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Internet interventions, technologies and digital innovations for mental health and behavior change
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.
Editorial Board members are currently being recruited, please contact us if you are interested (jmir.editorial.office at gmail.com).
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Background: Preoperative anxiety and depression are predominant risk factors for increased postoperative pain. Thoracic wall deformities in adolescents often cause low self-esteem, which contributes t...
Background: Preoperative anxiety and depression are predominant risk factors for increased postoperative pain. Thoracic wall deformities in adolescents often cause low self-esteem, which contributes to psychological concerns. Several studies have suggested a relationship between preoperative mental health treatment and enhanced recovery after surgery. Objective: This study investigated the validity of screening questionnaires concerning psychological trait and state characteristics via a patient-specific online platform. Methods: Patients scheduled for elective pectus surgery between June 2017 and August 2017 were invited to participate in clinical interviews and online self-report questionnaires. All patients were recruited in the Anesthesiology Department, Antwerp University Hospital, Belgium. This single-center observational cohort study was performed in accordance with the ethical standards of Good Clinical Practice guidelines (ICH-GCP) and the Declaration of Helsinki after obtaining study approval by the Institutional Review Board and Ethics Committee of the Antwerp University Hospital, Belgium (study identifier: 17/08/082). Patients with a history of a psychiatric disease, chronic opioid use (more than three months) or revision surgery were excluded. A preoperative psychological inventory was performed using the Rosenberg self-esteem scale (RSES), Hospital Anxiety and Depression Scale (HADs) and State-Trait Anxiety Inventory (STAI). The results were postoperatively compared with pain intensity and interference using the Multidisciplinary Pain Inventory (MPI), Coping Pain Questionnaire (CPQ) and numeric pain rating scale assessment (NRS). Results: Of the 22 patients, 21 used our web-based psychological perioperative screening platform. A “success” was reported by 85% of the patients for the smartphone application, 89% for individual online platform usability and 95% for accessibility. A total of 89% of the patients rated the effort of generating answers to the online questionnaire as low. The results from the completed questionnaires indicated a strong negative correlation between self-esteem and the anxiety trait (R = -0.72, p < 0.01) and overall anxiety characteristics (R = -0.49, p = 0.04). There was a positive correlation between depressive and anxiety characteristics and the anxiety trait (R = 0.52, p = 0.03; R = 0.6, p = 0.02, respectively). Moreover, preoperative anxiety was positively correlated with postoperative pain interference (R = 0.58, p = 0.02). Finally, there was a negative correlation between self-esteem and pain interference (R = -0.62, p = 0.01). Conclusions: Perioperative screening of psychological symptoms and trait characteristics with specific treatment, if necessary, could further improve postoperative pain and overall health status. Research on E-health technology, even for psychological patient care, is rapidly increasing. Clinical Trial: ClinicalTrials.gov NCT03100669
Background: Peer support groups for people with long-term mental health problems are at the heart of recovery-oriented approaches in mental health care. When conducted face-to-face (offline) or on the...
Background: Peer support groups for people with long-term mental health problems are at the heart of recovery-oriented approaches in mental health care. When conducted face-to-face (offline) or on the Internet (online), peer support groups have proven to have differing strengths and weaknesses. Little is known about the benefits and challenges of combining the two formats. Objective: The aim of this study was to gain insights into the benefits and challenges of combining online and offline peer support groups facilitated through an Internet intervention designed to support recovery processes. Methods: In this exploratory and descriptive study, an e-recovery portal called ReConnect was used by service users in two mental health communities in Norway for 6-12 months. The portal included an online peer support forum which also facilitated participation in local in-person ReConnect-cafés. Both formats of peer support were facilitated by an employed service user consultant with lived experience of mental health problems and with training in peer support. Qualitative data about service users’ experiences of using the portal were collected through focus groups and individual interviews and inductively analyzed thematically with focus on benefits and challenges of peer support online and offline. Results: A total of 14 service users 22-63 years of age with various diagnoses, receiving services at both primary and specialist levels of mental health care participated in three focus groups and 10 individual interviews. Two main themes were identified in the analysis: 1) balancing anonymity and openness, and 2) enabling connectedness. These themes are further illustrated with the subthemes: i) dilemmas of anonymity and confidentiality, ii) towards self-disclosure and openness, iii) new friendships, and iv) networks in the local community. Three of the subthemes mainly describe benefits. Challenges were more implicit and cut across the subthemes. Identified challenges were linked to transitions from anonymity to revealing one’s identity, how to protect confidentiality, or to participation at face-to-face meetings in the local community. Conclusions: Our study suggests that online peer support groups and offline meetings complement each other, and the combination is mainly beneficial to users. The identified benefits appeared to arise from participants’ options of one format or the other, or that they could combine formats in ways that suited their individual values and comfort zones. We also identified challenges related to combination of formats, and both formats require appropriate facilitation of peer support. Combining online formats that enable anonymity, a non-judgmental atmosphere, and 24/7 accessibility regardless of location, with offline formats that foster local, in-person community ties, is a promising concept for facilitating recovery-oriented care, and warrants continued research.
