychosis", keywords="mental health", abstract="Background: Recruitment processes for clinical trials of digital interventions for psychosis are seldom described in detail in the literature. Although trial staff have expertise in describing barriers to and facilitators of recruitment, a specific focus on understanding recruitment from the point of view of trial staff is rare, and because trial staff are responsible for meeting recruitment targets, a lack of research on their point of view is a key limitation. Objective: The primary aim of this study was to understand recruitment from the point of view of trial staff and discover what they consider important. Methods: We applied pluralistic ethnographic methods, including analysis of trial documents, observation, and focus groups, and explored the recruitment processes of the EMPOWER (Early Signs Monitoring to Prevent Relapse in Psychosis and Promote Well-being, Engagement, and Recovery) feasibility trial, which is a digital app--based intervention for people diagnosed with schizophrenia. Results: Recruitment barriers were categorized into 2 main themes: service characteristics (lack of time available for mental health staff to support recruitment, staff turnover, patient turnover [within Australia only], management styles of community mental health teams, and physical environment) and clinician expectations (filtering effects and resistance to research participation). Trial staff negotiated these barriers through strategies such as emotional labor (trial staff managing feelings and expressions to successfully recruit participants) and trying to build relationships with clinical staff working within community mental health teams. Conclusions: Researchers in clinical trials for digital psychosis interventions face numerous recruitment barriers and do their best to work flexibly and to negotiate these barriers and meet recruitment targets. The recruitment process appeared to be enhanced by trial staff supporting each other throughout the recruitment stage of the trial. ", doi="10.2196/24055", url="https://humanfactors.jmir.org/2021/1/e24055", url="http://www.ncbi.nlm.nih.gov/pubmed/33666555" } @Article{info:doi/10.2196/25722, author="Lustig, Andrew and Brookes, Gavin and Hunt, Daniel", title="Linguistic Analysis of Online Communication About a Novel Persecutory Belief System (Gangstalking): Mixed Methods Study", journal="J Med Internet Res", year="2021", month="Mar", day="5", volume="23", number="3", pages="e25722", keywords="internet", keywords="discourse analysis", keywords="psychosis", keywords="delusions", keywords="linguistics", keywords="language", keywords="online discourse", keywords="corpus linguistics", keywords="computer mediated communication", keywords="schizophrenia", keywords="eHealth", abstract="Background: Gangstalking is a novel persecutory belief system whereby those affected believe they are being followed, stalked, and harassed by a large number of people, often numbering in the thousands. The harassment is experienced as an accretion of innumerable individually benign acts such as people clearing their throat, muttering under their breath, or giving dirty looks as they pass on the street. Individuals affected by this belief system congregate in online fora to seek support, share experiences, and interact with other like-minded individuals. Such people identify themselves as targeted individuals. Objective: The objective of the study was to characterize the linguistic and rhetorical practices used by contributors to the gangstalking forum to construct, develop, and contest the gangstalking belief system. Methods: This mixed methods study employed corpus linguistics, which involves using computational techniques to examine recurring linguistic patterns in large, digitized bodies of authentic language data. Discourse analysis is an approach to text analysis which focuses on the ways in which linguistic choices made by text creators contribute to particular functions and representations. We assembled a 225,000-word corpus of postings on a gangstalking support forum. We analyzed these data using keyword analysis, collocation analysis, and manual examination of concordances to identify discursive and rhetorical practices among self-identified targeted individuals. Results: The gangstalking forum served as a site of discursive contest between 2 opposing worldviews. One is that gangstalking is a widespread, insidious, and centrally coordinated system of persecution employing community members, figures of authority, and state actors. This was the dominant discourse in the study corpus. The opposing view is a medicalized discourse supporting gangstalking as a form of mental disorder. Contributors used linguistic practices such as presupposition, nominalization, and the use of specialized jargon to construct gangstalking as real and external to the individual affected. Although contributors generally rejected the notion that they were affected by mental disorder, in some instances, they did label others in the forum as impacted/affected by mental illness if their accounts if their accounts were deemed to be too extreme or bizarre. Those affected demonstrated a concern with accumulating evidence to prove their position to incredulous others. Conclusions: The study found that contributors to the study corpus accomplished a number of tasks. They used linguistic practices to co-construct an internally coherent and systematized persecutory belief system. They advanced a position that gangstalking is real and contested the medicalizing discourse that gangstalking is a form of mental disorder. They supported one another by sharing similar experiences and providing encouragement and advice. Finally, they commiserated over the challenges of proving the existence of gangstalking. ", doi="10.2196/25722", url="https://www.jmir.org/2021/3/e25722", url="http://www.ncbi.nlm.nih.gov/pubmed/33666560" } @Article{info:doi/10.2196/24406, author="Granholm, Eric and Holden, Jason and Dwyer, Kristen and Mikhael, Tanya and Link, Peter and Depp, Colin", title="Mobile-Assisted Cognitive Behavioral Therapy for Negative Symptoms: Open Single-Arm Trial With Schizophrenia Patients", journal="JMIR Ment Health", year="2020", month="Dec", day="1", volume="7", number="12", pages="e24406", keywords="motivation", keywords="persistent negative symptoms", keywords="dysfunctional attitudes", keywords="mHealth", keywords="blended intervention", keywords="mobile phone", abstract="Background: Negative symptoms are an important unmet treatment need for schizophrenia. This study is a preliminary, open, single-arm trial of a novel hybrid intervention called mobile-assisted cognitive behavioral therapy for negative symptoms (mCBTn). Objective: The primary aim was to test whether mCBTn was feasible and could reduce severity of the target mechanism, defeatist performance attitudes, which are associated with experiential negative symptoms and poor functioning in schizophrenia. Methods: Participants with schizophrenia or schizoaffective disorder (N=31) who met prospective criteria for persistent negative symptoms were enrolled. The blended intervention combines weekly in-person group therapy with a smartphone app called CBT2go. The app extended therapy group skills, including recovery goal setting, thought challenging, scheduling of pleasurable activities and social interactions, and pleasure-savoring interventions to modify defeatist attitudes and improve experiential negative symptoms. Results: Retention was excellent (87\% at 18 weeks), and severity of defeatist attitudes and experiential negative symptoms declined significantly in the mCBTn intervention with large effect sizes. Conclusions: The findings suggest that mCBTn is a feasible and potentially effective treatment for experiential negative symptoms, if confirmed in a larger randomized controlled trial. The findings also provide support for the defeatist attitude model of experiential negative symptoms and suggest that blended technology-supported interventions such as mCBTn can strengthen and shorten intensive psychosocial interventions for schizophrenia. Trial Registration: ClinicalTrials.gov NCT03179696; https://clinicaltrials.gov/ct2/show/NCT03179696 ", doi="10.2196/24406", url="https://mental.jmir.org/2020/12/e24406", url="http://www.ncbi.nlm.nih.gov/pubmed/33258792" } @Article{info:doi/10.2196/22631, author="Cai, Yiyuan and Gong, Wenjie and He, Hua and Hughes, P. James and Simoni, Jane and Xiao, Shuiyuan and Gloyd, Stephen and Lin, Meijuan and Deng, Xinlei and Liang, Zichao and He, Wenjun and Dai, Bofeng and Liao, Jing and Hao, Yuantao and Xu, (Roman) Dong", title="Mobile Texting and Lay Health Supporters to Improve Schizophrenia Care in a Resource-Poor Community in Rural China (LEAN Trial): Randomized Controlled Trial Extended Implementation", journal="J Med Internet Res", year="2020", month="Dec", day="1", volume="22", number="12", pages="e22631", keywords="medication adherence", keywords="mobile texting", keywords="lay health worker", keywords="resource-poor community", keywords="primary health care", keywords="quality of care", keywords="mHealth", keywords="schizophrenia", abstract="Background: Schizophrenia is a severe and disabling condition that presents a dire health equity challenge. Our initial 6-month trial (previously reported) using mobile texting and lay health supporters, called LEAN, significantly improved medication adherence from 0.48 to 0.61 (adjusted mean 0.11, 95\% CI 0.03 to 0.20, P=.007) for adults with schizophrenia living in a resource-poor village in rural China. Objective: We explored the effectiveness of our texting program in improving participants' medication adherence, functioning, and symptoms in an extended implementation of the intervention after its initial phase. Methods: In an approximated stepped-wedge wait-list design randomized controlled trial, 277 community-dwelling villagers with schizophrenia were assigned 1:1 in phase 1 into intervention and wait-list control groups. The intervention group received (1) lay health supporters (medication or care supervisors), (2) e-platform (mobile-texting reminders and education message) access, (3) a token gift for positive behavioral changes, and (4) integration with the existing government community-mental health program (the 686 Program) while the wait-listed control group initially only received the 686 Program. Subsequently (in the extended period), both groups received the LEAN intervention plus the 686 Program. The primary outcome was antipsychotic medication adherence (percentage of dosages taken over the past month assessed by unannounced home-based pill counts). The secondary outcomes were symptoms measured during visits to 686 Program psychiatrists using the Clinical Global Impression scale for schizophrenia and functioning measured by trained student assessors using the World Health Organization Disability Assessment Schedule 2.0. Other outcomes included data routinely collected in the 686 Program system (refill records, rehospitalization due to schizophrenia, death for any reason, suicide, wandering, and violent behaviors). We used intention-to-treat analysis and missing data were imputed. A generalized estimating equation model was used to assess program effects on antipsychotics medication adherence, symptoms, and functioning. Results: Antipsychotics medication adherence improved from 0.48 in the control period to 0.58 in the extended intervention period (adjusted mean difference 0.11, 95\% CI 0.04 to 0.19; P=.004). We also noted an improvement in symptoms (adjusted mean difference --0.26, 95\% CI --0.50 to --0.02; P=.04; Cohen d effect size 0.20) and a reduction in rehospitalization (0.37, 95\% CI 0.18 to 0.76; P=.007; number-needed-to-treat 8.05, 95\% CI 4.61 to 21.41). There was no improvement in functioning (adjusted mean difference 0.02, 95\% CI --0.01 to 0.06; P=.18; Cohen d effect size 0.04). Conclusions: In an extended implementation, our intervention featuring mobile texting messages and lay health workers in a resource-poor community setting was more effective than the 686 Program alone in improving medication adherence, improving symptoms, and reducing rehospitalization. Trial Registration: Chinese Clinical Trial Registry; ChiCTR-ICR-15006053 https://tinyurl.com/y5hk8vng ", doi="10.2196/22631", url="https://www.jmir.org/2020/12/e22631", url="http://www.ncbi.nlm.nih.gov/pubmed/33258788" } @Article{info:doi/10.2196/22997, author="Bonet, Lucia and Torous, John and Arce, David and Blanquer, Ignacio and Sanjuan, Julio", title="ReMindCare App for Early Psychosis: Pragmatic Real World Intervention and Usability Study", journal="JMIR Mhealth Uhealth", year="2020", month="Nov", day="6", volume="8", number="11", pages="e22997", keywords="app", keywords="clinical practice", keywords="mental health", keywords="psychosis", keywords="real-world intervention", keywords="telemedicine", abstract="Background: eHealth interventions are widely used in clinical trials and increasingly in care settings as well; however, their efficacy in real-world contexts remains unknown. ReMindCare is a smartphone app that has been systematically implemented in a first episode of psychosis program (FEPP) for patients with early psychosis since 2018. Objective: The objective of this study was to assess the efficacy of ReMindCare after 19 months of use in the clinic and varying use by individual patients. Methods: The integration of the ReMindCare app into the FEPP started in October 2018. Patients with early psychosis self-selected to the app (ReMindCare group) or treatment as usual (TAU group). The outcome variables considered were adherence to the intervention and number of relapses, hospital admissions, and visits to urgent care units. Data from 90 patients with early psychosis were analyzed: 59 in the ReMindCare group and 31 in the TAU group. The mean age of the sample was 32.8 (SD 9.4) years, 73\% (66/90) were males, 91\% (83/90) were White, and 81\% (74/90) were single. Results: Significant differences between the ReMindCare and TAU groups were found in the number of relapses, hospitalizations, and visits to urgent care units, with each showing benefits for the app. Only 20\% (12/59) of patients from the ReMindCare group had a relapse, while 58\% (18/31) of the TAU patients had one or more relapses ($\chi$2=13.7, P=.001). Moreover, ReMindCare patients had fewer visits to urgent care units ($\chi$2=7.4, P=.006) and fewer hospitalizations than TAU patients ($\chi$2=4.6, P=.03). The mean of days using the app was 352.2 (SD 191.2; min/max: 18-594), and the mean of engagement was 84.5 (SD 16.04). Conclusions: To our knowledge, this is the first eHealth intervention that has preliminarily proven its benefits in the real-world treatment of patients with early psychosis. International Registered Report Identifier (IRRID): RR2-10.1111/eip.12960 ", doi="10.2196/22997", url="https://mhealth.jmir.org/2020/11/e22997", url="http://www.ncbi.nlm.nih.gov/pubmed/33155986" } @Article{info:doi/10.2196/19887, author="Lal, Shalini and Gleeson, John and Rivard, Lysanne and D'Alfonso, Simon and Joober, Ridha and Malla, Ashok and Alvarez-Jimenez, Mario", title="Adaptation of a Digital Health Innovation to Prevent Relapse and Support Recovery in Youth Receiving Services for First-Episode Psychosis: Results From the Horyzons-Canada Phase 1 Study", journal="JMIR Form Res", year="2020", month="Oct", day="29", volume="4", number="10", pages="e19887", keywords="psychotic disorders", keywords="mental health", keywords="telemedicine", keywords="young adult", keywords="mental health services", keywords="cultural adaptation", keywords="mobile phone", keywords="e-mental health", keywords="virtual care", keywords="schizophrenia", keywords="e-health", abstract="Background: Developing a digital health innovation can require a substantial amount of financial and human resource investment before it can be scaled for implementation across geographical, cultural, and health care contexts. As such, there is an increased interest in leveraging eHealth innovations developed and tested in one country or jurisdiction and using these innovations in local settings. However, limited knowledge exists on the processes needed to appropriately adapt digital health innovations to optimize their transferability across geographical, cultural, and contextual settings. Objective: We report on the results of an adaptation study of Horyzons, a digital health innovation originally developed and tested in Australia. Horyzons is designed to prevent relapses and support recovery in young people receiving services for first-episode psychosis (FEP). The aim of this study is to assess the initial acceptability of Horyzons and adapt it in preparation for pilot testing in Canada. Methods: This research took place in 2 specialized early intervention clinics for FEP, located in 1 urban and 1 urban-rural setting, in 2 Canadian provinces. A total of 26 participants were recruited: 15 clinicians (age range 26-56 years) and 11 patients (age range 19-37 years). Following the digital health adaptation framework developed by our team, we used a mixed methods approach, combining descriptive quantitative and qualitative methods across 3 stages of data collection (focus groups, interviews, and consultations), analysis, and adaptations. Results: Overall, patients and clinicians appreciated the strengths-based approach and social media features of Horyzons. However, participants expressed concerns related to implementation, especially in relation to capacity (eg, site moderation, crisis management, internet speed in rural locations). They also provided suggestions for adapting content and features, for example, in relation to community resources, volume of text, universal accessibility (eg, for individuals with limitations in vision), and optimization of platform accessibility through mobile devices. Additional aspects of the innovation were flagged for adaptation during the final stages of preparing it for live implementation. These included terms of use, time zone configuration to reflect local time and date, safety and moderation protocols, the need help now feature, and the list of trigger words to flag posts indicative of potential risk. Conclusions: In the context of the COVID-19 pandemic and public health guidelines for social distancing, there is an increasing interest and need to leverage the internet and mobile technologies for delivering youth mental health services. As countries look to one another for guidance on how to navigate changing social dynamics, knowledge on how to utilize and adapt existing innovations across contexts is now more important than ever. Using a systematic approach, this study illustrates the methods, processes, results, and lessons learned on adapting a digital health innovation to enhance its local acceptability. International Registered Report Identifier (IRRID): RR2-10.2196/resprot.8810 ", doi="10.2196/19887", url="http://formative.jmir.org/2020/10/e19887/", url="http://www.ncbi.nlm.nih.gov/pubmed/33118945" } @Article{info:doi/10.2196/18505, author="Kim, Hyunmin and Choi, Young In and Kim, Dai-Jin", title="Excessive Smartphone Use and Self-Esteem Among Adults With Internet Gaming Disorder: Quantitative Survey Study", journal="JMIR Mhealth Uhealth", year="2020", month="Sep", day="29", volume="8", number="9", pages="e18505", keywords="excessive smartphone use", keywords="internet gaming disorder", keywords="smartphone overuse", keywords="self-esteem", keywords="mental health", keywords="gender difference", keywords="Korean smartphone addiction proneness scale", keywords="smartphone", keywords="gaming", keywords="young adult", keywords="adult", keywords="gender", abstract="Background: Smartphone overuse can harm individual health and well-being. Although several studies have explored the relationship between problematic or excessive smartphone use and mental health, much less is known about effects on self-esteem, which is essential in having a healthy life, among adults with mental health disorders, including internet gaming disorder. Furthermore, given that smartphone usage differs by gender, little is known about gender differences in the relationship between smartphone overuse and self-esteem. Objective: The objective of this study was to assess self-esteem among individuals with mental health disorders and explore the relationship with excessive smartphone use. Methods: Participants were selected based on their responses to the internet gaming disorder assessment, which includes 9 items developed based on Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) criteria, from among a Korean cohort of smartphone users aged 20-40 years, resulting in a sample of 189 participants (men:120, women: 69). The Rosenberg self-esteem scale and the Korean smartphone addiction proneness scale were utilized to assess the outcome self-esteem with excessive smartphone use as the primary independent variable. Guided by the Bowlby attachment theory and prior studies, we selected several covariates. Generalized linear regression analyses, as well as subgroup analyses by gender, were performed. Results: Among adults with internet gaming disorder, the average Korean smartphone addiction proneness scale score was significantly higher in women than that in men (41.30 vs. 37.94; P=.001), and excessive smartphone use was significantly more prevalent in women than it was in men (30.43\% vs. 20.83\%; P=.02). Our findings from the generalized linear regression analyses indicated that an increase in Korean smartphone addiction proneness scale score had a negative relationship with self-esteem among those with internet gaming disorder ($\beta$=--0.18, P=.001). Furthermore, our interaction models showed that, among those with internet gaming disorder, more men than women had lower self-esteem associated with an increase in Korean smartphone addiction proneness scale score and a high degree of smartphone overuse ($\beta$=--0.19, P=.004; $\beta$=--3.73, P<.001). Conclusions: Excessive smartphone use was found to be adversely associated with self-esteem among