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Journal Description

JMIR Mental Health (JMH, ISSN 2368-7959) is a PubMed-indexed, peer-reviewed sister journal of JMIR, the leading eHealth journal by Impact Factor.

JMIR Mental Health focusses on digital health and Internet interventions, technologies and electronic innovations (software and hardware) for mental health, addictions, online counselling and behaviour change. This includes formative evaluation and system descriptions, theoretical papers, review papers, viewpoint/vision papers, and rigorous evaluations.

JMIR Mental Health publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research

JMIR Mental Health features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs. The journal is indexed in PubMed, PubMed Central, and ESCI (Emerging Sources Citation Index).

JMIR Mental Health adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics.

 

Recent Articles:

  • Two men playing video games. Source: Flickr; Copyright: Patrick Brosset; URL: https://www.flickr.com/photos/gnackgnackgnack/3245297998/; License: Creative Commons Attribution + Noncommercial (CC-BY-NC).

    Gender Moderates the Partial Mediation of Impulsivity in the Relationship Between Psychiatric Distress and Problematic Online Gaming: Online Survey

    Abstract:

    Background: Research has shown that some individuals can develop problematic patterns of online gaming, leading to significant psychological and interpersonal problems. Psychiatric distress and impulsivity have been suggested to contribute to problematic online gaming (POG). Objective: This study aimed to investigate the potential mediating or moderating mechanisms of impulsivity and gender-related differences in possible associations between psychiatric distress and POG. Methods: A total of 596 matched female and male participants, ranging in age from 14 to 38 years (mean 21.4, SD 4.5), were chosen from a large cross-sectional, nationwide Hungarian online gaming sample. Participants completed online questionnaires about self-reported impulsivity, psychiatric distress, and POG. Results: Psychiatric distress directly predicted POG, and impulsivity partially mediated the relationship between psychiatric distress and POG. However, this mediation effect was found only for the impatience factor of impulsivity. Impulsivity did not moderate the relationship between psychiatric distress and POG. A moderating effect of gender was not found in the direct relationship between psychiatric distress and POG. However, a moderated mediation analysis revealed that impatience mediated the association between psychiatric distress and POG in males, whereas the indirect effect of impatience was not significant in females. Conclusions: The results of this work highlight gender-related difference among online gamers in the mediation effect of impulsivity between psychiatric distress and POG and provide novel insights regarding clinical implications for preventing or treating POG.

  • Person who has to take many pills taking pills. Source: Pixabay; Copyright: Pixabay; URL: https://pixabay.com/photos/medications-cure-tablets-pharmacy-257344/; License: Public Domain (CC0).

    Technological Interventions for Medication Adherence in Adult Mental Health and Substance Use Disorders: A Systematic Review

    Abstract:

    Background: Medication adherence is critical to the effectiveness of psychopharmacologic therapy. Psychiatric disorders present special adherence considerations, notably an altered capacity for decision making and the increased street value of controlled substances. A wide range of interventions designed to improve adherence in mental health and substance use disorders have been studied; recently, many have incorporated information technology (eg, mobile phone apps, electronic pill dispensers, and telehealth). Many intervention components have been studied across different disorders. Furthermore, many interventions incorporate multiple components, making it difficult to evaluate the effect of individual components in isolation. Objective: The aim of this study was to conduct a systematic scoping review to develop a literature-driven, transdiagnostic taxonomic framework of technology-based medication adherence intervention and measurement components used in mental health and substance use disorders. Methods: This review was conducted based on a published protocol (PROSPERO: CRD42018067902) in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses systematic review guidelines. We searched 7 electronic databases: MEDLINE, EMBASE, PsycINFO, the Cochrane Central Register of Controlled Trials, Web of Science, Engineering Village, and ClinicalTrials.gov from January 2000 to September 2018. Overall, 2 reviewers independently conducted title and abstract screens, full-text screens, and data extraction. We included all studies that evaluate populations or individuals with a mental health or substance use disorder and contain at least 1 technology-delivered component (eg, website, mobile phone app, biosensor, or algorithm) designed to improve medication adherence or the measurement thereof. Given the wide variety of studied interventions, populations, and outcomes, we did not conduct a risk of bias assessment or quantitative meta-analysis. We developed a taxonomic framework for intervention classification and applied it to multicomponent interventions across mental health disorders. Results: The initial search identified 21,749 results; after screening, 127 included studies remained (Cohen kappa: 0.8, 95% CI 0.72-0.87). Major intervention component categories include reminders, support messages, social support engagement, care team contact capabilities, data feedback, psychoeducation, adherence-based psychotherapy, remote care delivery, secure medication storage, and contingency management. Adherence measurement components include self-reports, remote direct visualization, fully automated computer vision algorithms, biosensors, smart pill bottles, ingestible sensors, pill counts, and utilization measures. Intervention modalities include short messaging service, mobile phone apps, websites, and interactive voice response. We provide graphical representations of intervention component categories and an element-wise breakdown of multicomponent interventions. Conclusions: Many technology-based medication adherence and monitoring interventions have been studied across psychiatric disease contexts. Interventions that are useful in one psychiatric disorder may be useful in other disorders, and further research is necessary to elucidate the specific effects of individual intervention components. Our framework is directly developed from the substance use disorder and mental health treatment literature and allows for transdiagnostic comparisons and an organized conceptual mapping of interventions.