Background: Social isolation is associated with increased risk for mental and physical health problems. Older persons living with HIV (PLWH) are more socially isolated than their younger counterparts...
Background: Social isolation is associated with increased risk for mental and physical health problems. Older persons living with HIV (PLWH) are more socially isolated than their younger counterparts or older persons without HIV; however, little is known about factors related to engagement in social activity among older PLWH. Objective: To examine real-time relationships among social activity, mood, fatigue, and pain in a sample of older PLWH. Methods: Twenty older PLWH, recruited from UCSD’s HIV Neurobehavioral Research Program in 2016, completed smartphone-based ecological momentary assessment (EMA) surveys five times/day for one week. Participants reported current social activity (alone vs. not alone; number of social interactions), and levels of mood (sadness, happiness, stress), fatigue, and pain. Mixed-effects regression models were used to analyze concurrent and lagged associations among social activity, mood, fatigue, and pain. Results: Participants (mean age=58.8, SD=4.3) reported being alone 63% of time on average during waking hours. Being alone was related to lower concurrent happiness (b=-0.300; p=0.008). In lagged analyses, social activity predicted higher levels of fatigue later in the day (b=-1.089; p=0.002), and higher pain levels predicted being alone in the morning with a reduced likelihood of being alone as the day progressed (b=0.945; p=0.021). Conclusions: Use of EMA elucidated a high rate of time spent alone among older PLWH. Promoting social activity despite presence of pain or fatigue may improve happiness and psychological well-being in this population.
Background: Digital technology is increasingly being used to enhance healthcare in various areas of medicine. In the area of serious mental illness (SMI), it is important to understand the special cha...
Background: Digital technology is increasingly being used to enhance healthcare in various areas of medicine. In the area of serious mental illness (SMI), it is important to understand the special characteristics of target users that may influence motivation and competence to use digital health tools (DHTs), as well as the resources and training necessary for these patients to facilitate the use of this technology. Objective: To conduct a quantitative expert consensus survey to identify key characteristics of target users (patients and healthcare professionals [HCPs]), barriers and facilitators for appropriate use, and resources needed to optimize the use of DHTs in patients with SMI. Methods: A panel of 40 experts in digital behavioral health who met the participation criteria completed a 19-question survey rating predefined responses on a 9-point Likert scale. Consensus was determined using a chi-square test of score distributions across 3 ranges (1–3, 4–6, 7–9). Categorical ratings of first, second, or third line were designated based on the lowest category into which the confidence interval of the mean ratings fell, with a boundary >6.5 for first line. Here, we report experts’ responses to 9 questions (265 options) that focused on (1) user characteristics that would promote or hinder the use of DHTs, (2) potential benefits/motivators and barriers/unintended consequences of DHT use, and (3) support and training for patients and HCPs. Results: Among patient characteristics most likely to promote use of DHTs, experts endorsed interest in using state-of-the-art technology, availability of necessary resources, good occupational functioning, and perception of the tool as beneficial. Certain disease-associated signs and symptoms (eg, more severe symptoms, substance abuse problems, a chaotic living situation) were considered likely to make it difficult for patients to use DHTs. Enthusiasm among HCPs for DHTs and availability of staff and equipment to support their use were identified as variables to enable HCPs to successfully incorporate DHTs into their practices. The experts identified a number of potential benefits of and barriers to use of DHTs by patients and HCPs. Most experts agreed that both HCPs and patients would need to be trained in the use of these new technologies. Conclusions: These results provide guidance to the mental health field on how to optimize the development and deployment of DHTs for patients with SMI.