young and middle-aged adults with internet gaming disorder; notably, more men than women were negatively influenced (regarding self-esteem) by smartphone overuse. Based on our findings, more efforts should be made to reduce excessive or problematic smartphone use by considering developing public health interventions or policy, particularly among those with mental health disorders such as internet gaming disorder. ", doi="10.2196/18505", url="https://mhealth.jmir.org/2020/9/e18505", url="http://www.ncbi.nlm.nih.gov/pubmed/32990637" } @Article{info:doi/10.2196/18663, author="Yu, Yu and Li, Yilu and Li, Tongxin and Xi, Shijun and Xiao, Xi and Xiao, Shuiyuan and Tebes, Kraemer Jacob", title="New Path to Recovery and Well-Being: Cross-Sectional Study on WeChat Use and Endorsement of WeChat-Based mHealth Among People Living With Schizophrenia in China", journal="J Med Internet Res", year="2020", month="Sep", day="18", volume="22", number="9", pages="e18663", keywords="WeChat", keywords="mHealth", keywords="schizophrenia", keywords="China", keywords="symptoms", keywords="functioning", keywords="recovery", keywords="quality of life", keywords="well-being", abstract="Background: The past few decades have seen an exponential increase in using mobile phones to support medical care (mobile health [mHealth]) among people living with psychosis worldwide, yet little is known about WeChat use and WeChat-based mHealth among people living with schizophrenia (PLS) in China. Objective: This study aims to assess WeChat use, endorsement of WeChat-based mHealth programs, and health related to WeChat use among PLS. Methods: We recruited a random sample of 400 PLS from 12 communities in Changsha City of Hunan Province, China. WeChat use was assessed using the adapted WeChat Use Intensity Questionnaire (WUIQ). We also compared psychiatric symptoms, functioning, disability, recovery, quality of life, and general well-being between WeChat users and nonusers using one-to-one propensity-score matching. Results: The WeChat use rate was 40.8\% in this sample (163/400); 30.7\% (50/163) had more than 50 WeChat friends and nearly half (81/163, 49.7\%) spent more than half an hour on WeChat, a pattern similar to college students and the elderly. PLS also showed higher emotional connectedness to WeChat use than college students. About 80.4\% (131/163) of PLS were willing to participate in a WeChat-based mHealth program, including psychoeducation (91/163, 55.8\%), professional support (82/163, 50.3\%), and peer support (67/163, 41.1\%). Compared with nonusers, WeChat users were younger, better educated, and more likely to be employed. WeChat use was associated with improved health outcomes, including lower psychiatric symptoms, lower depression, higher functioning, better recovery, and higher quality of life. Conclusions: WeChat-based mHealth programs hold promise as an empowering tool to provide cost-effective interventions, to foster global recovery, and to improve both physical and mental well-being among PLS. WeChat and WeChat-based mHealth programs have the potential to offer a new path to recovery and well-being for PLS in China. ", doi="10.2196/18663", url="http://www.jmir.org/2020/9/e18663/", url="http://www.ncbi.nlm.nih.gov/pubmed/32945774" } @Article{info:doi/10.2196/19348, author="Birnbaum, Leo Michael and Kulkarni, ``Param'' Prathamesh and Van Meter, Anna and Chen, Victor and Rizvi, F. Asra and Arenare, Elizabeth and De Choudhury, Munmun and Kane, M. John", title="Utilizing Machine Learning on Internet Search Activity to Support the Diagnostic Process and Relapse Detection in Young Individuals With Early Psychosis: Feasibility Study", journal="JMIR Ment Health", year="2020", month="Sep", day="1", volume="7", number="9", pages="e19348", keywords="schizophrenia spectrum disorders", keywords="internet search activity", keywords="Google", keywords="diagnostic prediction", keywords="relapse prediction", keywords="machine learning", keywords="digital data", keywords="digital phenotyping", keywords="digital biomarkers", abstract="Background: Psychiatry is nearly entirely reliant on patient self-reporting, and there are few objective and reliable tests or sources of collateral information available to help diagnostic and assessment procedures. Technology offers opportunities to collect objective digital data to complement patient experience and facilitate more informed treatment decisions. Objective: We aimed to develop computational algorithms based on internet search activity designed to support diagnostic procedures and relapse identification in individuals with schizophrenia spectrum disorders. Methods: We extracted 32,733 time-stamped search queries across 42 participants with schizophrenia spectrum disorders and 74 healthy volunteers between the ages of 15 and 35 (mean 24.4 years, 44.0\% male), and built machine-learning diagnostic and relapse classifiers utilizing the timing, frequency, and content of online search activity. Results: Classifiers predicted a diagnosis of schizophrenia spectrum disorders with an area under the curve value of 0.74 and predicted a psychotic relapse in individuals with schizophrenia spectrum disorders with an area under the curve of 0.71. Compared with healthy participants, those with schizophrenia spectrum disorders made fewer searches and their searches consisted of fewer words. Prior to a relapse hospitalization, participants with schizophrenia spectrum disorders were more likely to use words related to hearing, perception, and anger, and were less likely to use words related to health. Conclusions: Online search activity holds promise for gathering objective and easily accessed indicators of psychiatric symptoms. Utilizing search activity as collateral behavioral health information would represent a major advancement in efforts to capitalize on objective digital data to improve mental health monitoring. ", doi="10.2196/19348", url="https://mental.jmir.org/2020/9/e19348", url="http://www.ncbi.nlm.nih.gov/pubmed/32870161" } @Article{info:doi/10.2196/18538, author="Yu, Yu and Li, Tongxin and Xi, Shijun and Li, Yilu and Xiao, Xi and Yang, Min and Ge, Xiaoping and Xiao, Shuiyuan and Tebes, Jacob", title="Assessing a WeChat-Based Integrative Family Intervention (WIFI) for Schizophrenia: Protocol for a Stepped-Wedge Cluster Randomized Trial", journal="JMIR Res Protoc", year="2020", month="Aug", day="25", volume="9", number="8", pages="e18538", keywords="schizophrenia", keywords="family intervention", keywords="WeChat", keywords="psychoeducation", keywords="peer support", keywords="professional support", keywords="stepped wedge", abstract="Background: Schizophrenia is a persistent and debilitating mental illness, and its prognosis depends largely on supportive care and systematic treatment. In developing countries like China, families constitute the major caregiving force for schizophrenia and are faced with many challenges, such as lack of knowledge, skills, and resources. The approach to support family caregiving in an accessible, affordable, feasible, and cost-effective way remains unclear. The wide-spread use of WeChat provides a promising and cost-effective medium for support. Objective: We aim to present a protocol for assessing a WeChat-based integrative family intervention (WIFI) to support family caregiving for schizophrenia. Methods: We will develop a WIFI program that includes the following three core components: (1) psychoeducation (WeChat official account), (2) peer support (WeChat chat group), and (3) professional support (WeChat video chat). A rigorous stepped-wedge cluster randomized trial will be used to evaluate the implementation, effectiveness, and cost of the WIFI program. The WIFI program will be implemented in 12 communities affiliated with Changsha Psychiatric Hospital through the free medicine delivery process in the 686 Program. The 12 communities will be randomized to one of four fixed sequences every 2 months during an 8-month intervention period in four clusters of three communities each. Outcomes will be assessed for both family caregivers and people with schizophrenia. Family caregivers will be assessed for their knowledge and skills about caregiving, social support, coping, perceived stigma, caregiver burden, family functioning, positive feelings, and psychological distress. People with schizophrenia will be assessed for their symptoms, functioning, quality of life, recovery, and rehospitalization. Cost data, such as intervention costs, health care utilization costs, and costs associated with lost productivity, will be collected. Moreover, we will collect process data, including fidelity and quality of program implementation, as well as user attitude data. Treatment effects will be estimated using generalized linear maximum likelihood mixed modeling with clusters as a random effect and time as a fixed effect. Cost-effectiveness analysis will be performed from the societal perspective using incremental cost-effectiveness ratios. Qualitative analysis will use the grounded theory approach and immersion-crystallization process. Results: The study was funded in August 2018 and approved by the institutional review board on January 15, 2019. Preliminary baseline data collection was conducted in May 2019 and completed in September 2019. The WIFI program is expected to start in September 2020. Conclusions: This is the first study to assess a WeChat-based mHealth intervention to support family caregiving for schizophrenia in China. The innovative study will contribute to the development of a more cost-effective and evidence-based family management model in the community for people with schizophrenia, and the approach could potentially be integrated into national policy and adapted for use in other populations. Trial Registration: ClinicalTrials.gov NCT04393896; https://clinicaltrials.gov/ct2/show/NCT04393896. International Registered Report Identifier (IRRID): PRR1-10.2196/18538 ", doi="10.2196/18538", url="http://www.researchprotocols.org/2020/8/e18538/", url="http://www.ncbi.nlm.nih.gov/pubmed/32687478" } @Article{info:doi/10.2196/17019, author="Lewis, Shon and Ainsworth, John and Sanders, Caroline and Stockton-Powdrell, Charlotte and Machin, Matthew and Whelan, Pauline and Hopkins, Richard and He, Zhimin and Applegate, Eve and Drake, Richard and Bamford, Charlie and Roberts, Chris and Wykes, Til", title="Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial", journal="J Med Internet Res", year="2020", month="Aug", day="13", volume="22", number="8", pages="e17019", keywords="digital", keywords="smartphone", keywords="m-health", keywords="psychosis", keywords="mental health", keywords="self management", abstract="Background: Improving recovery from acute symptoms and preventing relapse are two significant challenges in severe mental illness. We developed a personalized smartphone-based app to monitor symptoms in real time and validated its acceptance, reliability, and validity. Objective: To assess (i) acceptability of continuous monitoring to SMI patients and health professionals over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; and (iii) the feasibility of detecting early warning signs of relapse. Methods: The active symptom monitoring smartphone app was built into an end-to-end system in two NHS Trusts to enable real-time symptom self-monitoring and detection by the clinical team of early signs of relapse in people with severe mental illness. We conducted an open randomized controlled trial of active symptom monitoring compared to usual management to assess: (i) acceptability and safety of continuous monitoring over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; (iii) feasibility of detecting early warning signs of relapse communicated to the healthcare staff via an app streaming data to the electronic health record. Eligible participants with a Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) diagnosis of schizophrenia and related disorders, and a history of relapse within the previous two years were enrolled from an early intervention team and a community mental health team. Results: Of 181 eligible patients, 81 (45\%) consented and were randomized to either active symptom monitoring or management as usual. At 12 weeks, 90\% (33/36) of those in the active monitoring group continued to use the system and exhibited an adherence rate (defined as responding to >33\% of alerts) of 84\% (30/36\}. Active symptom monitoring was associated with no difference on the empowerment scale in comparison to the usual management group at 12 weeks. The pre-planned intent-to-treat analysis of the primary outcome, a positive score on the Positive and Negative Syndrome Scale (PANSS) scale, showed a significant reduction in the active symptom monitoring group over 12 weeks in the early intervention center. Alerts for personalized early warning signs of relapse were built into the workflows of both NHS Trusts, and 100\% of health professional staff used the system in a new digital workflow. Qualitative analyses supported the acceptability of the system to participants and staff. Conclusions: The active smartphone monitoring system is feasible and was accepted by users in a 3-month study of people with severe mental illness, with surprisingly high levels of adherence. App use was associated with psychotic symptom improvement in recent-onset participants, but not those with longstanding illness, supporting the notion of improved self-management. When built into clinical management workflows to enable personalized alerts of symptom deterioration, the app has demonstrated utility in promoting earlier intervention for relapse. Trial Registration: ISRCTN Registry ISRCTN88145142; http://www.isrctn.com/ISRCTN88145142 ", doi="10.2196/17019", url="https://www.jmir.org/2020/8/e17019", url="http://www.ncbi.nlm.nih.gov/pubmed/32788150" } @Article{info:doi/10.2196/16969, author="Yoo, Whi Dong and Birnbaum, L. Michael and Van Meter, R. Anna and Ali, F. Asra and Arenare, Elizabeth and Abowd, D. Gregory and De Choudhury, Munmun", title="Designing a Clinician-Facing Tool for Using Insights From Patients' Social Media Activity: Iterative Co-Design Approach", journal="JMIR Ment Health", year="2020", month="Aug", day="12", volume="7", number="8", pages="e16969", keywords="social media", keywords="psychotic disorders", keywords="information technology", abstract="Background: Recent research has emphasized the need for accessing information about patients to augment mental health patients' verbal reports in clinical settings. Although it has not been introduced in clinical settings, computational linguistic analysis on social media has proved it can infer mental health attributes, implying a potential use as collateral information at the point of care. To realize this potential and make social media insights actionable to clinical decision making, the gaps between computational linguistic analysis on social media and the current work practices of mental health clinicians must be bridged. Objective: This study aimed to identify information derived from patients' social media data that can benefit clinicians and to develop a set of design implications, via a series of low-fidelity (lo-fi) prototypes, on how to deliver the information at the point of care. Methods: A team of clinical researchers and human-computer interaction (HCI) researchers conducted a long-term co-design activity for over 6 months. The needs-affordances analysis framework was used to refine the clinicians' potential needs, which can be supported by patients' social media data. On the basis of those identified needs, the HCI researchers iteratively created 3 different lo-fi prototypes. The prototypes were shared with both groups of researchers via a videoconferencing software for discussion and feedback. During the remote meetings, potential clinical utility, potential use of the different prototypes in a treatment setting, and areas of improvement were discussed. Results: Our first prototype was a card-type interface that supported treatment goal tracking. Each card included attribute levels: depression, anxiety, social activities, alcohol, and drug use. This version confirmed what types of information are helpful but revealed the need for a glanceable dashboard that highlights the trends of these information. As a result, we then developed the second prototype, an interface that shows the clinical state and trend. We found that focusing more on the changes since the last visit without visual representation can be more compatible with clinicians' work practices. In addition, the second phase of needs-affordances analysis identified 3 categories of information relevant to patients with schizophrenia: symptoms related to psychosis, symptoms related to mood and anxiety, and social functioning. Finally, we developed the third prototype, a clinical summary dashboard that showed changes from the last visit in plain texts and contrasting colors. Conclusions: This exploratory co-design research confirmed that mental health attributes inferred from patients' social media data can be useful for clinicians, although it also revealed a gap between computational social media analyses and clinicians' expectations and conceptualizations of patients' mental health states. In summary, the iterative co-design process crystallized design directions for the future interface, including how we can organize and provide symptom-related information in a way that minimizes the clinicians' workloads. ", doi="10.2196/16969", url="http://mental.jmir.org/2020/8/e16969/", url="http://www.ncbi.nlm.nih.gov/pubmed/32784180" } @Article{info:doi/10.2196/17808, author="Nijman, Anne Saskia and Veling, Wim and Greaves-Lord, Kirstin and Vos, Maarten and Zandee, Regina Catharina Elizabeth and Aan het Rot, Marije and Geraets, Wil Chris Neeltje and Pijnenborg, Maria Gerdina Hendrika", title="Dynamic Interactive Social Cognition Training in Virtual Reality (DiSCoVR) for People With a Psychotic Disorder: Single-Group Feasibility and Acceptability Study", journal="JMIR Ment Health", year="2020", month="Aug", day="7", volume="7", number="8", pages="e17808", keywords="social cognition", keywords="virtual reality", keywords="psychotic disorder", keywords="cognitive remediation therapy", keywords="emotion perception", keywords="theory of mind", keywords="social cognition training", abstract="Background: People with a psychotic disorder commonly experience problems in social cognition and functioning. Social cognition training (SCT) improves social cognition, but may inadequately simulate real-life social interactions. Virtual reality (VR) provides a realistic, interactive, customizable, and controllable training environment, which could facilitate the application of skills in daily life. Objective: We developed a 16-session immersive VR SCT (Dynamic Interactive Social Cognition Training in Virtual Reality [DiSCoVR]) and conducted a single-group feasibility pilot study. Methods: A total of 22 people with a psychotic disorder and reported problems in social cognition participated. Feasibility and acceptability were assessed using a survey for participants and therapists, and by examining relevant parameters (eg, dropouts). We analyzed preliminary treatment effects on social cognition, neurocognition, and psychiatric symptoms. Results: A total of 17 participants completed the study. Participants enjoyed DiSCoVR (mean 7.25, SD 2.05; range 3-10), thought it was useful for daily social activities (mean 7.00, SD 2.05; range 3-10), and enjoyed the combination of VR and a therapist (mean 7.85, SD 2.11; range 3-10). The most frequently mentioned strength of DiSCoVR was the opportunity to practice with personalized social situations (14/20, 70\%). A significant improvement of emotion perception was observed (Ekman 60 Faces; t16=--4.79, P<.001, d=--0.67), but no significant change was found in other measures of social cognition, neurocognition, psychiatric symptoms, or self-esteem. Conclusions: DiSCoVR was feasible and acceptable to participants and therapists, and may improve emotion perception. ", doi="10.2196/17808", url="https://mental.jmir.org/2020/8/e17808", url="http://www.ncbi.nlm.nih.gov/pubmed/32763880" } @Article{info:doi/10.2196/17204, author="Tremain, Hailey and McEnery, Carla and Fletcher, Kathryn and Murray, Greg", title="The Therapeutic Alliance in Digital Mental Health Interventions for Serious Mental Illnesses: Narrative Review", journal="JMIR Ment Health", year="2020", month="Aug", day="7", volume="7", number="8", pages="e17204", keywords="mental health", keywords="mHealth", keywords="eHealth", keywords="telehealth", keywords="psychosis", keywords="bipolar disorder", keywords="mobile phone", abstract="Background: Digital mental health interventions offer unique advantages, and research indicates that these interventions are effective for a range of mental health concerns. Although these interventions are less established for individuals with serious mental illnesses, they demonstrate significant promise. A central consideration in traditional face-to-face therapies is the therapeutic alliance, whereas the nature of a digital therapeutic alliance and its relationship with outcomes requires further attention, particularly for individuals with serious mental illnesses. Objective: This narrative review aims to encourage further consideration and critical evaluation of the therapeutic alliance in digital mental health, specifically for individuals with serious mental illnesses. Methods: A narrative review was conducted by combining 3 main areas of the literature: the first examining the evidence for digital mental health interventions for serious mental illnesses, the second illuminating the nature and role of the therapeutic alliance in digital interventions, and the third surrounding practical considerations to enhance a digital therapeutic alliance. Results: Results indicated that a therapeutic alliance can be cultivated in digital interventions for those with serious mental illnesses, but that it may have unique, yet-to-be-confirmed characteristics in digital contexts. In addition, a therapeutic alliance