  • Source: Pixabay; Copyright: HammerandTusk; URL: https://pixabay.com/en/man-virtual-reality-samsung-gear-vr-1416140/; License: Licensed by JMIR.

    Believing Is Seeing: A Proof-of-Concept Semiexperimental Study on Using Mobile Virtual Reality to Boost the Effects of Interpretation Bias Modification for...

    Abstract:

    Background: Cognitive Bias Modification of Interpretations (CBM-I) is a computerized intervention designed to change negatively biased interpretations of ambiguous information, which underlie and reinforce anxiety. The repetitive and monotonous features of CBM-I can negatively impact training adherence and learning processes. Objective: This proof-of-concept study aimed to examine whether performing a CBM-I training using mobile virtual reality technology (virtual reality Cognitive Bias Modification of Interpretations [VR-CBM-I]) improves training experience and effectiveness. Methods: A total of 42 students high in trait anxiety completed 1 session of either VR-CBM-I or standard CBM-I training for performance anxiety. Participants’ feelings of immersion and presence, emotional reactivity to a stressor, and changes in interpretation bias and state anxiety, were assessed. Results: The VR-CBM-I resulted in greater feelings of presence (P<.001, d=1.47) and immersion (P<.001, ηp2=0.74) in the training scenarios and outperformed the standard training in effects on state anxiety (P<.001, ηp2=0.3) and emotional reactivity to a stressor (P=.03, ηp2=0.12). Both training varieties successfully increased the endorsement of positive interpretations (P<.001, drepeated measures [drm]=0.79) and decreased negative ones. (P<.001, drm=0.72). In addition, changes in the emotional outcomes were correlated with greater feelings of immersion and presence. Conclusions: This study provided first evidence that (1) the putative working principles underlying CBM-I trainings can be translated into a virtual environment and (2) virtual reality holds promise as a tool to boost the effects of CMB-I training for highly anxious individuals while increasing users’ experience with the training application.

  • Source: Unsplash; Copyright: rawpixel; URL: https://unsplash.com/photos/pVgRgKvsWxU; License: Licensed by the authors.

    Use of Mobile and Computer Devices to Support Recovery in People With Serious Mental Illness: Survey Study

    Abstract:

    Background: Mental health recovery refers to an individual’s experience of gaining a sense of personal control, striving towards one’s life goals, and meeting one’s needs. Although people with serious mental illness own and use electronic devices for general purposes, knowledge of their current use and interest in future use for supporting mental health recovery remains limited. Objective: This study aimed to identify smartphone, tablet, and computer apps that mental health service recipients use and want to use to support their recovery. Methods: In this pilot study, we surveyed a convenience sample of 63 mental health service recipients with serious mental illness. The survey assessed current use and interest in mobile and computer devices to support recovery. Results: Listening to music (60%), accessing the internet (59%), calling (59%), and texting (54%) people were the top functions currently used by participants on their device to support their recovery. Participants expressed interest in learning how to use apps for anxiety/stress management (45%), mood management (45%), monitoring mental health symptoms (43%), cognitive behavioral therapy (40%), sleep (38%), and dialectical behavior therapy (38%) to support their recovery. Conclusions: Mental health service recipients currently use general functions such as listening to music and calling friends to support recovery. Nevertheless, they reported interest in trying more specific illness-management apps.

  • m-RESIST project. Source: The Authors; Copyright: m-RESIST consortium; URL: https://www.mresist.eu/; License: Public Domain (CC0).

    Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review

    Abstract:

    Background: Mobile Therapeutic Attention for Patients with Treatment-Resistant Schizophrenia (m-RESIST) is an EU Horizon 2020-funded project aimed at designing and validating an innovative therapeutic program for treatment-resistant schizophrenia. The program exploits information from mobile phones and wearable sensors for behavioral tracking to support intervention administration. Objective: To systematically review original studies on sensor-based mHealth apps aimed at uncovering associations between sensor data and symptoms of psychiatric disorders in order to support the m-RESIST approach to assess effectiveness of behavioral monitoring in therapy. Methods: A systematic review of the English-language literature, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was performed through Scopus, PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials databases. Studies published between September 1, 2009, and September 30, 2018, were selected. Boolean search operators with an iterative combination of search terms were applied. Results: Studies reporting quantitative information on data collected from mobile use and/or wearable sensors, and where that information was associated with clinical outcomes, were included. A total of 35 studies were identified; most of them investigated bipolar disorders, depression, depression symptoms, stress, and symptoms of stress, while only a few studies addressed persons with schizophrenia. The data from sensors were associated with symptoms of schizophrenia, bipolar disorders, and depression. Conclusions: Although the data from sensors demonstrated an association with the symptoms of schizophrenia, bipolar disorders, and depression, their usability in clinical settings to support therapeutic intervention is not yet fully assessed and needs to be scrutinized more thoroughly.

