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Journal Description

JMIR Mental Health (JMH, ISSN 2368-7959, Editor-in-Chief: John Torous MD MBI) is a premier SCI/PubMed/Scopus-indexed, peer-reviewed journal which has a unique focus on digital health/digital psychiatry/digital psychology/e-mental health, covering Internet/mobile interventions, technologies and electronic innovations (software and hardware) for mental health, including addictions, online counselling and behaviour change. This includes formative evaluation and system descriptions, theoretical papers, review papers, viewpoint/vision papers, and rigorous evaluations related to digital psychiatry, e-mental health, and clinical informatics in psychiatry/psychology. The main themes/topics covered by this journal can be found here.

JMIR Mental Health has an international author- and readership and welcomes submissions from around the world.

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 CentralSCIE (Science Citation Index Expanded)/WoS/JCR (Journal Citation Reports), and Scopus.


Recent Articles:

  • Source: Adobe Stock; Copyright: rocketclips; URL:; License: Licensed by JMIR.

    Engagement and Clinical Improvement Among Older Adult Primary Care Patients Using a Mobile Intervention for Depression and Anxiety: Case Studies


    Background: Technology-based mental health interventions are an increasingly attractive option for expanding access to mental health services within the primary care system. Older adults are among the groups that could potentially benefit from the growing ubiquity of technology-based mental health interventions; however, older adults are perceived to be averse to using technology and have reported barriers to use. Objective: The aim of this paper is to present a case study of 3 participants from a clinical trial evaluating IntelliCare, an evidence-based mobile intervention for depression and anxiety, among adults recruited from primary care clinics. Our report of these 3 participants, who were aged 60 years or older, focuses on their engagement with the IntelliCare service (ie, app use, coach communication) and clinical changes in depression or anxiety symptoms over the intervention period. Methods: The 3 case study participants were offered IntelliCare with coaching for 8 weeks. The intervention consisted of 5 treatment intervention apps that support a variety of psychological skills, a Hub app that contained psychoeducational content and administered weekly assessments, and coaching for encouragement, accountability, and technical assistance as needed. The 3 case study participants were selected to reflect the overall demographics of participants within the trial and because their interactions with IntelliCare provided a good illustration of varied experiences regarding engagement with the intervention. Results: The 3 participants’ unique experiences with the intervention are described. Despite potential barriers and experiencing some technical glitches, the participants showed proficient ability to use the apps, high levels of participation through frequent app use and coach interaction, and decreased depression and anxiety scores. At the end of the 8-week intervention, each of these 3 participants expressed great enthusiasm for the benefit of this program through feedback to their coach, and they each identified a number of ways they had seen improvements in themselves. Conclusions: These 3 cases provide examples of older individuals who engaged with and benefitted from the IntelliCare service. Although the results from these 3 cases may not generalize to others, they provide an important, informed perspective of the experiences that can contribute to our understanding of how older adults use and overcome barriers to mental health technologies. The findings also contribute toward the ultimate goal of ensuring that the IntelliCare intervention is appropriate for individuals of all ages.

  • Source: freepik; Copyright: pch.vector; URL:; License: Licensed by JMIR.

    Digital Health Management During and Beyond the COVID-19 Pandemic: Opportunities, Barriers, and Recommendations


    During the coronavirus disease (COVID-19) crisis, digital technologies have become a major route for accessing remote care. Therefore, the need to ensure that these tools are safe and effective has never been greater. We raise five calls to action to ensure the safety, availability, and long-term sustainability of these technologies: (1) due diligence: remove harmful health apps from app stores; (2) data insights: use relevant health data insights from high-quality digital tools to inform the greater response to COVID-19; (3) freely available resources: make high-quality digital health tools available without charge, where possible, and for as long as possible, especially to those who are most vulnerable; (4) digital transitioning: transform conventional offline mental health services to make them digitally available; and (5) population self-management: encourage governments and insurers to work with developers to look at how digital health management could be subsidized or funded. We believe this should be carried out at the population level, rather than at a prescription level.

  • Source: The Authors / Placeit; Copyright: The Authors / Placeit; URL:; License: Licensed by the authors.