appears to be less directly associated with outcomes in digital interventions than with those in face-to-face therapies. One possibility is that the digital therapeutic alliance is associated with increased engagement and adherence to digital interventions, through which it appears to influence outcomes. A number of design and implementation considerations may enhance the digital therapeutic alliance, including human support and technological features. Conclusions: More research is required to further understand the nature and specific role of a therapeutic alliance in digital interventions for serious mental illnesses, particularly in informing their design. This review revealed several key research priorities to advance the therapeutic alliance in digital interventions. ", doi="10.2196/17204", url="https://mental.jmir.org/2020/8/e17204", url="http://www.ncbi.nlm.nih.gov/pubmed/32763881" } @Article{info:doi/10.2196/19778, author="Vaidyam, Aditya and Roux, Spencer and Torous, John", title="Patient Innovation in Investigating the Effects of Environmental Pollution in Schizophrenia: Case Report of Digital Phenotyping Beyond Apps", journal="JMIR Ment Health", year="2020", month="Aug", day="3", volume="7", number="8", pages="e19778", keywords="digital mental health", keywords="mHealth", keywords="apps", keywords="serious mental illness", keywords="schizophrenia", keywords="psychiatry", keywords="digital phenotyping", doi="10.2196/19778", url="https://mental.jmir.org/2020/8/e19778", url="http://www.ncbi.nlm.nih.gov/pubmed/32559173" } @Article{info:doi/10.2196/18990, author="Valentine, Lee and McEnery, Carla and Bell, Imogen and O'Sullivan, Shaunagh and Pryor, Ingrid and Gleeson, John and Bendall, Sarah and Alvarez-Jimenez, Mario", title="Blended Digital and Face-to-Face Care for First-Episode Psychosis Treatment in Young People: Qualitative Study", journal="JMIR Ment Health", year="2020", month="Jul", day="28", volume="7", number="7", pages="e18990", keywords="Blended Treatment", keywords="Psychotic Disorders", keywords="Digital Intervention", keywords="Adolescent", keywords="Young Adults", keywords="mHealth", abstract="Background: A small number of studies have found that digital mental health interventions can be feasible and acceptable for young people experiencing first-episode psychosis; however, little research has examined how they might be blended with face-to-face approaches in order to enhance care. Blended treatment refers to the integration of digital and face-to-face mental health care. It has the potential to capitalize on the evidence-based features of both individual modalities, while also exceeding the sum of its parts. This integration could bridge the online--offline treatment divide and better reflect the interconnected, and often complementary, ways young people navigate their everyday digital and physical lives. Objective: This study aimed to gain young people's perspectives on the design and implementation of a blended model of care in first-episode psychosis treatment. Methods: This qualitative study was underpinned by an end-user development framework and was based on semistructured interviews with 10 participants aged 19 to 28 (mean 23.4, SD 2.62). A thematic analysis was used to analyze the data. Results: Three superordinate themes emerged relating to young people's perspectives on the design and implementation of a blended model of care in first-episode psychosis treatment: (1) blended features, (2) cautions, and (3) therapeutic alliance. Conclusions: We found that young people were very enthusiastic about the prospect of blended models of mental health care, in so far as it was used to enhance their experience of traditional face-to-face treatment but not to replace it overall. Aspects of blended treatment that could enhance clinical care were readily identified by young people as increasing accessibility, continuity, and consolidation; accessing posttherapy support; strengthening the relationship between young person and clinician; and tracking personal data that could be used to better inform clinical decision making. Future research is needed to investigate the efficacy of blended models of care by evaluating its impact on the therapeutic alliance, clinical and social outcomes, cost-effectiveness, and engagement. ", doi="10.2196/18990", url="http://mental.jmir.org/2020/7/e18990/", url="http://www.ncbi.nlm.nih.gov/pubmed/32720904" } @Article{info:doi/10.2196/19497, author="Romm, Lie Kristin and Nilsen, Liv and Gjermundsen, Kristine and Holter, Marit and Fjell, Anne and Melle, Ingrid and Rep{\aa}l, Arne and Lobban, Fiona", title="Remote Care for Caregivers of People With Psychosis: Mixed Methods Pilot Study", journal="JMIR Ment Health", year="2020", month="Jul", day="28", volume="7", number="7", pages="e19497", keywords="REACT", keywords="psychosis", keywords="family work", keywords="early intervention", keywords="psychoeducation", keywords="mental health service", keywords="innovation", keywords="eHealth", abstract="Background: A reduced availability of resources has hampered the implementation of family work in psychosis. Web-based support programs have the potential to increase access to high-quality, standardized resources. This pilot study tested the Norwegian version of the Relatives Education and Coping Toolkit (REACT), a web-based United Kingdom National Health Service program in combination with phone-based support by trained family therapists. Objective: We investigated how the program was perceived by its users and identified the facilitators and barriers to its clinical implementation. Methods: Relatives of people with psychosis were offered access to REACT and to weekly family therapist support (with 1 of 2 trained family therapists) for 26 weeks. Level of distress and level of expressed emotion data were collected at baseline and after 26 weeks using the Family Questionnaire and the Relatives Stress Scale. Both family therapists and a subset of the relatives were interviewed about their experiences after completing the program. Results: During the program, relatives (n=19) had a median of 8 (range 4-11) consultations with the family therapists. Postintervention, there was a significant reduction in stress and in expressed emotions in the relatives of people with psychosis. Interviews with the relatives (n=7) and the family therapists (n=2) indicated the following themes as important---the intervention turned knowledge into action; the intervention strengthened the feeling of being involved and taken seriously by the health services; and management support and the ability for self-referral were important, while lack of reimbursement and clinician resistance to technology were barriers to implementation. Conclusions: The service was found to offer a valued clinical benefit; however, strategies that aim to engage clinicians and increase organizational support toward new technology need to be developed. ", doi="10.2196/19497", url="http://mental.jmir.org/2020/7/e19497/", url="http://www.ncbi.nlm.nih.gov/pubmed/32720905" } @Article{info:doi/10.2196/14865, author="Choi, TH William and Yu, KS Dan and Wong, Terry and Lantta, Tella and Yang, Min and V{\"a}lim{\"a}ki, Maritta", title="Habits and Attitudes of Video Gaming and Information Technology Use in People with Schizophrenia: Cross-Sectional Survey", journal="J Med Internet Res", year="2020", month="Jul", day="22", volume="22", number="7", pages="e14865", keywords="video gaming", keywords="internet", keywords="information technology", keywords="schizophrenia", abstract="Background: Information technology and video gaming have potential advantages in the treatment of schizophrenia. However, information regarding the habits and attitudes related to internet use and video gaming in people with schizophrenia is limited. Objective: The aim of this study was to explore the habits and attitudes regarding video gaming and information technology usage and their associated factors in people with schizophrenia in Hong Kong. Methods: In this cross-sectional survey, service users with schizophrenia were recruited from 6 halfway hostels and 7 integrated centers for mental wellness in Hong Kong. A 79-item self-report questionnaire was utilized to explore the habits of internet use and video gaming in these people with schizophrenia. The attitude toward video gaming was assessed using the Gaming Attitudes, Motivations, and Experiences Scales. Of the 148 individuals in a convenience sample who were invited to participate in this study, 110 willingly participated (a response rate of 74.3\%). The data were analyzed using descriptive statistics, a two-tailed independent t test, Pearson correlation, and principal analysis with 3 methods of rotation (varimax, equimax, and promax). Results: Most participants (100/110, 90.9\%) had access to the internet and half of them (54/110, 49.1\%) used the internet daily mostly to watch videos (66/110, 60.0\%) or read news or books, etc (42/110, 38.2\%). One-third of the participants (36/110, 32.7\%) used the internet to play web-based games, and most of them (88/110, 80.0\%) had played a video game in the past year. The most favorable gaming platforms were cellular phones (43/88, 49\%) followed by computers (19/88, 22\%) and arcade cabinets (6/88, 7\%). The most favorable game genre was action games (34/145, 23.4\%). Those who had a bachelor's degree or higher scored lower in social interaction than those with a lower education level (P=.03). Those who played video games daily scored higher in the category of story than those who did not play daily (t86=2.03, P=.05). The most popular gaming category was autonomy and the least popular categories were violent catharsis and violent reward. Two motives, ``social playing'' and ``evasive playing,'' were formed to describe the characteristics of playing video games. Conclusions: Our data showed a high internet utilization rate among people with schizophrenia in Hong Kong. Only a few of them used the internet to search for health-related information. Our study also exemplified the unique habits of gaming among the participants. Health care professionals could utilize video games to engage people with schizophrenia and promote coping with stress and provide social skills training to such people with schizophrenia. Identification of the gaming attitudes can contribute to the development of serious games for the schizophrenic population. Further investigation is vital for the promotion of mental health through web-based platforms. ", doi="10.2196/14865", url="http://www.jmir.org/2020/7/e14865/", url="http://www.ncbi.nlm.nih.gov/pubmed/32459646" } @Article{info:doi/10.2196/15878, author="Robinson, Heather and Appelbe, Duncan and Dodd, Susanna and Flowers, Susan and Johnson, Sonia and Jones, H. Steven and Mateus, C{\'e}u and Mezes, Barbara and Murray, Elizabeth and Rainford, Naomi and Rosala-Hallas, Anna and Walker, Andrew and Williamson, Paula and Lobban, Fiona", title="Methodological Challenges in Web-Based Trials: Update and Insights From the Relatives Education and Coping Toolkit Trial", journal="JMIR Ment Health", year="2020", month="Jul", day="17", volume="7", number="7", pages="e15878", keywords="randomized controlled trial", keywords="research design", keywords="methods", keywords="internet", keywords="web", keywords="mental health", keywords="relatives", keywords="carers", abstract="International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2017-016965 ", doi="10.2196/15878", url="https://mental.jmir.org/2020/7/e15878", url="http://www.ncbi.nlm.nih.gov/pubmed/32497018" } @Article{info:doi/10.2196/16730, author="Arnold, Chelsea and Williams, Anne and Thomas, Neil", title="Engaging With a Web-Based Psychosocial Intervention for Psychosis: Qualitative Study of User Experiences", journal="JMIR Ment Health", year="2020", month="Jun", day="19", volume="7", number="6", pages="e16730", keywords="psychosis", keywords="engagement", keywords="qualitative research", keywords="eHealth", keywords="internet intervention", keywords="mobile phone", abstract="Background: Web-based interventions are increasingly being used for individuals with serious mental illness, including psychosis, and preliminary evidence suggests clinical benefits. To achieve such benefits, individuals must have some level of engagement with the intervention. Currently, little is known about what influences engagement with web-based interventions for individuals with psychotic disorders. Objective: This study aimed to explore users' perspectives on what influenced engagement with a web-based intervention for psychosis. Methods: A qualitative design was employed using semistructured telephone interviews. Participants were 17 adults with psychosis who had participated in a trial examining engagement with a self-guided, web-based intervention promoting personal recovery and self-management of mental health. Results: We identified 2 overarching themes: challenges to using the website and factors supporting persistence. Both of the main themes included several subthemes related to both user-related factors (eg, mental health, personal circumstances, approach to using the website) and users' experience of the intervention (eg, having experienced similar content previously or finding the material confronting). Conclusions: Individuals with psychosis experienced several challenges to ongoing engagement with a web-based intervention. Adjunctive emails present an important design feature to maintain interest and motivation to engage with the intervention. However, fluctuations in mental health and psychosocial difficulties are a significant challenge. Design and implementation considerations include flexible interventions with tailoring opportunities to accommodate changeable circumstances and individual preferences. ", doi="10.2196/16730", url="https://mental.jmir.org/2020/6/e16730", url="http://www.ncbi.nlm.nih.gov/pubmed/32558659" } @Article{info:doi/10.2196/17098, author="Pot-Kolder, Roos and Veling, Wim and Geraets, Chris and Lokkerbol, Joran and Smit, Filip and Jongeneel, Alyssa and Ising, Helga and van der Gaag, Mark", title="Cost-Effectiveness of Virtual Reality Cognitive Behavioral Therapy for Psychosis: Health-Economic Evaluation Within a Randomized Controlled Trial", journal="J Med Internet Res", year="2020", month="May", day="5", volume="22", number="5", pages="e17098", keywords="psychosis", keywords="virtual reality", keywords="cognitive behavioral therapy", keywords="cost-effectiveness", abstract="Background: Evidence was found for the effectiveness of virtual reality-based cognitive behavioral therapy (VR-CBT) for treating paranoia in psychosis, but health-economic evaluations are lacking. Objective: This study aimed to determine the short-term cost-effectiveness of VR-CBT. Methods: The health-economic evaluation was embedded in a randomized controlled trial evaluating VR-CBT in 116 patients with a psychotic disorder suffering from paranoid ideation. The control group (n=58) received treatment as usual (TAU) for psychotic disorders in accordance with the clinical guidelines. The experimental group (n=58) received TAU complemented with add-on VR-CBT to reduce paranoid ideation and social avoidance. Data were collected at baseline and at 3 and 6 months postbaseline. Treatment response was defined as a pre-post improvement of symptoms of at least 20\% in social participation measures. Change in quality-adjusted life years (QALYs) was estimated by using Sanderson et al's conversion factor to map a change in the standardized mean difference of Green's Paranoid Thoughts Scale score on a corresponding change in utility. The incremental cost-effectiveness ratios were calculated using 5000 bootstraps of seemingly unrelated regression equations of costs and effects. The cost-effectiveness acceptability curves were graphed for the costs per treatment responder gained and per QALY gained. Results: The average mean incremental costs for a treatment responder on social participation ranged between {\texteuro}8079 and {\texteuro}19,525, with 90.74\%-99.74\% showing improvement. The average incremental cost per QALY was {\texteuro}48,868 over the 6 months of follow-up, with 99.98\% showing improved QALYs. Sensitivity analyses show costs to be lower when relevant baseline differences were included in the analysis. Average costs per treatment responder now ranged between {\texteuro}6800 and {\texteuro}16,597, while the average cost per QALY gained was {\texteuro}42,030. Conclusions: This study demonstrates that offering VR-CBT to patients with paranoid delusions is an economically viable approach toward improving patients' health in a cost-effective manner. Long-term effects need further research. Trial Registration: International Standard Randomised Controlled Trial Number (ISRCTN) 12929657; http://www.isrctn.com/ISRCTN12929657 ", doi="10.2196/17098", url="https://www.jmir.org/2020/5/e17098", url="http://www.ncbi.nlm.nih.gov/pubmed/32369036" } @Article{info:doi/10.2196/15521, author="Gremyr, Andreas and Andersson G{\"a}re, Boel and Greenhalgh, Trisha and Malm, Ulf and Thor, Johan and Andersson, Ann-Christine", title="Using Complexity Assessment to Inform the Development and Deployment of a Digital Dashboard for Schizophrenia Care: Case Study", journal="J Med Internet Res", year="2020", month="Apr", day="23", volume="22", number="4", pages="e15521", keywords="health care", keywords="complexity", keywords="schizophrenia", keywords="coproduction", keywords="learning health systems", abstract="Background: Health care is becoming more complex. For an increasing number of individuals, interacting with health care means addressing more than just one illness or disorder, engaging in more than one treatment, and interacting with more than one care provider. Individuals with severe mental illnesses such as schizophrenia are disproportionately affected by this complexity. Characteristic symptoms can make it harder to establish and maintain relationships. Treatment failure is common even where there is access to effective treatments, increasing suicide risk. Knowledge of complex adaptive systems has been increasingly recognized as useful in understanding and developing health care. A complex adaptive system is a collection of interconnected agents with the freedom to act based on their own internalized rules, affecting each other. In a complex health care system, relevant feedback is crucial in enabling continuous learning and improvement on all levels. New technology has potential, but the failure rate of technology projects in health care is high, arguably due to complexity. The Nonadoption, Abandonment, and challenges to Scale-up, Spread, and Sustainability (NASSS) framework and complexity assessment tool (NASSS-CAT) have been developed specifically to help identify and manage complexity in technology-related development projects in health care. Objective: This study aimed to use a pilot version of the NASSS-CAT instrument to inform the development and deployment of a point-of-care dashboard supporting schizophrenia care in west Sweden. Specifically, we report on the complexity profile of the project, stakeholders' experiences with using NASSS-CAT, and practical implications. Methods: We used complexity assessment to structure data collection and feedback sessions with stakeholders, thereby informing an emergent approach to the development and deployment of the point-of-care dashboard. We also performed a thematic analysis, drawing on observations and documents related to stakeholders' use of the NASSS-CAT to describe their views on its usefulness. Results: Application of the NASSS framework revealed different types of complexity across multiple domains, including the condition, technology, value proposition, organizational tasks and pathways, and wider system. Stakeholders perceived the NASSS-CAT tool as useful in gaining perspective and new insights, covering areas that might otherwise have been neglected. Practical implications derived from feedback sessions with managers and developers are described. Conclusions: This case study shows how stakeholders can identify and plan to address complexities during the introduction of a technological solution. Our findings suggest that NASSS-CAT can bring participants a greater understanding of complexities in digitalization projects in general. ", doi="10.2196/15521", url="http://www.jmir.org/2020/4/e15521/", url="http://www.ncbi.nlm.nih.gov/pubmed/32324143" } @Article{info:doi/10.2196/16470, author="Li, Ang and Jiao, Dongdong and Liu, Xiaoqian and Zhu, Tingshao", title="A Comparison of the Psycholinguistic Styles of Schizophrenia-Related Stigma and Depression-Related Stigma on Social Media: Content Analysis", journal="J Med Internet Res", year="2020", month="Apr", day="21", volume="22", number="4", pages="e16470", keywords="stigma", keywords="schizophrenia", keywords="depression", keywords="psycholinguistic analysis", keywords="social media", abstract="Background: Stigma related to schizophrenia is considered to be the primary focus of antistigma campaigns. Accurate and efficient detection of stigma toward schizophrenia in mass media is essential for the development of targeted antistigma interventions at the population level. Objective: The purpose of this study was to examine the psycholinguistic characteristics of schizophrenia-related stigma on social media (ie, Sina Weibo, a Chinese microblogging website), and then to explore whether schizophrenia-related stigma can be distinguished from stigma toward other mental illnesses (ie, depression-related stigma) in terms of psycholinguistic style. Methods: A total of 19,224 schizophrenia- and 15,879 depression-related Weibo posts were collected and analyzed. First, a human-based content analysis was performed on collected posts to determine whether they reflected stigma or not. Second, by using Linguistic Inquiry and Word Count software (Simplified Chinese version), a number of psycholinguistic features were automatically extracted from each post. Third, based on selected key features, four groups of classification models were established for