  • Source: The Authors; Copyright: The Authors; URL: http://mental.jmir.org/2019/2/e10186/; License: Public Domain (CC0).

    Identifying Behaviors Predicting Early Morning Emotions by Observing Permanent Supportive Housing Residents: An Ecological Momentary Assessment

    Abstract:

    Background: Behavior and emotions are closely intertwined. The relationship between behavior and emotions might be particularly important in populations of underserved people, such as people with physical or mental health issues. We used ecological momentary assessment (EMA) to examine the relationship between emotional state and other characteristics among people with a history of chronic homelessness who were participating in a health coaching program. Objective: The goal of this study was to identify relationships between daily emotional states (valence and arousal) shortly after waking and behavioral variables such as physical activity, diet, social interaction, medication compliance, and tobacco usage the prior day, controlling for demographic characteristics. Methods: Participants in m.chat, a technology-assisted health coaching program, were recruited from housing agencies in Fort Worth, Texas, United States. All participants had a history of chronic homelessness and reported at least one mental health condition. We asked a subset of participants to complete daily EMAs of emotions and other behaviors. From the circumplex model of affect, the EMA included 9 questions related to the current emotional state of the participant (happy, frustrated, sad, worried, restless, excited, calm, bored, and sluggish). The responses were used to calculate two composite scores for valence and arousal. Results: Nonwhites reported higher scores for both valence and arousal, but not at a statistically significant level after correcting for multiple testing. Among momentary predictors, greater time spent in one-on-one interactions, greater time spent in physical activities, a greater number of servings of fruits and vegetables, greater time spent interacting in a one-on-one setting as well as adherence to prescribed medication the previous day were generally associated with higher scores for both valence and arousal, and statistical significance was achieved in most cases. Number of cigarettes smoked the previous day was generally associated with lower scores on both valence and arousal, although statistical significance was achieved for valence only when correcting for multiple testing. Conclusions: This study provides an important glimpse into factors that predict morning emotions among people with mental health issues and a history of chronic homelessness. Behaviors considered to be positive (eg, physical activity and consumption of fruits and vegetables) generally enhanced positive affect and restrained negative affect the following morning. The opposite was true for behaviors such as smoking, which are considered to be negative.

  • Head Mounted Displays. Source: Image created by the authors; Copyright: The Authors; License: Creative Commons Attribution (CC-BY).

    Recommendations for Methodology of Virtual Reality Clinical Trials in Health Care by an International Working Group: Iterative Study

    Abstract:

    Background: Therapeutic virtual reality (VR) has emerged as an efficacious treatment modality for a wide range of health conditions. However, despite encouraging outcomes from early stage research, a consensus for the best way to develop and evaluate VR treatments within a scientific framework is needed. Objective: We aimed to develop a methodological framework with input from an international working group in order to guide the design, implementation, analysis, interpretation, and communication of trials that develop and test VR treatments. Methods: A group of 21 international experts was recruited based on their contributions to the VR literature. The resulting Virtual Reality Clinical Outcomes Research Experts held iterative meetings to seek consensus on best practices for the development and testing of VR treatments. Results: The interactions were transcribed, and key themes were identified to develop a scientific framework in order to support best practices in methodology of clinical VR trials. Using the Food and Drug Administration Phase I-III pharmacotherapy model as guidance, a framework emerged to support three phases of VR clinical study designs—VR1, VR2, and VR3. VR1 studies focus on content development by working with patients and providers through the principles of human-centered design. VR2 trials conduct early testing with a focus on feasibility, acceptability, tolerability, and initial clinical efficacy. VR3 trials are randomized, controlled studies that evaluate efficacy against a control condition. Best practice recommendations for each trial were provided. Conclusions: Patients, providers, payers, and regulators should consider this best practice framework when assessing the validity of VR treatments.

  • Source: Freepik; Copyright: Freepik; URL: https://www.freepik.com/free-photo/young-woman-lying-on-bed-using-mobile-phone_3251278.htm#term=depression%20phone&page=1&position=4; License: Licensed by JMIR.