    Development of an Emotion-Sensitive mHealth Approach for Mood-State Recognition in Bipolar Disorder


    Internet- and mobile-based approaches have become increasingly significant to psychological research in the field of bipolar disorders. While research suggests that emotional aspects of bipolar disorders are substantially related to the social and global functioning or the suicidality of patients, these aspects have so far not sufficiently been considered within the context of mobile-based disease management approaches. As a multiprofessional research team, we have developed a new and emotion-sensitive assistance system, which we have adapted to the needs of patients with bipolar disorder. Next to the analysis of self-assessments, third-party assessments, and sensor data, the new assistance system analyzes audio and video data of these patients regarding their emotional content or the presence of emotional cues. In this viewpoint, we describe the theoretical and technological basis of our emotion-sensitive approach and do not present empirical data or a proof of concept. To our knowledge, the new assistance system incorporates the first mobile-based approach to analyze emotional expressions of patients with bipolar disorder. As a next step, the validity and feasibility of our emotion-sensitive approach must be evaluated. In the future, it might benefit diagnostic, prognostic, or even therapeutic purposes and complement existing systems with the help of new and intuitive interaction models.

  • Untitled. Source: Freepik; Copyright: jcomp; URL:; License: Licensed by JMIR.

    Acceptability and Utility of an Open-Access, Online Single-Session Intervention Platform for Adolescent Mental Health


    Background: Many youths with mental health needs are unable to access care. Single-session interventions (SSIs) have helped reduce youth psychopathology across multiple trials, promising to broaden access to effective, low-intensity supports. Online, self-guided SSIs may be uniquely scalable, particularly if they are freely available for as-needed use. However, the acceptability of online SSI and their efficacy have remained unexamined outside of controlled trials, and their practical utility is poorly understood. Objective: We evaluated the perceived acceptability and proximal effects of Project YES (Youth Empowerment & Support), an open-access platform offering three online SSIs for youth internalizing distress. Methods: After selecting one of three SSIs to complete, participants (ages 11-17 years) reported pre- and post-SSI levels of clinically relevant outcomes that SSIs may target (eg, hopelessness, self-hate) and perceived SSI acceptability. User-pattern variables, demographics, and depressive symptoms were collected to characterize youths engaging with YES. Results: From September 2019 through March 2020, 694 youths accessed YES, 539 began, and 187 completed a 30-minute, self-guided SSI. SSI completers reported clinically elevated depressive symptoms, on average, and were diverse on several dimensions (53.75% non-white; 78.10% female; 43.23% sexual minorities). Regardless of SSI selection, completers reported pre- to post-program reductions in hopelessness (dav=0.53; dz=0.71), self-hate (dav=0.32; dz=0.61), perceived control (dav=0.60; dz=0.72) and agency (dav=0.39; dz=0.50). Youths rated all SSIs as acceptable (eg, enjoyable, likely to help peers). Conclusions: Results support the perceived acceptability and utility of open-access, free-of-charge SSIs for youth experiencing internalizing distress. Trial Registration: Open Science Framework;

  • Source: freepik; Copyright: Racool_studio; URL:; License: Licensed by JMIR.

    Surveying the Role of Analytics in Evaluating Digital Mental Health Interventions for Transition-Aged Youth: Scoping Review