different purposes: (a) differentiating schizophrenia-related stigma from nonstigma, (b) differentiating a certain subcategory of schizophrenia-related stigma from other subcategories, (c) differentiating schizophrenia-related stigma from depression-related stigma, and (d) differentiating a certain subcategory of schizophrenia-related stigma from the corresponding subcategory of depression-related stigma. Results: In total, 26.22\% of schizophrenia-related posts were labeled as stigmatizing posts. The proportion of posts indicating depression-related stigma was significantly lower than that indicating schizophrenia-related stigma ($\chi$21=2484.64, P<.001). The classification performance of the models in the four groups ranged from .71 to .92 (F measure). Conclusions: The findings of this study have implications for the detection and reduction of stigma toward schizophrenia on social media. ", doi="10.2196/16470", url="http://www.jmir.org/2020/4/e16470/", url="http://www.ncbi.nlm.nih.gov/pubmed/32314969" } @Article{info:doi/10.2196/14278, author="Hu, Ya-Han and Chen, Kuanchin and Chang, I-Chiu and Shen, Cheng-Che", title="Critical Predictors for the Early Detection of Conversion From Unipolar Major Depressive Disorder to Bipolar Disorder: Nationwide Population-Based Retrospective Cohort Study", journal="JMIR Med Inform", year="2020", month="Apr", day="3", volume="8", number="4", pages="e14278", keywords="major depressive disorder", keywords="bipolar disorder", keywords="National Health Insurance Database", keywords="data mining", keywords="classification and regression tree", abstract="Background: Unipolar major depressive disorder (MDD) and bipolar disorder are two major mood disorders. The two disorders have different treatment strategies and prognoses. However, bipolar disorder may begin with depression and could be diagnosed as MDD in the initial stage, which may later contribute to treatment failure. Previous studies indicated that a high proportion of patients diagnosed with MDD will develop bipolar disorder over time. This kind of hidden bipolar disorder may contribute to the treatment resistance observed in patients with MDD. Objective: In this population-based study, our aim was to investigate the rate and risk factors of a diagnostic change from unipolar MDD to bipolar disorder during a 10-year follow-up. Furthermore, a risk stratification model was developed for MDD-to-bipolar disorder conversion. Methods: We conducted a retrospective cohort study involving patients who were newly diagnosed with MDD between January 1, 2000, and December 31, 2004, by using the Taiwan National Health Insurance Research Database. All patients with depression were observed until (1) diagnosis of bipolar disorder by a psychiatrist, (2) death, or (3) December 31, 2013. All patients with depression were divided into the following two groups, according to whether bipolar disorder was diagnosed during the follow-up period: converted group and nonconverted group. Six groups of variables within the first 6 months of enrollment, including personal characteristics, physical comorbidities, psychiatric comorbidities, health care usage behaviors, disorder severity, and psychotropic use, were extracted and were included in a classi?cation and regression tree (CART) analysis to generate a risk stratification model for MDD-to-bipolar disorder conversion. Results: Our study enrolled 2820 patients with MDD. During the follow-up period, 536 patients were diagnosed with bipolar disorder (conversion rate=19.0\%). The CART method identified five variables (kinds of antipsychotics used within the first 6 months of enrollment, kinds of antidepressants used within the first 6 months of enrollment, total psychiatric outpatient visits, kinds of benzodiazepines used within one visit, and use of mood stabilizers) as significant predictors of the risk of bipolar disorder conversion. This risk CART was able to stratify patients into high-, medium-, and low-risk groups with regard to bipolar disorder conversion. In the high-risk group, 61.5\%-100\% of patients with depression eventually developed bipolar disorder. On the other hand, in the low-risk group, only 6.4\%-14.3\% of patients with depression developed bipolar disorder. Conclusions: The CART method identified five variables as significant predictors of bipolar disorder conversion. In a simple two- to four-step process, these variables permit the identification of patients with low, intermediate, or high risk of bipolar disorder conversion. The developed model can be applied to routine clinical practice for the early diagnosis of bipolar disorder. ", doi="10.2196/14278", url="https://medinform.jmir.org/2020/4/e14278", url="http://www.ncbi.nlm.nih.gov/pubmed/32242821" } @Article{info:doi/10.2196/16993, author="D'Arcey, Jessica and Collaton, Joanna and Kozloff, Nicole and Voineskos, N. Aristotle and Kidd, A. Sean and Foussias, George", title="The Use of Text Messaging to Improve Clinical Engagement for Individuals With Psychosis: Systematic Review", journal="JMIR Ment Health", year="2020", month="Apr", day="2", volume="7", number="4", pages="e16993", keywords="SMS", keywords="text messaging", keywords="psychosis", keywords="schizophrenia", keywords="bipolar disorder", keywords="engagement", keywords="medication adherence", keywords="attendance", keywords="patient appointments", abstract="Background: Individuals experiencing psychosis are at a disproportionate risk for premature disengagement from clinical treatment. Barriers to clinical engagement typically result from funding constraints causing limited access to and flexibility in services. Digital strategies, such as SMS text messaging, offer a low-cost alternative to potentially improve engagement. However, little is known about the efficacy of SMS text messaging in psychosis. Objective: This review aimed to address this gap, providing insights into the relationship between SMS text messaging and clinical engagement in the treatment of psychosis. Methods: Studies examining SMS text messaging as an engagement strategy in the treatment of psychosis were reviewed. Included studies were published from the year 2000 onward in the English language, with no methodological restrictions, and were identified using 3 core databases and gray literature sources. Results: Of the 233 studies extracted, 15 were eligible for inclusion. Most studies demonstrated the positive effects of SMS text messaging on dimensions of engagement such as medication adherence, clinic attendance, and therapeutic alliance. Studies examining the feasibility of SMS text messaging interventions found that they are safe, easy to use, and positively received. Conclusions: Overall, SMS text messaging is a low-cost, practical method of improving engagement in the treatment of psychosis, although efficacy may vary by symptomology and personal characteristics. Cost-effectiveness and safety considerations were not adequately examined in the studies included. Future studies should consider personalizing SMS text messaging interventions and include cost and safety analyses to appraise readiness for implementation. ", doi="10.2196/16993", url="https://mental.jmir.org/2020/4/e16993", url="http://www.ncbi.nlm.nih.gov/pubmed/32238334" } @Article{info:doi/10.2196/15028, author="Busk, Jonas and Faurholt-Jepsen, Maria and Frost, Mads and Bardram, E. Jakob and Vedel Kessing, Lars and Winther, Ole", title="Forecasting Mood in Bipolar Disorder From Smartphone Self-assessments: Hierarchical Bayesian Approach", journal="JMIR Mhealth Uhealth", year="2020", month="Apr", day="1", volume="8", number="4", pages="e15028", keywords="bipolar disorder", keywords="mood", keywords="early medical intervention", keywords="digital phenotyping", keywords="machine learning", keywords="forecasting", keywords="Bayesian analysis", abstract="Background: Bipolar disorder is a prevalent mental health condition that is imposing significant burden on society. Accurate forecasting of symptom scores can be used to improve disease monitoring, enable early intervention, and eventually help prevent costly hospitalizations. Although several studies have examined the use of smartphone data to detect mood, only few studies deal with forecasting mood for one or more days. Objective: This study aimed to examine the feasibility of forecasting daily subjective mood scores based on daily self-assessments collected from patients with bipolar disorder via a smartphone-based system in a randomized clinical trial. Methods: We applied hierarchical Bayesian regression models, a multi-task learning method, to account for individual differences and forecast mood for up to seven days based on 15,975 smartphone self-assessments from 84 patients with bipolar disorder participating in a randomized clinical trial. We reported the results of two time-series cross-validation 1-day forecast experiments corresponding to two different real-world scenarios and compared the outcomes with commonly used baseline methods. We then applied the best model to evaluate a 7-day forecast. Results: The best performing model used a history of 4 days of self-assessment to predict future mood scores with historical mood being the most important predictor variable. The proposed hierarchical Bayesian regression model outperformed pooled and separate models in a 1-day forecast time-series cross-validation experiment and achieved the predicted metrics, R2=0.51 and root mean squared error of 0.32, for mood scores on a scale of ?3 to 3. When increasing the forecast horizon, forecast errors also increased and the forecast regressed toward the mean of data distribution. Conclusions: Our proposed method can forecast mood for several days with low error compared with common baseline methods. The applicability of a mood forecast in the clinical treatment of bipolar disorder has also been discussed. ", doi="10.2196/15028", url="https://mhealth.jmir.org/2020/4/e15028", url="http://www.ncbi.nlm.nih.gov/pubmed/32234702" } @Article{info:doi/10.2196/15634, author="Allan, Stephanie and Mcleod, Hamish and Bradstreet, Simon and Beedie, Sara and Moir, Bethany and Gleeson, John and Farhall, John and Morton, Emma and Gumley, Andrew", title="Understanding Implementation of a Digital Self-Monitoring Intervention for Relapse Prevention in Psychosis: Protocol for a Mixed Method Process Evaluation", journal="JMIR Res Protoc", year="2019", month="Dec", day="10", volume="8", number="12", pages="e15634", keywords="telemedicine", keywords="schizophrenia", keywords="implementation science", abstract="Background: Relapse is common in people who experience psychosis and is associated with many negative consequences, both societal and personal. People who relapse often exhibit changes (early warning signs [EWS]) in the period before relapse. Successful identification of EWS offers an opportunity for relapse prevention. However, several known barriers impede the use of EWS monitoring approaches. Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) is a complex digital intervention that uses a mobile app to enhance the detection and management of self-reported changes in well-being. This is currently being tested in a pilot cluster randomized controlled trial. As digital interventions have not been widely used in relapse prevention, little is known about their implementation. Process evaluation studies run in parallel to clinical trials can provide valuable data on intervention feasibility. Objective: This study aims to transparently describe the protocol for the process evaluation element of the EMPOWER trial. We will focus on the development of a process evaluation framework sensitive to the worldview of service users, mental health staff, and carers; the aims of the process evaluation itself; the proposed studies to address these aims; and a plan for integration of results from separate process evaluation studies into one overall report. Methods: The overall process evaluation will utilize mixed methods across 6 substudies. Among them, 4 will use qualitative methodologies, 1 will use a mixed methods approach, and 1 will use quantitative methodologies. Results: The results of all studies will be triangulated into an overall analysis and interpretation of key implementation lessons. EMPOWER was funded in 2016, recruitment finished in January 2018. Data analysis is currently under way and the first results are expected to be submitted for publication in December 2019. Conclusions: The findings from this study will help identify implementation facilitators and barriers to EMPOWER. These insights will inform both upscaling decisions and optimization of a definitive trial. Trial Registration: ISRCTN Registry ISRCTN99559262; http://www.isrctn.com/ISRCTN99559262 International Registered Report Identifier (IRRID): DERR1-10.2196/15634 ", doi="10.2196/15634", url="https://www.researchprotocols.org/2019/12/e15634", url="http://www.ncbi.nlm.nih.gov/pubmed/31821154" } @Article{info:doi/10.2196/16393, author="Camacho, Erica and Levin, Leonard and Torous, John", title="Smartphone Apps to Support Coordinated Specialty Care for Prodromal and Early Course Schizophrenia Disorders: Systematic Review", journal="J Med Internet Res", year="2019", month="Nov", day="12", volume="21", number="11", pages="e16393", keywords="smartphones", keywords="mobile phones", keywords="app", keywords="schizophrenia", abstract="Background: Demand for mental health services, especially for clinical high-risk and early psychosis, has increased, creating a need for new solutions to increase access to and quality of care. Smartphones and mobile technology are potential tools to support coordinated specialty care for early psychosis, given their potential to augment the six core roles of care: case management and team leadership, recovery-oriented psychotherapy, medication management, support for employment and education, coordination with primary care services, and family education and support. However, the services smartphones are actually offering specifically for coordinated specialty care and the level of evidence are unknown. Objective: This study aimed to review the published literature on smartphone technology to enhance care for patients with prodromal and early course psychosis and schizophrenia and to analyze studies by type, aligned with coordinated specialty care domains. Methods: A systematic literature search was conducted on August 16 and 17, 2019, using the PubMed, EMBASE, Web of Sciences, and PsycINFO electronic databases. The eligible studies were reviewed and screened based on inclusion and exclusion criteria. Results: The search uncovered 388 unique results, of which 32 articles met the initial inclusion criteria; 21 eligible studies on 16 unique app platforms were identified. Feasibility studies showed a high user engagement and interest among patients, monitoring studies demonstrated a correlation between app assessments and clinical outcomes, and intervention studies indicated that these apps have the potential to advance care. Eighteen studies reported on app use for the case management roles of coordinated specialty care. No app studies focused on employment and education, coordination with primary care services, and family education and support. Conclusions: Although the published literature on smartphone apps for prodromal and first-episode psychosis is small, it is growing exponentially and holds promise to augment both monitoring and interventions. Although the research results and protocols for app studies are not well aligned with all coordinated specialty care roles today, high rates of adoption and feasibility suggest the potential for future efforts. These results will be used to develop coordinated specialty care--specific app evaluation scales and toolkits. ", doi="10.2196/16393", url="http://www.jmir.org/2019/11/e16393/", url="http://www.ncbi.nlm.nih.gov/pubmed/31714250" } @Article{info:doi/10.2196/14366, author="Allan, Stephanie and Bradstreet, Simon and Mcleod, Hamish and Farhall, John and Lambrou, Maria and Gleeson, John and Clark, Andrea and and Gumley, Andrew", title="Developing a Hypothetical Implementation Framework of Expectations for Monitoring Early Signs of Psychosis Relapse Using a Mobile App: Qualitative Study", journal="J Med Internet Res", year="2019", month="Oct", day="24", volume="21", number="10", pages="e14366", keywords="psychosis", keywords="self-management", keywords="implementation science", abstract="Background: Relapse is a common experience for people diagnosed with psychosis, which is associated with increased service costs and profound personal and familial distress. EMPOWER (Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery) is a peer worker--supported digital intervention that aims to enable service users to self-monitor their mental health with the aim of encouraging self-management and the shared use of personal data to promote relapse prevention. Digital interventions have not been widely used in relapse prevention and, therefore, little is currently known about their likely implementation---both within trials and beyond. Objective: Seeking the perspectives of all relevant stakeholder groups is recommended in developing theories about implementation because this can reveal important group differences in understandings and assumptions about whether and for whom the intervention is expected to work. However, the majority of intervention implementation research has been retrospective. This study aimed to discover and theoretically frame implementation expectations in advance of testing and synthesize these data into a framework. Methods: To develop a hypothetical implementation framework, 149 mental health professionals, carers, and people diagnosed with psychosis participated in 25 focus groups in both Australia and the United Kingdom. An interview schedule informed by the normalization process theory was used to explore stakeholders' expectations about the implementation of the EMPOWER intervention. Data were analyzed using thematic analysis and then theoretically framed using the Medical Research Council guidelines for understanding the implementation of complex interventions. Results: All groups expected that EMPOWER could be successfully implemented if the intervention generated data that were meaningful to mental health staff, carers, and service users within their unique roles. However, there were key differences between staff, carers, and service users about what facilitators and barriers that stakeholders believe exist for intervention implementation in both the cluster randomized controlled trial stage and beyond. For example, service user expectations mostly clustered around subjective user experiences, whereas staff and carers spoke more about the impact upon staff interactions with service users. Conclusions: A hypothetical implementation framework synthesized from stakeholder implementation expectations provides an opportunity to compare actual implementation data gathered during an ongoing clinical trial, giving valuable insights into the accuracy of these stakeholders' previous expectations. This is among the first studies to assess and record implementation expectations for a newly developed digital intervention for psychosis in advance of testing in a clinical trial. Trial Registration: ISRCTN Registry ISRCTN99559262; http://www.isrctn.com/ISRCTN99559262 ", doi="10.2196/14366", url="https://www.jmir.org/2019/10/e14366", url="http://www.ncbi.nlm.nih.gov/pubmed/31651400" } @Article{info:doi/10.2196/13073, author="Laine, Anna and V{\"a}lim{\"a}ki, Maritta and Pekurinen, Virve and L{\"o}yttyniemi, Eliisa and Marttunen, Mauri and Anttila, Minna", title="Feasibility, Acceptability, and Preliminary Impacts of Web-Based Patient Education on Patients With Schizophrenia Spectrum Disorder: Quasi-Experimental Cluster Study", journal="J Med Internet Res", year="2019", month="Oct", day="17", volume="21", number="10", pages="e13073", keywords="mental health", keywords="patient education", keywords="schizophrenia", keywords="feasibility study", keywords="internet", keywords="information system", abstract="Background: Web-based interventions are promising tools for increasing the understanding of illness and treatment among patients with serious mental disorders. Objective: This study aimed to test the feasibility and acceptability of a Web-based patient education intervention using a quasi-experimental cluster design to report feedback on patient education sessions and the website used and to report preliminary evidence of the intervention's impact on patients with schizophrenia spectrum disorder. Methods: A single-blind, parallel, quasi-experimental cluster study over a 6-month period comparing Web-based education (n=33) with a nonequivalent control group (treatment as usual, n=24) for people with schizophrenia spectrum disorder was conducted. Participants (N=57) were recruited from one psychiatric hospital (6 wards). Feasibility was assessed by participants' commitment (refusal rate, dropout rate) to the study. Acceptability was assessed as participants' commitment to the intervention. Patient education sessions and website feedback were assessed by the patients and health care professionals. The preliminary impact of the sessions on patients' self-efficacy, self-esteem, illness cognition, and knowledge level was measured at baseline and follow-ups (8 weeks, 6 months) with self-rated questionnaires. Results: The refusal rate among patients was high with no statistically significant difference (69\% [74/107] in the intervention group, 76\% [76/100] in the control group; P=.21). The same result was found for the dropout rates (48\% [16/33] vs 58\% [14/24]; P=.46). The acceptability of the intervention was good; 31 participants out of 33 (94\%) completed all five sessions. Feedback on the intervention was mainly positive; three out of four subscales of session were rated above the midpoint of 4.0. Feedback on the website was also positive, with a grade of good for content (69\%, 20/29 patients; 75\%, 21/28 professionals), layout (62\%, 18/29 patients; 61\%, 17/28 professionals), and usability (62\%, 18/29 patients; and 68\%, 19/28 professionals). The patients using the intervention had significantly higher scores 6 months after the sessions in self-efficacy (baseline mean 26.12, SD 5.64 vs 6-month mean 29.24, SD 6.05; P=.003) and regarding knowledge level about schizophrenia (mean 11.39, SD 4.65 vs 6-month mean 15.06, SD 5.26; P=.002), and lower scores in the subscale of helplessness in illness cognition (mean 2.26, SD 0.96 vs 6-month mean 1.85, SD 0.59; P=.03). Differences from the control group were not significant. No differences were found in patients' self-esteem or other subscales in illness cognition. Conclusions: The patients were reluctant to participate in the study and tended to drop out before the follow-ups. Once they had participated, their acceptance of the intervention was high. A more effective recruitment strategy and monitoring method will be needed in future studies. To assess the impact of the intervention, a more rigorous study design with an adequately powered sample size will be used in cooperation with outpatient mental health services. ", doi="10.2196/13073", url="http://www.jmir.org/2019/10/e13073/", url="http://www.ncbi.nlm.nih.gov/pubmed/31625952" } @Article{info:doi/10.2196/14581, author="Reilly, Thomas and Mechelli, Andrea and McGuire, Philip and Fusar-Poli, Paolo and Uhlhaas, J. Peter", title="E-Clinical High Risk for Psychosis: Viewpoint on Potential of Digital Innovations for Preventive Psychiatry", journal="JMIR Ment Health", year="2019", month="Oct", day="3", volume="6", number="10", pages="e14581", keywords="psychotic disorders", keywords="schizophrenia", keywords="prognosis", keywords="treatment", keywords="clinical high risk", keywords="digital", keywords="e-health", keywords="internet", keywords="smartphone", keywords="mobile phone", doi="10.2196/14581", url="https://mental.jmir.org/2019/10/e14581", url="http://www.ncbi.nlm.nih.gov/pubmed/31584006" } @Article{info:doi/10.2196/10876, author="Spencer, Lucy and Potterton, Rachel and Allen, Karina and Musiat, Peter and Schmidt, Ulrike", title="Internet-Based Interventions for Carers of Individuals With Psychiatric Disorders, Neurological Disorders, or Brain Injuries: Systematic Review", journal="J Med Internet Res", year="2019", month="Jul", day="09", volume="21", number="7", pages="e10876", keywords="internet", keywords="carers", keywords="mental health", keywords="technology", keywords="review", abstract="Background: Nonprofessional carers who provide support to an individual with a psychiatric or neurological disorder will often themselves experience symptoms of stress, anxiety, or low mood, and they perceive that they receive little support. Internet-based interventions have previously been found to be effective in the prevention and treatment of a range of mental health difficulties in carers. Objective: This review seeks to establish the status of internet-based interventions for informal (nonprofessional) carers of people with psychiatric or neurological disorders by investigating (1) the number and quality of studies evaluating the efficacy or effectiveness of internet-based carer interventions and (2) the impact that such interventions have on carer mental health, as well as (3) how internet-based interventions compare with other intervention types (eg, face-to-face treatment). Methods: A systematic literature search was conducted in January 2019 using the EMBASE (1974-present), Ovid MEDLINE (1946-present), PsychARTICLES, PsychINFO (1806-present), and Global Health (1973-present) databases, via the Ovid Technologies database. Search terms included carer, caregiver, online, technology, internet-based, internet, interactive, intervention, and evaluation. Studies selected for inclusion in this review met the following predetermined criteria: (1) delivering an intervention aimed primarily at informal carers, (2) carers supporting individuals with psychiatric disorders, stroke, dementia, or brain injury, (3) the intervention delivered to the carers was primarily internet based, (4) the study reported a pre- and postquantitative measure of carer depression, anxiety, stress, burden, or quality of life, (5) appeared in a peer-reviewed journal, and (6) was accessible in English. Results: A total of 46 studies were identified for inclusion through the detailed search strategy. The search was conducted, and data were extracted independently by 2 researchers. The majority of studies reported that 1 or more measures relating to carer mental health improved following receipt of a relevant intervention, with interventions for carers of people with traumatic brain injury showing a consistent link with improved outcomes. Conclusions: Studies investigating internet-based interventions for carers of individuals with diverse psychiatric or neurological difficulties show some evidence in support of the effectiveness of these interventions. In addition, such interventions are acceptable to carers. Available evidence is of varying quality, and more high-quality trials are needed. Further research should also establish how specific intervention components, such as structure or interactivity, contribute to their overall efficacy with regard to carer mental health. ", doi="10.2196/10876", url="https://www.jmir.org/2019/7/e10876/", url="http://www.ncbi.nlm.nih.gov/pubmed/31290399" } @Article{info:doi/10.2196/13957, author="Bjornestad, Jone and Hegelstad, Velden Wenche Ten and Berg, Henrik and Davidson, Larry and Joa, Inge and Johannessen, Olav Jan and Melle, Ingrid and Stain, J. Helen and Pallesen, St{\aa}le", title="Social Media and Social Functioning in Psychosis: A Systematic Review", journal="J Med Internet Res", year="2019", month="Jun", day="28", volume="21", number="6", pages="e13957", keywords="psychosis", keywords="schizophrenia", keywords="social media", keywords="social functioning", keywords="measures", keywords="assessment", keywords="systematic review", abstract="Background: Individuals with psychosis are heavy consumers of social media. It is unknown to what degree measures of social functioning include measures of online social activity. Objective: To examine the inclusion of social media activity in measures of social functioning in psychosis and ultrahigh risk (UHR) for psychosis. Methods: Two independent authors conducted a search using the following electronic databases: Epistemonikos, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, MEDLINE, Embase, and PsycINFO. The included articles were required to meet all of the following criteria: (1) an empirical study published in the English language in a peer-reviewed journal; (2) the study included a measure of objective or subjective offline (ie, non-Web-mediated contact) and/or online social functioning (ie, Web-mediated contact); (3) the social functioning measure had to be used in samples meeting criteria (ie, Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases) for a psychotic disorder or UHR for psychosis; and (4) the study was published between January 2004 and February 2019. Facebook was launched as the first large-scale social media platform in 2004 and, therefore, it is highly improbable that studies conducted prior to 2004 would have included measures of social media activity. Results: The electronic search resulted in 11,844 distinct articles. Full-text evaluation was conducted on 719 articles, of which 597 articles met inclusion criteria. A total of 58 social functioning measures were identified. With some exceptions, reports on reliability and validity were scarce, and only one measure integrated social media social activity. Conclusions: The ecological validity of social functioning measures is challenged by the lack of assessment of social media activity, as it fails to reflect an important aspect of the current social reality of persons with psychosis. Measures should be revised to include social media activity and thus avoid the clinical consequences of inadequate assessment of social functioning. Trial Registration: International Prospective Register of Systematic Reviews (PROSPERO) CRD42017058514; http://www.crd.york.ac.uk/PROSPERO/display\_record.php?ID=CRD42017058514 ", doi="10.2196/13957", url="http://www.jmir.org/2019/6/e13957/", url="http://www.ncbi.nlm.nih.gov/pubmed/31254338" } @Article{info:doi/10.2196/14110, author="Alvarez-Mon, Angel Miguel and Llavero-Valero, Mar{\'i}a and S{\'a}nchez-Bayona, Rodrigo and Pereira-Sanchez, Victor and Vallejo-Valdivielso, Maria and Monserrat, Jorge and Lahera, Guillermo and Asunsolo del Barco, Angel and Alvarez-Mon, Melchor", title="Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter", journal="J Med Internet Res", year="2019", month="May", day="28", volume="21", number="5", pages="e14110", keywords="social stigma", keywords="social media", keywords="psychosis", keywords="breast cancer", keywords="HIV", keywords="dementia", keywords="public opinion", keywords="diabetes", abstract="Background: Twitter is an?indicator of real-world?performance, thus, is an appropriate arena to assess the social consideration and attitudes toward psychosis. Objective: The aim of this study was to perform a mixed-methods study of the content and key metrics of tweets referring to psychosis in comparison with tweets referring to control diseases (breast cancer, diabetes, Alzheimer, and human immunodeficiency virus). Methods: Each tweet's content was rated as nonmedical (NM: testimonies, health care products, solidarity or awareness and misuse) or medical (M: included a reference to the illness's diagnosis, treatment, prognosis, or prevention). NM tweets were classified as positive or pejorative. We assessed the appropriateness of the medical content. The number of retweets generated and the potential reach and impact of the hashtags analyzed was also investigated. Results: We analyzed a total of 15,443 tweets: 8055 classified as NM and 7287 as M. Psychosis-related tweets (PRT) had a significantly higher frequency of misuse 33.3\% (212/636) vs 1.15\% (853/7419; P<.001) and pejorative content 36.2\% (231/636) vs 11.33\% (840/7419; P<.001). The medical content of the PRT showed the highest scientific appropriateness 100\% (391/391) vs 93.66\% (6030/6439; P<.001) and had a higher frequency of content about disease prevention. The potential reach and impact of the tweets related to psychosis were low, but they had a high retweet-to-tweet ratio. Conclusions: We show a reduced number and a different pattern of contents in tweets about psychosis compared with control diseases. PRT showed a predominance of nonmedical content with increased frequencies of misuse and pejorative tone. However, the medical content of PRT showed high scientific appropriateness aimed toward prevention. ", doi="10.2196/14110", url="http://www.jmir.org/2019/5/e14110/", url="http://www.ncbi.nlm.nih.gov/pubmed/31140438" } @Article{info:doi/10.2196/13882, author="Smelror, Elle Runar and Bless, Johann Josef and Hugdahl, Kenneth and Agartz, Ingrid", title="Feasibility and Acceptability of Using a Mobile Phone App for Characterizing Auditory Verbal Hallucinations in Adolescents With Early-Onset Psychosis: Exploratory Study", journal="JMIR Form Res", year="2019", month="May", day="14", volume="3", number="2", pages="e13882", keywords="experience sampling method", keywords="ecological momentary assessment", keywords="schizophrenia", keywords="mHealth", keywords="health care technology", abstract="Background: Auditory verbal hallucinations (AVH) are the most frequent symptom in early-onset psychosis (EOP) and a risk factor for increased suicide attempts in adolescents. Increased knowledge of AVH characteristics can lead to better prediction of risk and precision of diagnosis and help identify individuals with AVH who need care. As 98\% of Norwegian adolescents aged 12 to 16 years own a mobile phone, the use of mobile phone apps in symptom assessment and patient communication is a promising new tool. However, when introducing new technology to patients, their subjective experiences are crucial in identifying risks, further development, and potential integration into clinical care. Objective: The objective was to explore the feasibility and acceptability of a newly developed mobile phone app in adolescents with EOP by examining compliance with the app and user experiences. Indication of validity was explored by examining associations between AVH dimensions, which were correlated and analyzed. Methods: Three adolescents with EOP and active AVH were enrolled. Real-time AVH were logged on an iPod touch using the experience sampling method (ESM), for seven or more consecutive days. The app included five dimensions of AVH characteristics and was programmed with five daily notifications. Feasibility and acceptability were examined using the mean response rate of data sampling and by interviewing the participants. Validity was assessed by examining associations between the AVH dimensions using nonparametric correlation analysis and by visual inspection of temporal fluctuations of the AVH dimensions. Results: One participant was excluded from the statistical analyses but completed the interview and was included in the examination of acceptability. The sampling period of the two participants was mean 12 (SD 6) days with overall completed sampling rate of 74\% (SD 30\%), indicating adequate to high compliance with the procedure. The user experiences from the interviews clustered into four categories: (1) increased awareness, (2) personal privacy, (3) design and procedure, and (4) usefulness and clinical care. One participant experienced more commenting voices during the sampling period, and all three participants had concerns regarding personal privacy when using electronic devices in symptom assessment. The AVH dimensions of content, control, and influence showed moderate to strong significant correlations with all dimensions (P<.001). Days of data sampling showed weak to moderate correlations with localization (P<.001) and influence (P=.03). Visual inspection indicated that the app was able to capture fluctuations within and across days for all AVH dimensions. Conclusions: This study demonstrates the value of including patients' experiences in the development and pilot-testing of new technology. Based on the small sample size, the use of mobile phones with ESM seems feasible for patients with EOP, but the acceptability of using apps should be considered. Further investigation with larger samples is warranted before definitive conclusions are made. ", doi="10.2196/13882", url="http://formative.jmir.org/2019/2/e13882/", url="http://www.ncbi.nlm.nih.gov/pubmed/31094321" } @Article{info:doi/10.2196/12974, author="Soreni, Noam and Cameron, H. Duncan and Streiner, L. David and Rowa, Karen and McCabe, E. Randi", title="Seasonality Patterns of Internet Searches on Mental Health: Exploratory Infodemiology Study", journal="JMIR Ment Health", year="2019", month="Apr", day="24", volume="6", number="4", pages="e12974", keywords="anxiety", keywords="depression", keywords="OCD", keywords="schizophrenia", keywords="autism", keywords="suicide", keywords="seasonality", keywords="Google", keywords="internet", keywords="infodemiology", keywords="infoveillance", keywords="mental health", abstract="Background: The study of seasonal patterns of public interest in psychiatric disorders has important theoretical and practical implications for service planning and delivery. The recent explosion of internet searches suggests that mining search databases yields unique information on public interest in mental health disorders, which is a significantly more affordable approach than population health studies. Objective: This study aimed to investigate seasonal patterns of internet mental health queries in Ontario, Canada. Methods: Weekly data on health queries in Ontario from Google Trends were downloaded for a 5-year period (2012-2017) for the terms ``schizophrenia,'' ``autism,'' ``bipolar,'' ``depression,'' ``anxiety,'' ``OCD'' (obsessive-compulsive disorder), and ``suicide.'' Control terms were overall search results for the terms ``health'' and ``how.'' Time-series analyses using a continuous wavelet transform were performed to isolate seasonal components in the search volume for each term. Results: All mental health queries showed significant seasonal patterns with peak periodicity occurring over the winter months and troughs occurring during summer, except for ``suicide.'' The comparison term ``health'' also exhibited seasonal periodicity, while the term ``how'' did not, indicating that general information seeking may not follow a seasonal trend in the way that mental health information seeking does. Conclusions: Seasonal patterns of internet search volume in a wide range of mental health terms were observed, with the exception of ``suicide.'' Our study demonstrates that monitoring internet search trends is an affordable, instantaneous, and naturalistic method to sample public interest in large populations and inform health policy planners. ", doi="10.2196/12974", url="https://mental.jmir.org/2019/4/e12974/", url="http://www.ncbi.nlm.nih.gov/pubmed/31017582" } @Article{info:doi/10.2196/11824, author="Fern{\'a}ndez-Sotos, Patricia and Fern{\'a}ndez-Caballero, Antonio and Gonz{\'a}lez, Pascual and Aparicio, Isabel Ana and Mart{\'i}nez-Gras, Isabel and Torio, Iosune and Dompablo, M{\'o}nica and Garc{\'i}a-Fern{\'a}ndez, Lorena and Santos, Luis Jos{\'e} and Rodriguez-Jimenez, Roberto", title="Digital Technology for Internet Access by Patients With Early-Stage Schizophrenia in Spain: Multicenter Research Study", journal="J Med Internet Res", year="2019", month="Apr", day="05", volume="21", number="4", pages="e11824", keywords="information technology", keywords="computers", keywords="internet", keywords="schizophrenia", abstract="Background: Digital technology and social networks are part of everyday life in the current internet age, especially among young people. To date, few studies have been published worldwide on the pattern of use of digital technology devices and applications in patients with early-stage schizophrenia and even fewer comparing them with healthy participants (not using data from general population surveys) from the same demographic areas. In Spain, no such study has been carried out. Objective: The aim of this study was to analyze how patients with early-stage schizophrenia use internet and social networks compared with healthy participants matched by age and gender and also to examine which devices are utilized to access internet resources. Methods: A cross-sectional, multicentric study was carried out through a semistructured interview asking about the use of digital technology devices and internet. The sample comprised 90 patients and 90 healthy participants. The semistructured interview was conducted on 30 outpatients and 30 healthy subjects in each of the 3 different cities (Madrid, Alicante, and Cuenca). Student t test was used for continuous variables and chi-square test for categorical variables. In the case of ordinal variables, nonparametric Mann-Whitney U and Kruskal-Wallis H tests for independent samples were performed to compare groups. Results: The results indicated that a large proportion of patients with early-stage schizophrenia have access to different digital devices and use them frequently. In addition, both groups coincide in the order of preference and the purpose for which they use the devices. However, a lower frequency of use of most digital technology devices was detected in patients compared with healthy participants. In the case of some devices, this was due to the impossibility of access and not a lack of interest. Conclusions: To our knowledge, this is the first study to analyze patterns of internet access and use of digital technology devices and applications in Spanish patients with early-stage schizophrenia compared with healthy participants from the same demographic areas. The results on significant access and use of digital technology and internet shown in this cross-sectional study will allow enhanced and more efficient treatment strategies to be planned, utilizing digital technology devices, for patients with early-stage schizophrenia. ", doi="10.2196/11824", url="https://www.jmir.org/2019/4/e11824/", url="http://www.ncbi.nlm.nih.gov/pubmed/30950798" } @Article{info:doi/10.2196/11568, author="Eisner, Emily and Drake, James Richard and Berry, Natalie and Barrowclough, Christine and Emsley, Richard and Machin, Matthew and Bucci, Sandra", title="Development and Long-Term Acceptability of ExPRESS, a Mobile Phone App to Monitor Basic Symptoms and Early Signs of Psychosis Relapse", journal="JMIR Mhealth Uhealth", year="2019", month="Mar", day="29", volume="7", number="3", pages="e11568", keywords="schizophrenia", keywords="psychotic disorders", keywords="recurrence", keywords="telemedicine", keywords="mobile health", keywords="mHealth", keywords="eHealth", keywords="mental health", abstract="Background: Schizophrenia relapses are common, have profound, adverse consequences for patients and are costly to health services. Early signs interventions aim to use warning signs of deterioration to prevent full relapse. Such interventions show promise but could be further developed. This study addresses 2 developments: adding basic symptoms to checklists of conventional early signs and using a mobile phone app ExPRESS to aid early signs monitoring. Objective: This study aimed to (1) design a pool of self-report items assessing basic symptoms (Basic Symptoms Checklist, BSC); (2) develop and beta test a mobile phone app (ExPRESS) for monitoring early signs, basic symptoms, and psychotic symptoms; and (3) evaluate the long-term acceptability of ExPRESS via qualitative feedback from participants in a 6-month feasibility study. Methods: The BSC items and ExPRESS were developed and then adjusted following feedback from beta testers (n=5) with a schizophrenia diagnosis. Individuals (n=18) experiencing a relapse of schizophrenia within the past year were asked to use ExPRESS for 6 months to answer weekly questions about experiences of early signs, basic symptoms, and psychotic