    Adoption of Mobile Apps for Depression and Anxiety: Cross-Sectional Survey Study on Patient Interest and Barriers to Engagement

    Abstract:

    Background: Emerging research suggests that mobile apps can be used to effectively treat common mental illnesses like depression and anxiety. Despite promising efficacy results and ease of access to these interventions, adoption of mobile health (mHealth; mobile device–delivered) interventions for mental illness has been limited. More insight into patients’ perspectives on mHealth interventions is required to create effective implementation strategies and to adapt existing interventions to facilitate higher rates of adoption. Objective: The aim of this study was to examine, from the patient perspective, current use and factors that may impact the use of mHealth interventions for mental illness. Methods: This was a cross-sectional survey study of veterans who had attended an appointment at a single Veterans Health Administration facility in early 2016 that was associated with one of the following mental health concerns: unipolar depression, any anxiety disorder, or posttraumatic stress disorder. We used the Veteran Affairs Corporate Data Warehouse to create subsets of eligible participants demographically stratified by gender (male or female) and minority status (white or nonwhite). From each subset, 100 participants were selected at random and mailed a paper survey with items addressing the demographics, overall health, mental health, technology ownership or use, interest in mobile app interventions for mental illness, reasons for use or nonuse, and interest in specific features of mobile apps for mental illness. Results: Of the 400 potential participants, 149 (37.3%, 149/400) completed and returned a survey. Most participants (79.9%, 119/149) reported that they owned a smart device and that they use apps in general (71.1%, 106/149). Most participants (73.1%, 87/149) reported interest in using an app for mental illness, but only 10.7% (16/149) had done so. Paired samples t tests indicated that ratings of interest in using an app recommended by a clinician were significantly greater than general interest ratings and even greater when the recommending clinician was a specialty mental health provider. The most frequent concerns related to using an app for mental illness were lacking proof of efficacy (71.8%, 107/149), concerns about data privacy (59.1%, 88/149), and not knowing where to find such an app (51.0%, 76/149). Participants expressed interest in a number of app features with particularly high-interest ratings for context-sensitive apps (85.2%, 127/149), and apps focused on the following areas: increasing exercise (75.8%, 113/149), improving sleep (73.2%, 109/149), changing negative thinking (70.5%, 105/149), and increasing involvement in activities (67.1%, 100/149). Conclusions: Most respondents had access to devices to use mobile apps for mental illness, already used apps for other purposes, and were interested in mobile apps for mental illness. Key factors that may improve adoption include provider endorsement, greater publicity of efficacious apps, and clear messaging about efficacy and privacy of information. Finally, multifaceted apps that address a range of concerns, from sleep to negative thought patterns, may be best received.

  • Source: Freepik; Copyright: Freepik; URL: https://www.freepik.com/free-photo/man-browsing-laptop-near-sleeping-wife_1935495.htm#term=bed%20laptop&page=19&position=9; License: Licensed by JMIR.

    Sexual Desire, Mood, Attachment Style, Impulsivity, and Self-Esteem as Predictive Factors for Addictive Cybersex

    Abstract:

    Background: An increasing number of studies are concerned with various aspects of cybersex addiction, the difficulty some persons have in limiting cybersex use despite a negative impact on everyday life. Objective: The aim of this study was to assess potential links between the outcome variable cybersex addiction, assessed with the Compulsive Internet Use Scale (CIUS) adapted for cybersex use, and several psychological and psychopathological factors, including sexual desire, mood, attachment style, impulsivity, and self-esteem, by taking into account the age, sex, and sexual orientation of cybersex users. Methods: A Web-based survey was conducted in which participants were assessed for sociodemographic variables and with the following instruments: CIUS adapted for cybersex use, Sexual Desire Inventory, and Short Depression-Happiness Scale. Moreover, attachment style was assessed with the Experiences in Close Relationships-Revised questionnaire (Anxiety and Avoidance subscales). Impulsivity was measured by using the Urgency, Premeditation (lack of), Perseverance (lack of), Sensation Seeking, Positive Urgency Impulsive Behavior Scale. Global self-esteem was assessed with the 1-item Self-Esteem Scale. Results: A sample of 145 subjects completed the study. Addictive cybersex use was associated with higher levels of sexual desire, depressive mood, avoidant attachment style, and male gender but not with impulsivity. Conclusions: Addictive cybersex use is a function of sexual desire, depressive mood, and avoidant attachment.

  • One group using a cognitive training app and the other using a mindfulness training app. Source: The Authors; Copyright: The Authors; URL: http://mental.jmir.org/2019/1/e10844/; License: Creative Commons Attribution (CC-BY).

    Effects of a Mindfulness Meditation App on Subjective Well-Being: Active Randomized Controlled Trial and Experience Sampling Study

    Abstract:

    Background: Mindfulness training (MT) includes a variety of contemplative practices aimed at promoting intentional awareness of experience, coupled with attitudes of nonjudgment and curiosity. Following the success of 8-week, manualized group interventions, MT has been implemented in a variety of modalities, including smartphone apps that seek to replicate the success of group interventions. However, although smartphone apps are scalable and accessible to a wider swath of population, their benefits remain largely untested. Objective: This study aimed to investigate a newly developed MT app called Wildflowers, which was codeveloped with the laboratory for use in mindfulness research. It was hypothesized that 3 weeks of MT through this app would improve subjective well-being, attentional control, and interoceptive integration, albeit with weaker effects than those published in the 8 week, manualized group intervention literature. Methods: Undergraduate students completed 3 weeks of MT with Wildflowers (n=45) or 3 weeks of cognitive training with a game called 2048 (n=41). State training effects were assessed through pre- and postsession ratings of current mood, stress level, and heart rate. Trait training effects were assessed through pre- and postintervention questionnaires canvassing subjective well-being and behavioral task measures of attentional control and interoceptive integration. State and trait training data were analyzed in a multilevel model using emergent latent factors (acceptance, awareness, and openness) to summarize the trait questionnaire battery. Results: Analyses revealed both state and trait effects specific to MT; participants engaging in MT demonstrated improved mood (r=.14) and a reduction of stress (r=−.13) immediately after each training session compared with before the training session and decreased postsession stress over 3 weeks (r=−.08). In addition, MT relative to cognitive training resulted in greater improvements in attentional control (r=−.24). Interestingly, both groups demonstrated increased subjective ratings of awareness (r=.28) and acceptance (r=.23) from pre- to postintervention, with greater changes in acceptance for the MT group trending (r=.21). Conclusions: MT, using a smartphone app, may provide immediate effects on mood and stress while also providing long-term benefits for attentional control. Although further investigation is warranted, there is evidence that with continued usage, MT via a smartphone app may provide long-term benefits in changing how one relates to their inner and outer experiences. Trial Registration: ClinicalTrials.gov NCT03783793; https://clinicaltrials.gov/ct2/show/NCT03783793 (Archived by WebCite at http://www.webcitation.org/75EF2ehst)

  • Source: Pexels; Copyright: rawpixel.com; URL: https://www.pexels.com/photo/person-holding-pen-writing-on-daily-report-schedule-paper-1549001/; License: Licensed by JMIR.

    Web-Based Measure of Life Events Using Computerized Life Events and Assessment Record (CLEAR): Preliminary Cross-Sectional Study of Reliability, Validity,...

    Abstract:

    Background: Given the criticisms of life event checklists and the costs associated with interviews, life event research requires a sophisticated but easy-to-use measure for research and clinical practice. Therefore, the Computerized Life Events and Assessment Record (CLEAR), based on the Life Events and Difficulties Schedule (LEDS), was developed. Objective: The objective of our study was to test CLEAR’s reliability, validity, and association with depression. Methods: CLEAR, the General Health Questionnaire, and the List of Threatening Experiences Questionnaire (LTE-Q) were completed by 328 participants (126 students; 202 matched midlife sample: 127 unaffected controls, 75 recurrent depression cases). Test-retest reliability over 3-4 weeks was examined and validity determined by comparing CLEAR with LEDS and LTE-Q. Both CLEAR and LTE-Q were examined in relation to depression. Results: CLEAR demonstrated good test-retest reliability for the overall number of life events (0.89) and severe life events (.60). Long-term problems showed similar findings. In terms of validity, CLEAR severe life events had moderate sensitivity (59.1%) and specificity (65.4%) when compared with LEDS. CLEAR demonstrated moderate sensitivity (43.1%) and specificity (78.6%) when compared with LTE-Q. CLEAR severe life events and long-term problems were significantly associated with depression (odds ratio, OR 3.50, 95% CI 2.10 to 5.85, P<.001; OR 3.38, 95% CI 2.02 to 5.67, P<.001, respectively), whereas LTE-Q events were not (OR 1.06, 95% CI 0.43 to 2.60, P=.90). Conclusions: CLEAR has acceptable reliability and validity and predicts depression. It, therefore, has great potential for effective use in research and clinical practice identifying stress-related factors for the onset and maintenance of depression and related disorders.

  • Source: iStock by Getty Images; Copyright: verbaska_studio; URL: https://www.istockphoto.com/ca/photo/face-to-face-online-psychotherapy-session-gm518410972-90025345; License: Licensed by the authors.

    Internet-Based Interventions for Problem Gambling: Scoping Review

    Abstract:

    Background: This study seeks to give an overview of academic research on internet-based interventions that are used to address problem gambling. The rate of treatment seeking has been demonstrated to be low across several research environments. This is in part because of the systemic barriers that treatment seekers face to accessing traditional face-to-face treatment. Making treatment resources for problem gambling available through the internet is one way to reduce the impact of those systemic barriers. The use of internet-based resources to address problem gambling has been growing, and a field of research evaluating it has developed as well. However, little has been done to summarize this collection of research. Objective: This study aimed to provide a scoping review of the use of internet-based interventions for problem gambling treatment and prevention to provide an understanding of the current state of the field. Methods: A scoping review was performed for 6 peer-reviewed research databases (Web of Science, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, MEDLINE, Social Science Abstracts, and Scopus) and 3 gray literature databases (MedEdPortal, Proquest: Dissertations, and OpenGrey). Article inclusion criteria were as follows: published over the 10-year period of 2007 to 2017, including an intervention for problem gambling, and involving the use of internet to deliver that intervention. Results: A total of 27 articles were found that met the review criteria. Studies were found from several different areas, with particularly strong representation for Australia, New Zealand, and Scandinavia. Cognitive behavioral therapy was the most common form of internet-based intervention. Internet-based interventions were generally shown to be effective in reducing problem gambling scores and gambling behaviors. A wide range of interventions that made use of internet resources included text-based interactions with counselors and peers, automated personalized and normative feedback on gambling behaviors, and interactive cognitive behavioral therapies. A lack of diversity in samples, little comparison with face-to-face interventions, and issues of changes in the treatment dynamic are identified as areas that require further investigation. Conclusions: Internet-based interventions are a promising direction for treatment and prevention of problem gambling, particularly in reducing barriers to accessing professional help. The state of the current literature is sparse, and more research is needed for directly comparing internet-based interventions and their traditional counterparts.