    Background: Consumer-facing digital health interventions provide a promising avenue to bridge gaps in mental health care delivery. To evaluate these interventions, understanding how the target population uses a solution is critical to the overall validity and reliability of the evaluation. As a result, usage data (analytics) can provide a proxy for evaluating the engagement of a solution. However, there is paucity of guidance on how usage data or analytics should be used to assess and evaluate digital mental health interventions. Objective: This review aimed to examine how usage data are collected and analyzed in evaluations of mental health mobile apps for transition-aged youth (15-29 years). Methods: A scoping review was conducted using the Arksey and O’Malley framework. A systematic search was conducted on 5 journal databases using keywords related to usage and engagement, mental health apps, and evaluation. A total of 1784 papers from 2008 to 2019 were identified and screened to ensure that they included analytics and evaluated a mental health app for transition-aged youth. After full-text screening, 49 papers were included in the analysis. Results: Of the 49 papers included in the analysis, 40 unique digital mental health innovations were evaluated, and about 80% (39/49) of the papers were published over the past 6 years. About 80% involved a randomized controlled trial and evaluated apps with information delivery features. There were heterogeneous findings in the concept that analytics was ascribed to, with the top 3 being engagement, adherence, and acceptability. There was also a significant spread in the number of metrics collected by each study, with 35% (17/49) of the papers collecting only 1 metric and 29% (14/49) collecting 4 or more analytic metrics. The number of modules completed, the session duration, and the number of log ins were the most common usage metrics collected. Conclusions: This review of current literature identified significant variability and heterogeneity in using analytics to evaluate digital mental health interventions for transition-aged youth. The large proportion of publications from the last 6 years suggests that user analytics is increasingly being integrated into the evaluation of these apps. Numerous gaps related to selecting appropriate and relevant metrics and defining successful or high levels of engagement have been identified for future exploration. Although long-term use or adoption is an important precursor to realizing the expected benefits of an app, few studies have examined this issue. Researchers would benefit from clarification and guidance on how to measure and analyze app usage in terms of evaluating digital mental health interventions for transition-aged youth. Given the established role of adoption in the success of health information technologies, understanding how to abstract and analyze user adoption for consumer digital mental health apps is also an emerging priority.

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

    Apps With Maps—Anxiety and Depression Mobile Apps With Evidence-Based Frameworks: Systematic Search of Major App Stores


    Background: Mobile mental health apps have become ubiquitous tools to assist people in managing symptoms of anxiety and depression. However, due to the lack of research and expert input that has accompanied the development of most apps, concerns have been raised by clinicians, researchers, and government authorities about their efficacy. Objective: This review aimed to estimate the proportion of mental health apps offering comprehensive therapeutic treatments for anxiety and/or depression available in the app stores that have been developed using evidence-based frameworks. It also aimed to estimate the proportions of specific frameworks being used in an effort to understand which frameworks are having the most influence on app developers in this area. Methods: A systematic review of the Apple App Store and Google Play store was performed to identify apps offering comprehensive therapeutic interventions that targeted anxiety and/or depression. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist was adapted to guide this approach. Results: Of the 293 apps shortlisted as offering a therapeutic treatment for anxiety and/or depression, 162 (55.3%) mentioned an evidence-based framework in their app store descriptions. Of the 293 apps, 88 (30.0%) claimed to use cognitive behavioral therapy techniques, 46 (15.7%) claimed to use mindfulness, 27 (9.2%) claimed to use positive psychology, 10 (3.4%) claimed to use dialectical behavior therapy, 5 (1.7%) claimed to use acceptance and commitment therapy, and 20 (6.8%) claimed to use other techniques. Of the 162 apps that claimed to use a theoretical framework, only 10 (6.2%) had published evidence for their efficacy. Conclusions: The current proportion of apps developed using evidence-based frameworks is unacceptably low, and those without tested frameworks may be ineffective, or worse, pose a risk of harm to users. Future research should establish what other factors work in conjunction with evidence-based frameworks to produce efficacious mental health apps.

  • Source: The Authors/Placeit; Copyright: The Authors/Placeit; URL:; License: Licensed by the authors.

    Engaging With a Web-Based Psychosocial Intervention for Psychosis: Qualitative Study of User Experiences


    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.

  • EEG test for ADHD. Source: flickr; Copyright: Helgelandssykehuset; URL:; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    Using Mobile Electroencephalography and Actigraphy to Diagnose Attention-Deficit/Hyperactivity Disorder: Case-Control Comparison Study