symptoms. At the end of follow-up, face-to-face qualitative interviews (n=16; 2 were uncontactable) explored experiences of using ExPRESS. The topic guide sought participants' views on the following a priori themes regarding app acceptability: item content, layout, and wording; app appearance; length and frequency of assessments; worries about app use; how app use fitted with participants' routines; and the app's extra features. Interview transcripts were analyzed using the framework method, which allows examination of both a priori and a posteriori themes, enabling unanticipated aspects of app use experiences to be explored. Results: Participants' mean age was 38 years (range 22-57 years). Responses to a priori topics indicated that long-term use of ExPRESS was acceptable; small changes for future versions of ExPRESS were suggested. A posteriori themes gave further insight into individuals' experiences of using ExPRESS. Some reported finding it more accessible than visits from a clinician, as assessments were more frequent, more anonymous, and did not require the individual to explain their feelings in their own words. Nevertheless, barriers to app use (eg, unfamiliarity with smartphones) were also reported. Despite ExPRESS containing no overtly therapeutic components, some participants found that answering the weekly questions prompted self-reflection, which had therapeutic value for them. Conclusions: This study suggests that apps are acceptable for long-term symptom monitoring by individuals with a schizophrenia diagnosis across a wide age range. If the potential benefits are understood, patients are generally willing and motivated to use a weekly symptom-monitoring app; most participants in this study were prepared to do so for more than 6 months. Trial Registration: ClinicalTrials.gov NCT03558529; https://clinicaltrials.gov/ct2/show/NCT03558529 (Archived by WebCite at http://www.webcitation.org/70qvtRmZY). ", doi="10.2196/11568", url="http://mhealth.jmir.org/2019/3/e11568/", url="http://www.ncbi.nlm.nih.gov/pubmed/30924789" } @Article{info:doi/10.2196/11483, author="Hswen, Yulin and Naslund, A. John and Brownstein, S. John and Hawkins, B. Jared", title="Monitoring Online Discussions About Suicide Among Twitter Users With Schizophrenia: Exploratory Study", journal="JMIR Ment Health", year="2018", month="Dec", day="13", volume="5", number="4", pages="e11483", keywords="schizophrenia", keywords="social media", keywords="suicide", keywords="Twitter", keywords="digital technology", keywords="mental health", abstract="Background: People with schizophrenia experience elevated risk of suicide. Mental health symptoms, including depression and anxiety, contribute to increased risk of suicide. Digital technology could support efforts to detect suicide risk and inform suicide prevention efforts. Objective: This exploratory study examined the feasibility of monitoring online discussions about suicide among Twitter users who self-identify as having schizophrenia. Methods: Posts containing the terms suicide or suicidal were collected from a sample of Twitter users who self-identify as having schizophrenia (N=203) and a random sample of control users (N=173) over a 200-day period. Frequency and timing of posts about suicide were compared between groups. The associations between posting about suicide and common mental health symptoms were examined. Results: Twitter users who self-identify as having schizophrenia posted more tweets about suicide (mean 7.10, SD 15.98) compared to control users (mean 1.89, SD 4.79; t374=-4.13, P<.001). Twitter users who self-identify as having schizophrenia showed greater odds of tweeting about suicide compared to control users (odds ratio 2.15, 95\% CI 1.42-3.28). Among all users, tweets about suicide were associated with tweets about depression (r=0.62, P<.001) and anxiety (r=0.45, P<.001). Conclusions: Twitter users who self-identify as having schizophrenia appear to commonly discuss suicide on social media, which is associated with greater discussion about other mental health symptoms. These findings should be interpreted cautiously, as it is not possible to determine whether online discussions about suicide correlate with suicide risk. However, these patterns of online discussion may be indicative of elevated risk of suicide observed in this patient group. There may be opportunities to leverage social media for supporting suicide prevention among individuals with schizophrenia. ", doi="10.2196/11483", url="http://mental.jmir.org/2018/4/e11483/", url="http://www.ncbi.nlm.nih.gov/pubmed/30545811" } @Article{info:doi/10.2196/11222, author="Hardy, Amy and Wojdecka, Anna and West, Jonathan and Matthews, Ed and Golby, Christopher and Ward, Thomas and Lopez, D. Natalie and Freeman, Daniel and Waller, Helen and Kuipers, Elizabeth and Bebbington, Paul and Fowler, David and Emsley, Richard and Dunn, Graham and Garety, Philippa", title="How Inclusive, User-Centered Design Research Can Improve Psychological Therapies for Psychosis: Development of SlowMo", journal="JMIR Ment Health", year="2018", month="Dec", day="05", volume="5", number="4", pages="e11222", keywords="inclusive design", keywords="user-centered design", keywords="participatory design", keywords="design thinking", keywords="mHealth", keywords="eHealth", keywords="digital therapy", keywords="schizophrenia", keywords="paranoia", keywords="psychosis", abstract="Background: Real-world implementation of psychological interventions for psychosis is poor. Barriers include therapy being insufficiently usable and useful for a diverse range of people. User-centered, inclusive design approaches could improve the usability of therapy, which may increase uptake, adherence, and effectiveness. Objective: This study aimed to optimize the usability of an existing psychological intervention, Thinking Well, which targets reasoning processes in paranoia using a basic digital interface. Methods: We conducted inclusive, user-centered design research characterized by purposive sampling of extreme users from the margins of groups, ethnographic investigation of the problem context, and iterative prototyping of solutions. The UK Design Council's double diamond method was used. This consisted of 4 phases: discover, including a case series of Thinking Well, stakeholder interviews, desk research, user profiling, system mapping, and a mood board; define, consisting of workshops to synthesize findings and generate the design brief; develop, involving concept workshops and prototype testing; and deliver, in which the final minimal viable product was storyboarded and iteratively coded. Results: Consistent with our previous work, the Thinking Well case series showed medium to large effects on paranoia and well-being and small effects on reasoning. These were maintained at follow-up despite some participants reporting difficulties with the therapy interface. Insights from the discover phase confirmed that usability was challenged by information complexity and poor accessibility. Participants were generally positive about the potential of technology to be enjoyable, help manage paranoia, and provide tailored interpersonal support from therapists and peers, although they reported privacy and security concerns. The define phase highlighted that the therapy redesign should support monitoring, simplify information processing, enhance enjoyment and trust, promote personalization and normalization, and offer flexible interpersonal support. During the develop phase over 60 concepts were created, with 2 key concepts of thoughts visualized as bubbles and therapy as a journey selected for storyboarding. The output of the deliver phase was a minimal viable product of an innovative digital therapy, SlowMo. SlowMo works by helping people to notice their worries and fast thinking habits, and encourages them to slow down for a moment to find ways of feeling safer. A Web app supports the delivery of 8 face-to-face sessions, which are synchronized to a native mobile app. Conclusions: SlowMo makes use of personalization, ambient information, and visual metaphors to tailor the appeal, engagement, and memorability of therapy to a diversity of needs. Feasibility testing has been promising, and the efficacy of SlowMo therapy is now being tested in a multicentered randomized controlled trial. The study demonstrates that developments in psychological theory and techniques can be enhanced by improving the usability of the therapy interface to optimize its impact in daily life. ", doi="10.2196/11222", url="http://mental.jmir.org/2018/4/e11222/", url="http://www.ncbi.nlm.nih.gov/pubmed/30518514" } @Article{info:doi/10.2196/10091, author="Bucci, Sandra and Morris, Rohan and Berry, Katherine and Berry, Natalie and Haddock, Gillian and Barrowclough, Christine and Lewis, Sh{\^o}n and Edge, Dawn", title="Early Psychosis Service User Views on Digital Technology: Qualitative Analysis", journal="JMIR Ment Health", year="2018", month="Oct", day="31", volume="5", number="4", pages="e10091", keywords="qualitative", keywords="psychosis", keywords="framework analysis", keywords="digital health", keywords="mHealth", keywords="mobile phone", abstract="Background: Digital technology has the potential to improve outcomes for people with psychosis. However, to date, research has largely ignored service user views on digital health interventions (DHIs). Objective: The objective of our study was to explore early psychosis service users' subjective views on DHIs. Methods: Framework analysis was undertaken with data obtained from 21 semistructured interviews with people registered with early intervention for psychosis services. Robust measures were used to develop a stable framework, including member checking, triangulation, independent verification of themes, and consensus meetings. Results: The following 4 themes were established a priori: acceptability of technology in psychosis and mental health; technology increasing access to and augmenting mental health support; barriers to adopting DHIs; and concerns about management of data protection, privacy, risk, and security of information. The following 2 themes were generated a posteriori: blending DHIs with face-to-face treatment and empowerment, control, and choice. DHIs were also viewed as potentially destigmatizing, overcoming barriers faced in traditional service settings, facilitating communication, and empowering service users to take active control of their health care. Conclusions: In the first study of its kind, early psychosis service users' were largely positive about the potential use of DHIs supporting and managing mental health. Overall, service users felt that DHIs were a progressive, modern, and relevant platform for health care delivery. Concerns were expressed around privacy and data security and practical barriers inherent within DHIs, all of which require further attention. Future research should explore whether findings transfer to other service user groups, other technology delivery formats, and across a range of treatment modalities. ", doi="10.2196/10091", url="http://mental.jmir.org/2018/4/e10091/", url="http://www.ncbi.nlm.nih.gov/pubmed/30381280" } @Article{info:doi/10.2196/11160, author="Fletcher, Kathryn and Foley, Fiona and Murray, Greg", title="Web-Based Self-Management Programs for Bipolar Disorder: Insights From the Online, Recovery-Oriented Bipolar Individualised Tool Project", journal="J Med Internet Res", year="2018", month="Oct", day="24", volume="20", number="10", pages="e11160", keywords="Web-based intervention", keywords="bipolar disorder", keywords="self-management", abstract="Background: Bipolar disorder (BD) is a complex, relapsing mood disorder characterized by considerable morbidity and mortality. Web-based self-management interventions provide marked opportunities for several chronic mental health conditions. However, Web-based self-management programs targeting BD are underrepresented compared with programs targeting other psychiatric conditions. Objective: This paper aims at facilitating future research in the area of self-management of BD and draws insights from the development of one such intervention---the Online, Recovery-Oriented Bipolar Individualised Tool (ORBIT)---that is aimed at improving the quality of life of people with BD. Methods: We have discussed the opportunities and challenges in developing an engaging, evidence-based, safe intervention within the context of the following three nested domains: (1) intervention development; (2) scientific testing of the intervention; and (3) ethical framework including risk management. Results: We gained the following insights across the three abovementioned overlapping domains: Web-based interventions can be optimized through (1) codesign with consumers with lived experience to ensure relevance and appropriateness to the target audience; (2) novel content development processes that iteratively combine evidence-based information with lived experience perspectives, capitalizing on multimedia (eg, videos) that the digital health space provides; and (3) incorporating Web-based communities to connect end users and promote constructive engagement by access to a Web-based coach. Conclusions: Self-management is effective in BD, even for those on the more severe end of the spectrum. While there are challenges to be aware of, guided self-management programs, such as those offered by the ORBIT project, which are specifically developed for Web-based delivery provide highly accessible, engaging, and potentially provocative treatments for chronically ill populations who may otherwise have never engaged with treatment. Key questions about engagement, effectiveness, and cost-effectiveness will be answered by the ORBIT project over the next 18 months. ", doi="10.2196/11160", url="http://www.jmir.org/2018/10/e11160/", url="http://www.ncbi.nlm.nih.gov/pubmed/30355553" } @Article{info:doi/10.2196/10157, author="Terp, Malene and J{\o}rgensen, Rikke and Laursen, Schantz Birgitte and Mainz, Jan and Bj{\o}rnes, D. Charlotte", title="A Smartphone App to Foster Power in the Everyday Management of Living With Schizophrenia: Qualitative Analysis of Young Adults' Perspectives", journal="JMIR Ment Health", year="2018", month="Oct", day="01", volume="5", number="4", pages="e10157", keywords="mental health", keywords="mHealth", keywords="mobile app", keywords="participatory design", keywords="patient empowerment", keywords="patient involvement", keywords="patient participation", keywords="schizophrenia", keywords="smartphone", keywords="young adults", abstract="Background: Literature indicates that using smartphone technology is a feasible way of empowering young adults recently diagnosed with schizophrenia to manage everyday living with their illness. The perspective of young adults on this matter, however, is unexplored. Objective: This study aimed at exploring how young adults recently diagnosed with schizophrenia used and perceived a smartphone app (MindFrame) as a tool to foster power in the everyday management of living with their illness. Methods: Using participatory design thinking and methods, MindFrame was iteratively developed. MindFrame consists of a smartphone app that allows young adults to access resources to aid their self-management. The app is affiliated with a website to support collaboration with their health care providers (HCPs). From January to December 2016, community-dwelling young adults with a recent diagnosis of schizophrenia were invited to use MindFrame as part of their care. They customized the resources while assessing their health on a daily basis. Then, they were invited to evaluate the use and provide their perspective on the app. The evaluation was qualitative, and data were generated from in-depth interviews. Data were analyzed using a hermeneutical approach. Results: A total of 98 individuals were eligible for the study (mean age 24.8, range 18-36). Of these, 27 used MindFrame and 13 participated in the evaluation. The analysis showed that to the young adults, MindFrame served to foster power in their everyday management of living with schizophrenia. When MindFrame was used with the HCPs consistently for more than a month, it could provide them with the power to keep up their medication, to keep a step ahead of their illness, and to get appropriate help based on their needs. This empowered them to stay on track with their illness, thus in control of it. It was also reported that MindFrame could fuel the fear of restraint and illness exacerbation, thereby disempowering some from feeling certain and secure. Conclusions: The findings demonstrate that young adults diagnosed with schizophrenia are amenable to use a smartphone app to monitor their health, manage their medication, and stay alert of the early signs of illness exacerbation. This may empower them to stay on track with their illness, thus in control of it. This indicates the potential of smartphone-based care being capable of aiding this specific population to more confidently manage their new life situation. The potentially disempowering aspect of MindFrame accentuates a need for further research to understand the best uptake and the limitations of smartphone-based schizophrenia care of young adults. ", doi="10.2196/10157", url="https://mental.jmir.org/2018/4/e10157/", url="http://www.ncbi.nlm.nih.gov/pubmed/30274966" } @Article{info:doi/10.2196/mental.9857, author="Onwumere, Juliana and Amaral, Filipa and Valmaggia, R. Lucia", title="Digital Technology for Caregivers of People With Psychosis: Systematic Review", journal="JMIR Ment Health", year="2018", month="Sep", day="05", volume="5", number="3", pages="e55", keywords="carers", keywords="digital interventions", keywords="families", keywords="psychosis", keywords="technology", abstract="Background: Psychotic disorders are severe mental health conditions that adversely affect the quality of life and life expectancy. Schizophrenia, the most common and severe form of psychosis affects 21 million people globally. Informal caregivers (families) are known to play an important role in facilitating patient recovery outcomes, although their own health and well-being could be adversely affected by the illness. The application of novel digital interventions in mental health care for patient groups is rapidly expanding; interestingly, however, far less is known about their role with family caregivers. Objective: This study aimed to systematically identify the application of digital interventions that focus on informal caregivers of people with psychosis and describe their outcomes. Methods: We completed a search for relevant papers in four electronic databases (EMBASE, MEDLINE, PsycINFO, and Web of Science). The search also included the Cochrane database and manual search of reference lists of relevant papers. The search was undertaken in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines. Results: The search identified 9 studies derived from 8 unique datasets. Most studies were assessments of feasibility and were undertaken in the United States. Interventions were predominately Web-based, with a focus on improving the caregivers' knowledge and understanding about psychosis. Conclusions: This study offers preliminary support for the feasibility and acceptability of digital interventions for psychosis in informal caregiver populations. However, the findings underpin a clear need for greater development in the range of caregiver-focused digital approaches on offer and robust evaluation of their outcomes. The use of digital approaches with caregiver populations seemingly lags someway behind the significant developments observed in patient groups. ", doi="10.2196/mental.9857", url="http://mental.jmir.org/2018/3/e55/", url="http://www.ncbi.nlm.nih.gov/pubmed/30185402" } @Article{info:doi/10.2196/10092, author="Mueller, E. Nora and Panch, Trishan and Macias, Cathaleene and Cohen, M. Bruce and Ongur, Dost and Baker, T. Justin", title="Using Smartphone Apps to Promote Psychiatric Rehabilitation in a Peer-Led Community Support Program: Pilot Study", journal="JMIR Ment Health", year="2018", month="Aug", day="15", volume="5", number="3", pages="e10092", keywords="psychosis", keywords="smartphone", keywords="app", abstract="Background: Management of severe and persistent mental illness is a complex, resource-intensive challenge for individuals, their families, treaters, and the health care system at large. Community-based rehabilitation, in which peer specialists provide support for individuals managing their own condition, has demonstrated effectiveness but has only been implemented in specialty centers. It remains unclear how the peer-based community rehabilitation model could be expanded, given that it requires significant resources to both establish and maintain. Objective: Here, we describe the results from a study of one such program implemented within Waverley Place, a community support program at McLean Hospital, emphasizing psychiatric rehabilitation for individuals with severe and persistent mental illness, as well as describing the challenges encountered during the implementation of the program. Key questions were whether the patients could, and would, successfully use the app. Methods: The smartphone app offered multiple features relevant to psychiatric rehabilitation, including daily task lists, activity tracking, and text messaging with peer specialists. A 90-day program of activities, goals, and content specific to the community support program was created on the basis of a prior pilot, in collaboration between members of the app development team (WellFrame), and peers, clinical, and research staff associated with the program. Hospital research staff recruited patients into the study, monitored peer and patient engagement, and handled all raw data acquired from the study. Results: Of 100 people approached for the study, a total of 13 provided consent, of which 10 downloaded and used the app. Two patients were unable to complete the app installation. Five used the app regularly as part of their daily lives for at least 20 days of the 90-day program. We were unable to identify any