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  • Predicting Risk of Post-Traumatic Stress Disorder Symptomology Using Machine Learning

    Date Submitted: Mar 8, 2019

    Open Peer Review Period: Mar 12, 2019 - May 7, 2019

    Background: The majority of adults in the US will be exposed to a potentially traumatic event, but only a handful will go on to develop impairing mental health conditions such as Post-traumatic Stress...

    Background: The majority of adults in the US will be exposed to a potentially traumatic event, but only a handful will go on to develop impairing mental health conditions such as Post-traumatic Stress Disorder (PTSD). Objective: Identifying those at elevated risk shortly after trauma exposure is a clinical challenge. We aim to develop computational methods to more effectively identify at-risk patients, and thereby support better early interventions. Methods: We propose machine learning (ML) induction of models to automatically predict elevated PTSD symptoms in patients one month after a trauma, using self-reported symptoms from data collected via smartphones. Results: We show that an ensemble model accurately predicts elevated PTSD symptoms, with an AUC of 0.85, using a bag of SVM, Naïve Bayes, logistic regression, and random forest algorithms. Furthermore, we show that only 7 self-report items (features) are needed to obtain this AUC. Most importantly, we show that accurate predictions can be made after 10-20 days post trauma. Conclusions: These results suggest that simple smartphone-based patient surveys, coupled with automated analysis using ML-trained models, can identify those at risk for developing elevated PTSD symptoms and thus target them for early intervention.

  • Social Anxiety Management through Digital Manipulation of Faces: Two Crowdsourced Studies and One Gaze-Tracking Experiment

    Date Submitted: Mar 5, 2019

    Open Peer Review Period: Mar 5, 2019 - Apr 30, 2019

    Background: Augmented reality (AR) and mixed reality offer novel opportunities for digital intervention design to manage social anxiety; for example, faces can be manipulated in real-time to help peop...

    Background: Augmented reality (AR) and mixed reality offer novel opportunities for digital intervention design to manage social anxiety; for example, faces can be manipulated in real-time to help people avoid fixating on threatening faces and instead orient toward happy ones. However, because an intervention design using face manipulation will be based on underlying scientific models of anxiety and not be a digitization of existing therapies, preliminary research is needed to determine if face manipulation is an effective approach. Objective: To determine: Exp 1) if digitally manipulating angry expressions reduces their threat; Exp 2) if people orient faster to augmented happy faces and if these hold their attention longer; Exp 3) if digitally manipulating faces reduces anxiety after exposure to them and increases resilience to a subsequent stressor. Methods: We reduced the negativity of angry expressions by either obfuscating the eyes through digitally-added sunglasses or by blurring the entire face. We directed attention to positive faces either by adding particle effects around the face that leveraged motion to draw attention or through comical digitally-added features, similar to a SnapchatTM filter. Exp 1) We had participants (n=33) rate unfiltered and augmented faces for arousal, valence, happiness, and anger in an online study. Exp 2) We tested how long participants (n=20) took to orient toward augmented faces (compared to unfiltered) and how long they dwelled on them in a laboratory-based gaze-tracking study. Exp 3) We identified how exposure to augmented faces affected anxiety (compared to a control condition) and response to a subsequent stressor (n=226). Results: Exp 1) Ratings for arousal and anger were lower for blurred images (Parousal<.001; Panger<.001) and when sunglasses were added (Parousal =.04; Panger <.001). Exp 2) Augmenting images decreased time to first fixation (P<.001) and increased fixation duration (P<.001), regardless of whether particle effects or comic filters were used (Porient=.12, Pfixate=.17). Exp 3) After exposure to faces, blurring angry faces reduced state anxiety (P=.015). After exposure to a subsequent stressor, blurring angry faces reduced experienced negative affect (P=.03). Conclusions: Blurring negative facial expressions and simultaneously directing attention to positive ones with motion particles was the most effective approach at reducing anxiety after a brief exposure in a face-viewing task. These results can inform the design of novel AR-based digital interventions for anxiety that manipulates faces based on a model of threat processing. Clinical Trial: N/A.