    Background: Children with attention-deficit/hyperactivity disorder (ADHD), a neurobehavioral disorder, display behaviors of inattention, hyperactivity, or impulsivity, which can affect their ability to learn and establish proper family and social relationships. Various tools are currently used by child and adolescent psychiatric clinics to diagnose, evaluate, and collect information and data. The tools allow professional physicians to assess if patients need further treatment, following a thorough and careful clinical diagnosis process. Objective: We aim to determine potential indicators extracted from a mobile electroencephalography (EEG) device (Mindset; NeuroSky) and an actigraph (MotionWatch 8; CamNtech) and to validate them for diagnosis of ADHD. The 3 indicators are (1) attention, measured by the EEG; (2) meditation, measured by the EEG; and (3) activity, measured by the actigraph. Methods: A total of 63 participants were recruited. The case group comprised 40 boys and 9 girls, while the control group comprised 5 boys and 9 girls. The groups were age matched. The test was divided into 3 stages—pretest, in-test, and posttest—with a testing duration of 20 minutes each. We used correlation analysis, repeated measures analysis of variance, and regression analysis to investigate which indicators can be used for ADHD diagnosis. Results: With the EEG indicators, the analysis results show a significant correlation of attention with both hit reaction time (RT) interstimulus interval (ISI) change (r=–0.368; P=.003) and hit standard error (SE) ISI change (r=–0.336; P=.007). This indicates that the higher the attention of the participants, the smaller both the hit RT change and the hit SE ISI change. With the actigraph indicator, confidence index (r=0.352; P=.005), omissions (r=0.322; P=.01), hit RT SE (r=0.393; P=.001), and variability (r=0.351; P=.005) were significant. This indicates that the higher the activity amounts, the higher the impulsive behavior of the participants and the more target omissions in the continuous performance test (CPT). The results show that the participants with ADHD present a significant difference in activity amounts (P<0.001). The actigraph outperforms the EEG in screening ADHD. Conclusions: When the participants with ADHD are stimulated under restricted conditions, they will present different amounts of activity than in unrestricted conditions due to participants’ inability to exercise control over their concentration. This finding could be a new electronic physiological biomarker of ADHD. An actigraph can be used to detect the amount of activity exhibited and to help physicians diagnose the disorder in order to develop more objective, rapid auxiliary diagnostic tools. Trial Registration: This research was supported by Chang Gung Memorial Hospital (CMRPG 3F1581 and CORPG 3F0751) and approved by the Institutional Review Board of Chang Gung Memorial Hospital (No. 104-5397B) on October 01, 2015.

  • Source: Unsplash; Copyright: Adam Nieścioruk; URL:; License: Licensed by JMIR.

    Using Internet-Based Psychological Measurement to Capture the Deteriorating Community Mental Health Profile During COVID-19: Observational Study


    Background: The coronavirus disease (COVID-19) is expected to have widespread and pervasive implications for mental health in terms of deteriorating outcomes and increased health service use, leading to calls for empirical research on mental health during the pandemic. Internet-based psychological measurement can play an important role in collecting imperative data, assisting to guide evidence-based decision making in practice and policy, and subsequently facilitating immediate reporting of measurement results to participants. Objective: The aim of this study is to use an internet-based mental health measurement platform to compare the mental health profile of community members during COVID-19 with community members assessed before the pandemic. Methods: This study uses an internet-based self-assessment tool to collect data on psychological distress, mental well-being, and resilience in community cohorts during (n=673) and prior to the pandemic (two cohorts, n=1264 and n=340). Results: Our findings demonstrate significantly worse outcomes on all mental health measures for participants measured during COVID-19 compared to those measured before (P<.001 for all outcomes, effect sizes ranging between Cohen d=0.32 to Cohen d=0.81. Participants who demonstrated problematic scores for at least one of the mental health outcomes increased from 58% (n=197/340) before COVID-19 to 79% (n=532/673) during COVID-19, leading to only 21% (n=141) of measured participants displaying good mental health during the pandemic. Conclusions: The results clearly demonstrate deterioration in mental health outcomes during COVID-19. Although further research is needed, our findings support the serious mental health implications of the pandemic and highlight the utility of internet-based data collection tools in providing evidence to innovate and strengthen practice and policy during and after the pandemic.