specific factors (eg, clinical or demographic) that affected willingness to consent or engage with the app platform in the very limited sample, although the individuals with significant app use were generally satisfied with the experience. Conclusions: Smartphone apps may become a useful tool for psychiatric rehabilitation, addressing both psychiatric and co-occurring medical problems. Individualizing functions to each patient and facilitating connection with a certified peer specialist may be an important feature of useful apps. Unlike prior reports emphasizing that patients with schizophrenia will adopt smartphone platforms, we found that implementation of digital tools into existing community support programs for severe and persistent mental illness has many challenges yet to be fully overcome to realize the potential benefits such apps could have to promote systematization and cost reduction for psychiatric rehabilitation. ", doi="10.2196/10092", url="http://mental.jmir.org/2018/3/e10092/", url="http://www.ncbi.nlm.nih.gov/pubmed/30111526" } @Article{info:doi/10.2196/mental.9950, author="Bonet, Lucia and Ll{\'a}cer, Blanca and Hernandez-Viadel, Miguel and Arce, David and Blanquer, Ignacio and Ca{\~n}ete, Carlos and Escart{\'i}, Maria and Gonz{\'a}lez-Pinto, M. Ana and Sanju{\'a}n, Julio", title="Differences in the Use and Opinions About New eHealth Technologies Among Patients With Psychosis: Structured Questionnaire", journal="JMIR Ment Health", year="2018", month="Jul", day="25", volume="5", number="3", pages="e51", keywords="eHealth", keywords="internet", keywords="mobile phone", keywords="viability", keywords="acceptability", keywords="psychosis", keywords="schizophrenia", abstract="Background: Despite a growing interest in the use of technology in order to support the treatment of psychotic disorders, limited knowledge exists about the viability and acceptability of these eHealth interventions in relation to the clinical characteristics of patients. Objective: The objective of this study was to assess the access and use of, as well as experiences and interest in, new technologies using a survey of patients diagnosed with early psychosis compared with a survey of patients diagnosed with chronic psychotic disorders. Methods: We designed a structured questionnaire. This questionnaire was divided into five parts: (1) clinical and demographic information, (2) access and use of the internet, (3) use of the internet in relation to mental health, (4) experiences with technology, and (5) patients' interest in eHealth services. In total, 105 patients were recruited from early psychosis units (n=65) and recovery units (n=40). Results: In this study, 84.8\% (89/105) of the patients had access to the internet and 88.6\% (93/105) owned an electronic internet device. In total, 71.3\% (57/80) of patients who owned a mobile phone were interested in eHealth systems and 38.2\% (37/97) reported negative experiences related to the internet usage. We observed differences between the groups in terms of device ownership (P=.02), the frequency of internet access (P<.001), the use of social media (P=.01), and seeking health information (P=.04); the differences were found to be higher in the early psychosis group. No differences were found between the groups in terms of the use of internet in relation to mental health, experiences and opinions about the internet, or interest in eHealth interventions (P=.43). Conclusions: The availability and use of technology for the participants in our survey were equivalent to those for the general population. The differences found between the groups in relation to the access or use of technology seemed to due to age-related factors. The use of technology involving mental health and the interest in eHealth interventions were mainly positive and equivalent between the groups. Accordingly, this group of patients is a potential target for the emerging eHealth interventions, regardless of their clinical status. However, 28.7\% (23/80) of the studied patients rejected the use of internet interventions and 38.2\% (37/97) had unpleasant experiences related to its usage; thus, more in-depth studies are needed to better define the profile of patients with psychosis who may benefit from eHealth treatments. ", doi="10.2196/mental.9950", url="http://mental.jmir.org/2018/3/e51/", url="http://www.ncbi.nlm.nih.gov/pubmed/30045835" } @Article{info:doi/10.2196/resprot.8810, author="Lal, Shalini and Gleeson, John and Malla, Ashok and Rivard, Lysanne and Joober, Ridha and Chandrasena, Ranjith and Alvarez-Jimenez, Mario", title="Cultural and Contextual Adaptation of an eHealth Intervention for Youth Receiving Services for First-Episode Psychosis: Adaptation Framework and Protocol for Horyzons-Canada Phase 1", journal="JMIR Res Protoc", year="2018", month="Apr", day="23", volume="7", number="4", pages="e100", keywords="mental health", keywords="young adult", keywords="telemedicine", keywords="eHealth", keywords="social support", keywords="therapy", keywords="psychology", abstract="Background: eHealth interventions have the potential to address challenges related to access, service engagement, and continuity of care in the delivery of mental health services. However, the initial development and evaluation of such interventions can require substantive amounts of financial and human resource investments to bring them to scale. Therefore, it may be warranted to pay greater attention to policy, services, and research with respect to eHealth platforms that have the potential to be adapted for use across settings. Yet, limited attention has been placed on the methods and processes for adapting eHealth interventions to improve their applicability across cultural, geographical, and contextual boundaries. Objective: In this paper, we describe an adaptation framework and protocol to adapt an eHealth intervention designed to promote recovery and prevent relapses in youth receiving specialized services for first-episode psychosis. The Web-based platform, called Horyzons, was initially developed and tested in Australia and is now being prepared for evaluation in Canada. Methods: Service users and service providers from 2 specialized early intervention programs for first-episode psychosis located in different provinces will explore a beta-version of the eHealth intervention through focus group discussions and extended personal explorations to identify the need for, and content of contextual and cultural adaptations. An iterative consultation process will then take place with service providers and users to develop and assess platform adaptations in preparation for a pilot study with a live version of the platform. Results: Data collection was completed in August 2017, and analysis and adaptation are in process. The first results of the study will be submitted for publication in 2018 and will provide preliminary insights into the acceptability of the Web-based platform (eg, perceived use and perceived usefulness) from service provider and service user perspectives. The project will also provide knowledge about the adaptations and process needed to prepare the platform for evaluation in Canada. Conclusions: This study contributes to an important gap in the literature pertaining to the specific principles, methods, and steps involved in adapting eHealth interventions for implementation and evaluation across a diverse range of cultural, geographical, and health care settings. ", doi="10.2196/resprot.8810", url="http://www.researchprotocols.org/2018/4/e100/", url="http://www.ncbi.nlm.nih.gov/pubmed/29685867" } @Article{info:doi/10.2196/mental.8551, author="Kumar, Divya and Tully, M. Laura and Iosif, Ana-Maria and Zakskorn, N. Lauren and Nye, E. Kathleen and Zia, Aqsa and Niendam, Ann Tara", title="A Mobile Health Platform for Clinical Monitoring in Early Psychosis: Implementation in Community-Based Outpatient Early Psychosis Care", journal="JMIR Ment Health", year="2018", month="Feb", day="27", volume="5", number="1", pages="e15", keywords="mHealth", keywords="schizophrenia", keywords="smartphone", keywords="ecological momentary assessment", keywords="experience sampling", abstract="Background: A growing body of literature indicates that smartphone technology is a feasible add-on tool in the treatment of individuals with early psychosis (EP) . However, most studies to date have been conducted independent of outpatient care or in a research clinic setting, often with financial incentives to maintain user adherence to the technology. Feasibility of dissemination and implementation of smartphone technology into community mental health centers (CMHCs) has yet to be tested, and whether young adults with EP will use this technology for long periods of time without incentive is unknown. Furthermore, although EP individuals willingly adopt smartphone technology as part of their treatment, it remains unclear whether providers are amenable to integrating smartphone technology into treatment protocols. Objective: This study aimed to establish the feasibility of implementing a smartphone app and affiliated Web-based dashboard in 4 community outpatient EP clinics in Northern California. Methods: EP individuals in 4 clinics downloaded an app on their smartphone and responded to daily surveys regarding mood and symptoms for up to 5 months. Treatment providers at the affiliated clinics viewed survey responses on a secure Web-based dashboard in sessions with their clients and between appointments. EP clients and treatment providers filled out satisfaction surveys at study end regarding usability of the app. Results: Sixty-one EP clients and 20 treatment providers enrolled in the study for up to 5 months. Forty-one EP clients completed the study, and all treatment providers remained in the study for their duration in the clinic. Survey completion for all 61 EP clients was moderate: 40\% and 39\% for daily and weekly surveys, respectively. Completion rates were slightly higher in the participants who completed the study: 44\% and 41\% for daily and weekly surveys, respectively. Twenty-seven of 41 (66\%) EP clients who completed the study and 11 of 13 (85\%) treatment providers who responded to satisfaction surveys reported they would continue to use the app as part of treatment services. Six (15\%; 6/41) clients and 3 providers (23\%; 3/13) stated that technological glitches impeded their engagement with the platform. Conclusions: EP clients and treatment providers in community-based outpatient clinics are responsive to integrating smartphone technology into treatment services. There were logistical and technical challenges associated with enrolling individuals in CMHCs. To be most effective, implementing smartphone technology in CMHC EP care necessitates adequate technical staff and support for utilization of the platform. ", doi="10.2196/mental.8551", url="http://mental.jmir.org/2018/1/e15/", url="http://www.ncbi.nlm.nih.gov/pubmed/29487044" } @Article{info:doi/10.2196/mental.7717, author="Mistler, A. Lisa and Ben-Zeev, Dror and Carpenter-Song, Elizabeth and Brunette, F. Mary and Friedman, J. Matthew", title="Mobile Mindfulness Intervention on an Acute Psychiatric Unit: Feasibility and Acceptability Study", journal="JMIR Ment Health", year="2017", month="Aug", day="21", volume="4", number="3", pages="e34", keywords="mindfulness", keywords="meditation", keywords="mHealth", keywords="psychiatry", keywords="mobile phone", keywords="aggression", keywords="violence", keywords="schizophrenia", keywords="bipolar disorder", keywords="psychotic disorders", abstract="Background: Aggression and violence on acute psychiatric inpatient units is extensive and leads to negative sequelae for staff and patients. With increasingly acute inpatient milieus due to shorter lengths of stay, inpatient staff is limited in training and time to be able to provide treatments. Mobile technology provides a new platform for offering treatment on such units, but it has not been tested for feasibility or usability in this particular setting. Objective: The aim of this study was to examine the feasibility, usability, and acceptability of a brief mindfulness meditation mobile phone app intended to reduce anger and aggression in acute psychiatric inpatients with schizophrenia, schizoaffective disorder, or bipolar disorder, and a history of violence. Methods: Participants were recruited between November 1, 2015 and June 1, 2016. A total of 13 inpatients at an acute care state hospital carried mobile phones for 1 week and were asked to try a commercially available mindfulness app called Headspace. The participants completed a usability questionnaire and engaged in a qualitative interview upon completion of the 7 days. In addition, measures of mindfulness, state and trait anger, and cognitive ability were administered before and after the intervention. Results: Of the 13 enrolled participants, 10 used the app for the 7 days of the study and completed all measures. Two additional participants used the app for fewer than 7 days and completed all measures. All participants found the app to be engaging and easy to use. Most (10/12, 83\%) felt comfortable using Headspace and 83\% (10/12) would recommend it to others. All participants made some effort to try the app, with 6 participants (6/12, 50\%) completing the first 10 10-minute ``foundation'' guided meditations. Conclusions: This is the first known study of the use of a commercially available app as an intervention on acute psychiatric inpatient units. Acutely ill psychiatric inpatients at a state hospital found the Headspace app easy to use, were able to complete a series of meditations, and felt the app helped with anxiety, sleep, and boredom on the unit. There were no instances of an increase in psychotic symptoms reported and there were no episodes of aggression or violence noted in the record. ", doi="10.2196/mental.7717", url="http://mental.jmir.org/2017/3/e34/", url="http://www.ncbi.nlm.nih.gov/pubmed/28827214" } @Article{info:doi/10.2196/jmir.7956, author="Birnbaum, L. Michael and Ernala, Kiranmai Sindhu and Rizvi, F. Asra and De Choudhury, Munmun and Kane, M. John", title="A Collaborative Approach to Identifying Social Media Markers of Schizophrenia by Employing Machine Learning and Clinical Appraisals", journal="J Med Internet Res", year="2017", month="Aug", day="14", volume="19", number="8", pages="e289", keywords="schizophrenia", keywords="psychotic disorders", keywords="online social networks", keywords="machine learning", keywords="linguistic analysis", keywords="Twitter", abstract="Background: Linguistic analysis of publicly available Twitter feeds have achieved success in differentiating individuals who self-disclose online as having schizophrenia from healthy controls. To date, limited efforts have included expert input to evaluate the authenticity of diagnostic self-disclosures. Objective: This study aims to move from noisy self-reports of schizophrenia on social media to more accurate identification of diagnoses by exploring a human-machine partnered approach, wherein computational linguistic analysis of shared content is combined with clinical appraisals. Methods: Twitter timeline data, extracted from 671 users with self-disclosed diagnoses of schizophrenia, was appraised for authenticity by expert clinicians. Data from disclosures deemed true were used to build a classifier aiming to distinguish users with schizophrenia from healthy controls. Results from the classifier were compared to expert appraisals on new, unseen Twitter users. Results: Significant linguistic differences were identified in the schizophrenia group including greater use of interpersonal pronouns (P<.001), decreased emphasis on friendship (P<.001), and greater emphasis on biological processes (P<.001). The resulting classifier distinguished users with disclosures of schizophrenia deemed genuine from control users with a mean accuracy of 88\% using linguistic data alone. Compared to clinicians on new, unseen users, the classifier's precision, recall, and accuracy measures were 0.27, 0.77, and 0.59, respectively. Conclusions: These data reinforce the need for ongoing collaborations integrating expertise from multiple fields to strengthen our ability to accurately identify and effectively engage individuals with mental illness online. These collaborations are crucial to overcome some of mental illnesses' biggest challenges by using digital technology. ", doi="10.2196/jmir.7956", url="http://www.jmir.org/2017/8/e289/", url="http://www.ncbi.nlm.nih.gov/pubmed/28807891" } @Article{info:doi/10.2196/humanfactors.5933, author="Ferron, C. Joelle and Brunette, F. Mary and Geiger, Pamela and Marsch, A. Lisa and Adachi-Mejia, M. Anna and Bartels, J. Stephen", title="Mobile Phone Apps for Smoking Cessation: Quality and Usability Among Smokers With Psychosis", journal="JMIR Hum Factors", year="2017", month="Mar", day="03", volume="4", number="1", pages="e7", keywords="mHealth", keywords="mobile apps", keywords="smoking cessation", keywords="schizophrenia", keywords="psychotic disorders", abstract="Background: Smoking is one of the top preventable causes of mortality in people with psychotic disorders such as schizophrenia. Cessation treatment improves abstinence outcomes, but access is a barrier. Mobile phone apps are one way to increase access to cessation treatment; however, whether they are usable by people with psychotic disorders, who often have special learning needs, is not known. Objective: Researchers reviewed 100 randomly selected apps for smoking cessation to rate them based on US guidelines for nicotine addiction treatment and to categorize them based on app functions. We aimed to test the usability and usefulness of the top-rated apps in 21 smokers with psychotic disorders. Methods: We identified 766 smoking cessation apps and randomly selected 100 for review. Two independent reviewers rated each app with the Adherence Index to US Clinical Practice Guideline for Treating Tobacco Use and Dependence. Then, smokers with psychotic disorders evaluated the top 9 apps within a usability testing protocol. We analyzed quantitative results using descriptive statistics and t tests. Qualitative data were open-coded and analyzed for themes. Results: Regarding adherence to practice guidelines, most of the randomly sampled smoking cessation apps scored poorly---66\% rated lower than 10 out of 100 on the Adherence Index (Mean 11.47, SD 11.8). Regarding usability, three common usability problems emerged: text-dense content, abstract symbols on the homepage, and subtle directions to edit features. Conclusions: In order for apps to be effective and usable for this population, developers should utilize a balance of text and simple design that facilitate ease of navigation and content comprehension that will help people learn quit smoking skills. ", doi="10.2196/humanfactors.5933", url="http://humanfactors.jmir.org/2017/1/e7/", url="http://www.ncbi.nlm.nih.gov/pubmed/28258047" } @Article{info:doi/10.2196/mhealth.7030, author="Bain, E. Earle and Shafner, Laura and Walling, P. David and Othman, A. Ahmed and Chuang-Stein, Christy and Hinkle, John and Hanina, Adam", title="Use of a Novel Artificial Intelligence Platform on Mobile Devices to Assess Dosing Compliance in a Phase 2 Clinical Trial in Subjects With Schizophrenia", journal="JMIR Mhealth Uhealth", year="2017", month="Feb", day="21", volume="5", number="2", pages="e18", keywords="medication adherence", keywords="artificial intelligence", keywords="clinical trials as topic", abstract="Background: Accurately monitoring and collecting drug adherence data can allow for better understanding and interpretation of the outcomes of clinical trials. Most clinical trials use a combination of pill counts and self-reported data to measure drug adherence, despite the drawbacks of relying on these types of indirect measures. It is assumed that doses are taken, but the exact timing of these events is often incomplete and imprecise. Objective: The objective of this pilot study was to evaluate the use of a novel artificial intelligence (AI) platform (AiCure) on mobile devices for measuring medication adherence, compared with modified directly observed therapy (mDOT) in a substudy of a Phase 2 trial of the $\alpha$7 nicotinic receptor agonist (ABT-126) in subjects with schizophrenia. Methods: AI platform generated adherence measures were compared with adherence inferred from drug concentration measurements. Results: The mean cumulative pharmacokinetic adherence over 24 weeks was 89.7\% (standard deviation [SD] 24.92) for subjects receiving ABT-126 who were monitored using the AI platform, compared with 71.9\% (SD 39.81) for subjects receiving ABT-126 who were monitored by mDOT. The difference was 17.9\% (95\% CI -2 to 37.7; P=.08). Conclusions: Using drug levels, this substudy demonstrates the potential of AI platforms to increase adherence, rapidly detect nonadherence, and predict future nonadherence. Subjects monitored using the AI platform demonstrated a percentage change in adherence of 25\% over the mDOT group. Subjects were able to use the technology successfully for up to 6 months in an ambulatory setting with early termination rates that are comparable to subjects outside of the substudy. Trial Registration: ClinicalTrials.gov NCT01655680 https://clinicaltrials.gov/ct2/show/NCT01655680?term=NCT01655680 ", doi="10.2196/mhealth.7030", url="http://mhealth.jmir.org/2017/2/e18/", url="http://www.ncbi.nlm.nih.gov/pubmed/28223265" } @Article{info:doi/10.2196/jmir.5954, author="Berrouiguet, Sofian and Barrig{\'o}n, Luisa Maria and Brandt, A. Sara and Nitzburg, C. George and Ovejero, Santiago and Alvarez-Garcia, Raquel and Carballo, Juan and Walter, Michel and Billot, Romain and Lenca, Philippe and Delgado-Gomez, David and Ropars, Juliette and de la Calle Gonzalez, Ivan and Courtet, Philippe and Baca-Garc{\'i}a, Enrique", title="Ecological Assessment of Clinicians' Antipsychotic Prescription Habits in Psychiatric Inpatients: A Novel Web- and Mobile Phone--Based Prototype for a Dynamic Clinical Decision Support System", journal="J Med Internet