Background: Standardized measurement of aspects of physical and mental health is useful for screening and identification of health problems. Personalized feedback of the results of standardized measur...
Background: Standardized measurement of aspects of physical and mental health is useful for screening and identification of health problems. Personalized feedback of the results of standardized measurement can additionally influence health behavior. Treatment outcomes can be improved by monitoring feedback about health status over time. However, few resources are available that (i) are free for users, (ii) provide feedback from validated scales, and (iii) measure a wide range of health domains. Objective: Our goals were (i) to develop an internet self-assessment resource that met the criteria above and would also collect data that could be used to generate and test hypotheses about health, (ii) test its feasibility as a self-assessment and research tool, and (iii) describe the characteristics of its users. Methods: The Self-Assessment Kiosk was built using previously validated health measurement instruments and implemented on a commercial internet survey platform. Data regarding its usage and the characteristics of its users was collected over 54 weeks. The rate of accrual of new users, popularity of particular measurement domains, frequency with which multiple domains were selected for measurement and characteristics of users who chose particular questionnaires were assessed. Results: Of 1,435 visits, 570 users completed at least one measure and consented to research. Growth in the number of users over time was approximately linear. Users were skewed towards old age, higher income and higher education. More than half (55.2%) reported at least one medical condition. The median number of questionnaires completed on the first visit was four. The most commonly chosen questionnaires measured depression (61%), anxiety (60%), attachment insecurity (44%) and coping (41%). Depression and anxiety scores (both mean scores and proportion above a clinical cut-off) were intermediate between previously studied populations with and without mental illness. With respect to the sample size required to study relationships between specific domains, it was found that two to three times greater participant accrual was required for a three-variable study than for a single variable study. Conclusions: The value of the Self-Assessment Kiosk to users and the feasibility of providing this resource are supported by the steady accumulation of new users over its first year of availability in response to modest marketing. Completion of multiple measurement instruments will allow the Self-Assessment Kiosk database to be interrogated to understand the relationships between health variables. Users who select particular instruments tend to have scores that are higher than found in the general population, indicating that instruments are more likely to be selected when they are salient to users. Self-selection bias limits generalizability and needs to be taken into account when using the Self-Assessment Kiosk database as a research resource. Ethical issues that were considered in developing and implementing the Self-Assessment Kiosk are also discussed.
Background: Studies have shown that individuals with eating disorders (ED) often suffer from negative emotional arousal as well. Increasingly, studies have been utilizing social media as a tool to bet...
Background: Studies have shown that individuals with eating disorders (ED) often suffer from negative emotional arousal as well. Increasingly, studies have been utilizing social media as a tool to better understanding public health issues. Objective: The aim of the study was to explore whether Twitter users who show signs of ED also show signs of negative emotional states and can be identified by their tweets. Methods: Using the Twitter API, six pro-ED Twitter accounts were identified. Twenty-percent of account followers were randomly extracted and screened for ED-related content (N=2139). Tweets from identified followers were analyzed using LIWC and MALLET to test for signs of depression. Machine learning was used to build a model to classify individuals as having an eating disorder or not based on the language used in their Tweets. Results: Twitter users with ED mentioned terms related to negative emotions, anxiety, anger, and sadness significantly more often than non-ED Twitter users; they also mentioned terms related to positive emotion less often. It was found that word clusters formed by ED users’ tweets were related to negative arousal and self-harm. It was also determined that people with eating disorders can be accurately classified using machine learning (sensitivity: 0.89, specificity: 0.94, positive predictive value: 0.94, negative predictive value: 0.88). Conclusions: Users who show signs of ED on Twitter also show signs of negative emotions on Twitter, and models induced with machine learning can accurately differentiate those with eating disorders from those without.