  • The Internet-based Cognitive Assessment Tool: System Design and Feasibility Study

    Date Submitted: Mar 4, 2019

    Open Peer Review Period: Mar 4, 2019 - Apr 29, 2019

    Background: Persistent cognitive impairment is prevalent in unipolar and bipolar disorders and is associated with decreased quality of life and psychosocial dysfunction. However, there is no digital c...

    Background: Persistent cognitive impairment is prevalent in unipolar and bipolar disorders and is associated with decreased quality of life and psychosocial dysfunction. However, there is no digital cognitive screening tool for brief and accurate assessment of cognitive impairments in patients with these affective disorders. The Screen for Cognitive Impairment in Psychiatry (SCIP) test is a validated, short paper-and-pencil instrument for assessment of cognition in affective disorders. Objective: To present the design, implementation, and feasibility study of the Internet-based Cognitive Assessment Tool (ICAT) as a web-based cognitive test battery designed based on the SCIP cognitive tasks. The aim of the feasibility study in this early stage was three-folded; among healthy individuals (i) to evaluate the usability of ICAT, (ii) to investigate the feasibility of ICAT as a patient-administered cognitive assessment tool, and (iii) to examine the performance of automatic speech recognition (ASR) for assessment of cognitive function. Methods: ICAT was developed in a user-centered design process. The final implementation of ICAT was a web-based tool involving five short cognitive tasks modified from the SCIP to assess immediate and delayed recall, working memory, executive skills, and psychomotor speed. Usability and feasibility studies were conducted with two groups of healthy individuals (N=21 and N=19, respectively). Tests were done for Danish as well as English speaking participants. Each participant of the feasibility study first performed the Danish version of the SCIP test (SCIP-D), and then did the ICAT. Think-aloud method was used during both studies and the participants were asked to fill in the Post-Study System Usability Questionnaire (PSSUQ) upon completing the ICAT. Verbal recall in ICAT was assessed using ASR and performance evaluation criteria was word error rate (WER). Pearson’s two-tailed correlation analysis significant at 0.05 level was applied to investigate the association between SCIP and ICAT total and sub-test scores. Results: The psychometric factors of PSSUQ gave scores above 4 (out of 5). Overall, the analysis of the feasibility study revealed moderate to strong correlation between the total scores of SCIP and ICAT (r = 0.63, P= 0.009). There were also moderate to strong correlations between the SCIP and ICAT sub-tests for immediate verbal recall (r=0.67, P=0.002) and psychomotor speed (r=0.71, P=0.001). The associations between the respective sub-tests for working memory, psychomotor speed and delayed recall, however, were not statistically significant. The corresponding WER for English and Danish responses were 17.8% and 6.3%. Conclusions: ICAT is the first digital patient-administered screening instrument modified from the SCIP using web-based technology and ASR. The usability ratings revealed that healthy participants found ICAT easy to use. The moderate correlation between the ICAT and SCIP scores suggests that ICAT is a valid tool to assess cognition, although this should be confirmed in a larger study with greater statistical power. There was good accuracy of the ASR for verbal memory assessment. Taken together, the ICAT seems to be a valid online cognitive assessment tool which after some minor modifications and further validation may be used to screen for cognitive impairment in clinical settings.

  • An Immersive VR Platform for Assessing Spatial Navigation Memory in pre-dementia Screening: A Study of Feasibility and Usability

    Date Submitted: Mar 2, 2019

    Open Peer Review Period: Mar 4, 2019 - Apr 29, 2019

    Background: Traditional methods for assessing memory are expensive and have high administrative costs. Memory assessment is important for establishing cognitive impairment in cases such as detecting d...

    Background: Traditional methods for assessing memory are expensive and have high administrative costs. Memory assessment is important for establishing cognitive impairment in cases such as detecting dementia in older adults. Technology can assist in better quality outcome in such crucial screening, by supporting the wellbeing of individuals and offering them an engaging, cognitively challenging task, that is not stressful. However, unmet user needs can compromise the validity of the outcome. Therefore, screening technology, particularly for older adults, must address their specific design and usability requirements. Objective: The objective of this research was to design and evaluate the feasibility of an immersive Virtual Reality (VR) platform to assess spatial navigation memory in older adults and establish its compatibility by comparing the outcome to a standard screening platform on computer PC. Methods: VR-CogAssess, is a platform integrating an Oculus Rift Head Mounted Display (HMD) and immersive photo-realistic imagery. In a pilot study with healthy older adults (N = 42, age M(SD) = 73.22(9.26)) a landmark recall test was conducted and assessment on the VR-CogAssess was compared against a Standard PC (SPC) setup. Results: Results showed participants in VR were more engaged (p = .003), achieved higher landmarks recall scores (p = .004), made less navigational mistakes (p = .042) and reported a higher level of presence (p = .002). Conclusions: The study findings suggest immersive VR is feasible and compatible with SPC counterpart for spatial navigation memory assessment. The study provides a set of design guidelines for creating similar platforms in the future.