Res", year="2017", month="Jan", day="26", volume="19", number="1", pages="e25", keywords="clinical decision-making", keywords="antipsychotic agents", keywords="software", keywords="mobile applications", keywords="off-label use", keywords="prescriptions", abstract="Background: Electronic prescribing devices with clinical decision support systems (CDSSs) hold the potential to significantly improve pharmacological treatment management. Objective: The aim of our study was to develop a novel Web- and mobile phone--based application to provide a dynamic CDSS by monitoring and analyzing practitioners' antipsychotic prescription habits and simultaneously linking these data to inpatients' symptom changes. Methods: We recruited 353 psychiatric inpatients whose symptom levels and prescribed medications were inputted into the MEmind application. We standardized all medications in the MEmind database using the Anatomical Therapeutic Chemical (ATC) classification system and the defined daily dose (DDD). For each patient, MEmind calculated an average for the daily dose prescribed for antipsychotics (using the N05A ATC code), prescribed daily dose (PDD), and the PDD to DDD ratio. Results: MEmind results found that antipsychotics were used by 61.5\% (217/353) of inpatients, with the largest proportion being patients with schizophrenia spectrum disorders (33.4\%, 118/353). Of the 217 patients, 137 (63.2\%, 137/217) were administered pharmacological monotherapy and 80 (36.8\%, 80/217) were administered polytherapy. Antipsychotics were used mostly in schizophrenia spectrum and related psychotic disorders, but they were also prescribed in other nonpsychotic diagnoses. Notably, we observed polypharmacy going against current antipsychotics guidelines. Conclusions: MEmind data indicated that antipsychotic polypharmacy and off-label use in inpatient units is commonly practiced. MEmind holds the potential to create a dynamic CDSS that provides real-time tracking of prescription practices and symptom change. Such feedback can help practitioners determine a maximally therapeutic drug treatment while avoiding unproductive overprescription and off-label use. ", doi="10.2196/jmir.5954", url="http://www.jmir.org/2017/1/e25/", url="http://www.ncbi.nlm.nih.gov/pubmed/28126703" } @Article{info:doi/10.2196/mental.5946, author="Villani, Murielle and Kovess-Masfety, Viviane", title="How Do People Experiencing Schizophrenia Spectrum Disorders or Other Psychotic Disorders Use the Internet to Get Information on Their Mental Health? Literature Review and Recommendations", journal="JMIR Ment Health", year="2017", month="Jan", day="03", volume="4", number="1", pages="e1", keywords="Internet", keywords="health information", keywords="e-mental health", keywords="e-support", keywords="schizophrenia spectrum disorders", keywords="psychotic disorders", abstract="Background: Studies show that the Internet has become an influential source of information for people experiencing serious psychiatric conditions such as schizophrenia spectrum disorders or other psychotic disorders, among which the rate of Internet users is growing, with rates ranging from 33.3\% to 79.5\% given the country. Between 20.5\% and 56.4\% of these Internet users seek mental health information. Objective: Focusing on this population's Web searches about their mental health, this paper examines what type of content they look for and what could be the benefits and disadvantages of this navigation. Methods: We conducted a literature review through medical and psychological databases between 2000 and 2015 using the keywords ``Internet,'' ``Web,'' ``virtual,'' ``health information,'' ``schizophrenia,'' ``psychosis,'' ``e-mental health,'' ``e-support,'' and ``telepsychiatry.'' Results: People experiencing schizophrenia spectrum disorders or other psychotic disorders wish to find on the Internet trustful, nonstigmatizing information about their disease, flexibility, security standards, and positive peer-to-peer exchanges. E-mental health also appears to be desired by a substantial proportion of them. In this field, the current developments towards intervention and early prevention in the areas of depression and bipolar and anxiety disorders become more and more operational for schizophrenia spectrum disorders and other psychotic disorders as well. The many benefits of the Internet as a source of information and support, such as empowerment, enhancement of self-esteem, relief from peer information, better social interactions, and more available care, seem to outbalance the difficulties. Conclusions: In this paper, after discussing the challenges related to the various aspects of the emergence of the Internet into the life of people experiencing schizophrenia spectrum disorders or other psychotic disorders, we will suggest areas of future research and practical recommendations for this major transition. ", doi="10.2196/mental.5946", url="http://mental.jmir.org/2017/1/e1/", url="http://www.ncbi.nlm.nih.gov/pubmed/28049620" } @Article{info:doi/10.2196/mental.6671, author="Biagianti, Bruno and Schlosser, Danielle and Nahum, Mor and Woolley, Josh and Vinogradov, Sophia", title="Creating Live Interactions to Mitigate Barriers (CLIMB): A Mobile Intervention to Improve Social Functioning in People With Chronic Psychotic Disorders", journal="JMIR Ment Health", year="2016", month="Dec", day="13", volume="3", number="4", pages="e52", keywords="psychosis", keywords="social cognition", keywords="digital health", keywords="mobile health", abstract="Background: Numerous psychosocial interventions for individuals with chronic psychotic disorders (CPD) have shown positive effects on social cognitive and functional outcome measures. However, access to and engagement with these interventions remains limited. This is partly because these interventions require specially trained therapists, are not available in all clinical settings, and have a high scheduling burden for participants, usually requiring a commitment of several weeks. Delivering interventions remotely via mobile devices may facilitate access, improve scheduling flexibility, and decrease participant burden, thus improving adherence to intervention requirements. To address these needs, we designed the Creating Live Interactions to Mitigate Barriers (CLIMB) digital intervention, which aims to enhance social functioning in people with CPD. CLIMB consists of two treatment components: a computerized social cognition training (SCT) program and optimized remote group therapy (ORGT). ORGT is an innovative treatment that combines remote group therapy with group texting (short message service, SMS). Objectives: The objectives of this single-arm study were to investigate the feasibility of delivering 6 weeks of CLIMB to people with CPD and explore the initial effects on outcomes. Methods: Participants were recruited, screened and enrolled via the Internet, and delivered assessments and interventions remotely using provided tablets (iPads). Participants were asked to complete 18 hours of SCT and to attend 6 remote group therapy sessions. To assess feasibility, adherence to study procedures, attrition rates, engagement metrics, and acceptability of the intervention were evaluated. Changes on measures of social cognition, quality of life, and symptoms were also explored. Results: In total, 27 participants were enrolled over 12 months. Remote assessments were completed successfully on 96\% (26/27) of the enrolled participants. Retention in the 6-week trial was 78\% (21/27). Of all the iPads used, 95\% (22/23) were returned undamaged at the end of the intervention. Participants on average attended 84\% of the group therapy sessions, completed a median of 9.5 hours of SCT, and posted a median of 5.2 messages per week on the group text chat. Participants rated CLIMB in the medium range in usability, acceptability, enjoyment, and perceived benefit. Participants showed significant improvements in emotion identification abilities for prosodic happiness (P=.001), prosodic happiness intensity (P=.04), and facial anger (P=.04), with large within-group effect sizes (d=.60 to d=.86). Trend-level improvements were observed on aspects of quality of life (P values less than .09). No improvements were observed for symptoms. Conclusions: It is feasible and acceptable to remotely deliver an intervention aimed at enhancing social functioning in people with CPD using mobile devices. This approach may represent a scalable method to increase treatment access and adherence. Our pilot data also demonstrate within-group gains in some aspects of social cognition after 6 weeks of CLIMB. Future randomized controlled studies in larger samples should evaluate the extent to which CLIMB significantly improves social cognition, symptoms, and quality of life in CPD. ", doi="10.2196/mental.6671", url="http://mental.jmir.org/2016/4/e52/", url="http://www.ncbi.nlm.nih.gov/pubmed/27965190" } @Article{info:doi/10.2196/jmir.6511, author="Robotham, Dan and Satkunanathan, Safarina and Doughty, Lisa and Wykes, Til", title="Do We Still Have a Digital Divide in Mental Health? A Five-Year Survey Follow-up", journal="J Med Internet Res", year="2016", month="Nov", day="22", volume="18", number="11", pages="e309", keywords="digital divide", keywords="socioeconomic factors", keywords="technology", keywords="mobile phone", keywords="psychotic disorders", keywords="distance counseling", abstract="Background: Nearly everyone in society uses the Internet in one form or another. The Internet is heralded as an efficient way of providing mental health treatments and services. However, some people are still excluded from using Internet-enabled technology through lack of resources, skills, and confidence. Objective: Five years ago, we showed that people with severe mental illness were at risk of digital exclusion, especially middle-aged patients with psychosis and/or people from black or minority ethnic groups with psychosis. An understanding of the breadth of potential digital exclusion is vital for the implementation of digital health services. The aim of this study is to understand the context of digital exclusion for people who experience mental illness. Methods: We conducted a survey involving people with a primary diagnosis of psychosis or depression in London, United Kingdom. A total of 241 participants were recruited: 121 with psychosis and 120 with depression. The majority of surveys were collected face-to-face (psychosis: n=109; depression: n=71). Participants answered questions regarding familiarity, access, use, motivation, and confidence with Internet-enabled technologies (ie, computers and mobile phones). Variables predicting digital exclusion were identified in regression analyses. The results were compared with the survey conducted in 2011. Results: Digital exclusion has declined since 2011. Online survey collection introduced biases into the sample, masking those who were likely to be excluded. Only 18.3\% (20/109) of people with psychosis in our sample were digitally excluded, compared with 30\% (28/93) in 2011 ($\chi$21=3.8, P=.04). People with psychosis had less confidence in using the Internet than people with depression ($\chi$21=7.4, P=.004). Only 9.9\% (24/241) of participants in the total sample were digitally excluded, but the majority of these people had psychosis (n=20). Those with psychosis who were digitally excluded were significantly older than their included peers (t30=3.3, P=.002) and had used services for longer (t97=2.5, P=.02). Younger people were more likely to use mobile phones. Digitally excluded participants cited a lack of knowledge as a barrier to digital inclusion, and most wanted to use the Internet via computers (rather than mobile phones). Conclusions: Digital exclusion is lower, but some remain excluded. Facilitating inclusion among this population means helping them develop skills and confidence in using technology, and providing them with access. Providing mobile phones without basic information technology training may be counterproductive because excluded people may be excluded from mobile technology too. An evidence-based digital inclusion strategy is needed within the National Health Service to help digitally excluded populations access Internet-enabled services. ", doi="10.2196/jmir.6511", url="http://www.jmir.org/2016/11/e309/", url="http://www.ncbi.nlm.nih.gov/pubmed/27876684" } @Article{info:doi/10.2196/mhealth.5716, author="Huerta-Ramos, Elena and Escobar-Villegas, Soledad Maria and Rubinstein, Katya and Unoka, Szabolcs Zsolt and Grasa, Eva and Hospedales, Margarita and J{\"a}{\"a}skel{\"a}inen, Erika and Rubio-Abadal, Elena and Caspi, Asaf and Bitter, Istv{\'a}n and Berdun, Jesus and Sepp{\"a}l{\"a}, Jussi and Ochoa, Susana and Fazekas, Kata and and Corripio, Iluminada and Usall, Judith", title="Measuring Users' Receptivity Toward an Integral Intervention Model Based on mHealth Solutions for Patients With Treatment-Resistant Schizophrenia (m-RESIST): A Qualitative Study", journal="JMIR Mhealth Uhealth", year="2016", month="Sep", day="28", volume="4", number="3", pages="e112", keywords="mHealth solution", keywords="treatment-resistant schizophrenia", keywords="intervention model", keywords="qualitative research", keywords="needs assessment", abstract="Background: Despite the theoretical potential of mHealth solutions in the treatment of patients with schizophrenia, there remains a lack of technological tools in clinical practice. Objective: The aim of this study was to measure the receptivity of patients, informal carers, and clinicians to a European integral intervention model focused on patients with persistent positive symptoms: Mobile Therapeutic Attention for Patients with Treatment-Resistant Schizophrenia (m-RESIST). Methods: Before defining the system requirements, a qualitative study of the needs of outpatients with treatment-resistant schizophrenia was carried out in Spain, Israel, and Hungary. We analyzed the opinions of patients, informal carers, and clinicians concerning the services originally intended to be part of the solution. A total of 9 focus groups (72 people) and 35 individual interviews were carried out in the 3 countries, using discourse analysis as the framework. Results: A webpage and an online forum were perceived as suitable to get both reliable information on the disease and support. Data transmission by a smart watch (monitoring), Web-based visits, and instant messages (clinical treatment) were valued as ways to improve contact with clinicians. Alerts were appreciated as reminders of daily tasks and appointments. Avoiding stressful situations for outpatients, promoting an active role in the management of the disease, and maintaining human contact with clinicians were the main suggestions provided for improving the effectiveness of the solution. Conclusions: Positive receptivity toward m-RESIST services is related to its usefulness in meeting user needs, its capacity to empower them, and the possibility of maintaining human contact. ", doi="10.2196/mhealth.5716", url="http://mhealth.jmir.org/2016/3/e112/", url="http://www.ncbi.nlm.nih.gov/pubmed/27682896" } @Article{info:doi/10.2196/resprot.3880, author="Wahlstr{\"o}m, Viktor and {\AA}hlander, Fredrik and Wynn, Rolf", title="Auditory Brainstem Response as a Diagnostic Tool for Patients Suffering From Schizophrenia, Attention Deficit Hyperactivity Disorder, and Bipolar Disorder: Protocol", journal="JMIR Res Protoc", year="2015", month="Feb", day="12", volume="4", number="1", pages="e16", keywords="brainstem audiometry", keywords="diagnosis", keywords="schizophrenia", keywords="ADHD", keywords="bipolar disorder", abstract="Background: Psychiatric disorders, such as schizophrenia, attention deficit hyperactivity disorder (ADHD), and bipolar disorder, may sometimes be difficult to diagnose. There is a great need for a valid and reliable diagnostic tool to aid clinicians in arriving at the diagnoses in a timely and accurate manner. Prior studies have suggested that patients suffering from schizophrenia and ADHD may process certain sound stimuli in the brainstem in an unusual manner. When these patient groups have been examined with the electrophysiological method of brainstem audiometry, some studies have found illness-specific aberrations. Such aberrations may also exist for patients suffering from bipolar disorder. Objective: In this study, we will examine whether the method of brainstem audiometry can be used as a diagnostic tool for patients suffering from schizophrenia, ADHD, and bipolar disorder. Methods: The method includes three steps: (1) auditory stimulation with specific sound stimuli, (2) simultaneous measurement of brainstem activity, and (3) automated interpretation of the resulting brain stem audiograms with data-based signal analysis. We will compare three groups of 12 individuals with confirmed diagnoses of schizophrenia, ADHD, or bipolar disorder with 12 healthy subjects under blinded conditions for a total of 48 participants. The extent to which the method can be used to reach the correct diagnosis will be investigated. Results: The project is now in a recruiting phase. When all patients and controls have been recruited and the measurements have been performed, the data will be analyzed according to a previously arranged algorithm. We expect the recruiting phase and measurements to be completed in early 2015, the analyses to be performed in mid-2015, and the results of the study to be published in early 2016. Conclusions: If the results support previous findings, this will lend strength to the idea that brainstem audiometry can offer objective diagnostic support for patients suffering from schizophrenia, ADHD, and bipolar disorder. A positive result from the study could imply that brainstem audiometry could become an important supportive tool for clinicians in their efforts to diagnose patients with these disorders in a timely and accurate manner. Trial Registration: ClinicalTrials.gov NCT01629355; https://clinicaltrials.gov/ct2/show/NCT01629355 (Archived by WebCite at http://www.webcitation.org/6VBfTwx5H). ", doi="10.2196/resprot.3880", url="http://www.researchprotocols.org/2015/1/e16/", url="http://www.ncbi.nlm.nih.gov/pubmed/25679914" } @Article{info:doi/10.2196/mental.3926, author="Forchuk, Cheryl and Donelle, Lorie and Ethridge, Paige and Warner, Laura", title="Client Perceptions of the Mental Health Engagement Network: A Secondary Analysis of an Intervention Using Smartphones and Desktop Devices for Individuals Experiencing Mood or Psychotic Disorders in Canada", journal="JMIR Mental Health", year="2015", month="Jan", day="21", volume="2", number="1", pages="e1", keywords="mental health", keywords="mobile health", keywords="eHealth", keywords="personal health records", keywords="mood disorders", keywords="psychotic disorders", keywords="mental disorders", abstract="Background: The use of innovative technologies in mental health care has the potential to improve system efficiency, enhance quality of care, and increase patient engagement. The Mental Health Engagement Network (MHEN) project developed, delivered, and evaluated an interactive Web-based personal health record, the Lawson SMART Record (LSR), to assist mental health clients in managing their care and connecting with their care providers. This paper presents a secondary analysis of data collected in the MHEN project regarding clients' perceptions of technology and the use of these technologies in their care. Objective: We aimed to answer six questions: (1) What is the level of comfort with technology within a sample of individuals experiencing mood or psychotic disorders? (2) How easy to use and helpful are the MHEN technologies from the perspective of individuals experiencing a mental illness? (3) Are there differences in how helpful or useful individuals find the smartphone compared to the LSR? (4) Are there specific functions of MHEN technologies (eg, reminders for medications or appointments) that are more valued than others? (5) What are the other ways that individuals are using MHEN technologies in their daily lives? (6) How likely are individuals to be able to retain and maintain their smartphone? Methods: Mental health clients aged 18-80 (N=400) and diagnosed with a mood or psychotic disorder were provided with a smartphone (iPhone 4S) and participating care providers (n=52) were provided with a tablet (iPad) in order to access and engage with the LSR. A delayed implementation design with mixed methods was used. Survey and interview data were collected over the course of 18 months through semistructured interviews conducted by experienced research assistants every 6 months post-implementation of the intervention. Paired t tests were used to determine differences between 6 and 12-month data for perceptions of the MHEN technologies. A paired t test was used to examine whether differences existed between perceptions of the smartphone and the LSR at 12 months post-implementation. Results: Due to dropout or loss of contact, 394 out of 400 individuals completed the study. At the end of the study, 52 devices were lost or unusable. Prior to the intervention, participants reported being comfortable using technology. Perceptions of the MHEN technologies and their functions were generally positive. Positive perceptions of the smartphone increased over time (P=.002), while positive perceptions of the LSR decreased over time (P<.001). Conclusions: Quantitative and qualitative findings from this analysis demonstrated that these technologies positively impacted the lives of individuals experiencing severe mental illnesses and dispeled some of the myths regarding retention of technology among marginalized populations. This secondary analysis supported the acceptability of using mental health technologies within this population and provided considerations for future development. Trial Registration: ClinicalTrials.gov NCT01473550; http://clinicaltrials.gov/show/NCT01473550 (Archived by WebCite at http://www.webcitation.org/6SLNcoKb8). ", doi="10.2196/mental.3926", url="http://mental.jmir.org/2015/1/e1/", url="http://www.ncbi.nlm.nih.gov/pubmed/26543906" }