  • How the persuasive systems design features of Internet-based cognitive behavioural therapy programs may reduce symptoms for children and adolescents with anxiety: A realist synthesis

    Date Submitted: Feb 25, 2019

    Open Peer Review Period: Feb 28, 2019 - Apr 25, 2019

    Background: Internet-based cognitive behavioural therapy (iCBT) for children and adolescents is a ‘persuasive system’ in that it combines 3 major components to therapy—therapeutic content, techn...

    Background: Internet-based cognitive behavioural therapy (iCBT) for children and adolescents is a ‘persuasive system’ in that it combines 3 major components to therapy—therapeutic content, technological features and interactions between the user and program—to reduce users’ anxiety symptoms. Several reviews report the effectiveness of iCBT; however, iCBT design and delivery components differ widely across programs raising important questions about how iCBT effects are produced and can be optimized. One approach to addressing these questions involves examining the persuasive design features of iCBT programs. Objective: We conducted a realist synthesis of iCBT literature using a persuasive system perspective to: (i) document the design and delivery components of iCBT, and (ii) explore how these components may explain the change in anxiety symptoms after completing iCBT. Methods: A multi-strategy search identified published and gray literature on iCBT for child and adolescent anxiety up until November 2017. Documents that met our pre-specified inclusion criteria were appraised for relevance and methodological rigor. Data extraction was guided by the persuasive systems design (PSD) model. The model describes 28 technological design features, organized into 4 categories, that help users meet their health goals: Primary task support, Dialogue support, System credibility support, and Social support. We generated hypotheses for how PSD features (Mechanisms) and program delivery features (Context of use) were linked to symptom changes (Outcomes) across iCBT programs using realist and meta-ethnographic techniques. These hypothesized Context-Mechanism-Outcome configurations were refined during analysis using evidence from the literature to improve their explanatory value. Results: Forty-five documents detailing 12 iCBT programs were included. Six iCBT programs were rated ‘high’ for relevance and most studies were of moderate-to-high methodological rigor. Eleven Context-Mechanism-Outcome configurations were generated. Configurations were primarily comprised of PSD features from the Primary task and Dialogue support categories. Several key PSD features (Self-monitoring, Simulation, Social role, Similarity, Social learning, Rehearsal) were consistently reported in programs shown to reduce anxiety; many features were employed simultaneously, suggesting synergy in their grouping. The proposed functions of PSD features in iCBT impacts were also included in the configurations. Adjunct support was an important aspect of Context that may have complemented certain PSD features in reducing users’ anxiety. Conclusions: The Context-Mechanism-Outcome configurations we developed suggest that, when delivered with adjunct support, PSD features may contribute to symptom reductions for children and adolescents with anxiety. These findings provide an improved understanding of the function, combination and impacts of iCBT program components thought to support desired program effects. Formal testing of the 11 configurations is required to confirm their impact on anxiety-based outcomes. From this we encourage a systematic and deliberate approach to iCBT design and evaluation to increase the pool of evidence-based interventions available to prevent and treat child and adolescents with anxiety.

  • Using Ecological Momentary Assessment to Measure Mood Fluctuations during Drinking Episodes among Individuals with HIV

    Date Submitted: Feb 19, 2019

    Open Peer Review Period: Feb 22, 2019 - Apr 19, 2019

    Background: Individuals with HIV have high rates of mood disorders that have been noted to interrupt adherence care practices. Yet, intraday fluctuations in mood among these individuals are mostly unk...

    Background: Individuals with HIV have high rates of mood disorders that have been noted to interrupt adherence care practices. Yet, intraday fluctuations in mood among these individuals are mostly unknown. Objective: This study examined mood and alcohol use among a sample of individuals with HIV in their natural environments. Methods: This prospective 28-day pilot study enrolled 34 individuals engaged in HIV care. Mood was measured using the Positive and Negative Affect Scale-Short Form (PANAS-SF) and completed at the same moment of their alcohol consumption questionnaire. Descriptive and multilevel analyses aimed at identifying predictive patterns of mood changes in relation to alcohol use. Results: Among the 27 participants who completed the study with alcohol use reports, mood was measured at each of the 227 drinking episodes. The positive and negative affect scores ranged from 10 to 50, with a mean of 25.7 and 11.4 for each, respectively. There was significant reduction in mean positive mood scores from the start of the alcohol episode to the following day. Means for negative mood reports and fluctuation was low in this sample. Those that had a higher drinking pace overall were more likely to be in a worse mood at the end of the alcohol episode, regardless of the number of drinks consumed. Conclusions: This pilot study reveals the initial relationships between mood and alcohol use, namely reductions in positive mood after alcoholic drinks were consumed. These patterns suggest intervention opportunities, yet larger scale studies are likely to identify more significant opportunities for interventions.

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