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    Associations of Electronic Device Use Before and After Sleep With Psychological Distress Among Chinese Adults in Hong Kong: Cross-Sectional Study


    Background: Hong Kong has a high rate of electronic device (e-device; computer, smartphone, and tablet) use. However, little is known about the associations of the duration of e-device use before and after sleep with psychological symptoms. Objective: This study aimed to investigate the associations of the duration of e-device use before and after sleep with psychological distress. Methods: A probability-based telephone survey was conducted on 3162 Hong Kong adults (54.6% female; mean age 47.4 years, SD 18.3 years) in 2016. Multivariate linear and Poisson regressions were used to calculate adjusted regression coefficients (aBs) and prevalence ratios (aPRs) of anxiety and depressive symptoms (measured by Patient Health Questionnaire-4) for the duration from waking to the first e-device use (≥61, 31-60, 6-30, and ≤5 minutes) and the duration of e-device use before sleeping (≤5, 6-30, 31-60, and ≥61 minutes). Results: The first e-device use in ≤5 (vs ≥61) minutes after waking was associated with anxiety (aB 0.35, 95% CI 0.24-0.46; aPR 1.74, 95% CI 1.34-2.25) and depressive symptoms (aB 0.27, 95% CI 0.18-0.37; aPR 1.84, 95% CI 1.33-2.54). Using e-devices for ≥61 (vs ≤5) minutes before sleeping was also associated with anxiety (aB 0.17, 95% CI 0.04-0.31; aPR 1.32, 95% CI 1.01-1.73) and depressive symptoms (aB 0.17, 95% CI 0.05-0.28; aPR 1.47, 95% CI 1.07-2.02). E-device use both ≤5 minutes after waking and for ≥61 minutes before sleeping was strongly associated with anxiety (aB 0.68, 95% CI 0.47-0.90; aPR 2.64, 95% CI 1.90-3.67) and depressive symptoms (aB 0.55, 95% CI 0.36-0.74; aPR 2.56, 95% CI 1.69-3.88). Conclusions: E-device use immediately (≤5 minutes) after waking and use for a long duration (≥61 minutes) before sleeping were associated with anxiety and depressive symptoms among Chinese adults in Hong Kong.

  • Self-assessment function. Source: Monsenso; Copyright: Monsenso; URL:; License: Creative Commons Attribution (CC-BY).

    Mobile App Integration Into Dialectical Behavior Therapy for Persons With Borderline Personality Disorder: Qualitative and Quantitative Study


    Background: The advancement of and access to technology such as smartphones has implications for psychotherapeutic health care and how interventions for a range of mental health disorders are provided. Objective: The objective of this study was to describe the experiences of participants while using a mobile phone app that was designed to enhance and support dialectical behavior therapy for personality disorders. Methods: A combination of in-depth interviews and questionnaires were used to capture the experiences of participants who used the app while undergoing dialectical behavior therapy treatment. A mixed methods approach was used; qualitative data from the interviews were analyzed using thematic analysis and were combined with quantitative data from the questionnaires. Results: Participants (N=24) who were receiving dialectical behavior therapy used the trial app. Participants (n=20) completed an evaluation questionnaire and a subset of this group (n=8) participated in semistructured interviews. Major themes that were identified from the interviews were (1) an overall positive experience of using the app—participants perceived that the app facilitated access and implementation of dialectical behavior therapy strategies (to regulate mood and behavior in challenging situations)—and (2) that the app provided a common source of information for patient and therapist interactions—app-based interactions were perceived to facilitate therapeutic alliance. Qualitative themes from the interviews were largely congruent with the quantitative responses from the questionnaires. Conclusions: Participants welcomed the integration of technology as a supplement to clinical treatment. The app was perceived to facilitate and support many of the therapeutic techniques associated with dialectical behavior therapy treatment. The incorporation of technology into psychotherapeutic interventions may facilitate the transfer of knowledge and strategies that are learned in therapy to use in real-world settings thereby promoting recovery from mental health problems.

  • Source: freepik; Copyright: yanalya; URL:; License: Licensed by JMIR.

    Causal Factors of Anxiety and Depression in College Students: Longitudinal Ecological Momentary Assessment and Causal Analysis Using Peter and Clark...


    Background: Across college campuses, the prevalence of clinically relevant depression or anxiety is affecting more than 27% of the college population at some point between entry to college and graduation. Stress and self-esteem have both been hypothesized to contribute to depression and anxiety levels. Although contemporaneous relationships between these variables have been well-defined, the causal relationship between these mental health factors is not well understood, as frequent sampling can be invasive, and many of the current causal techniques are not well suited to investigate correlated variables. Objective: This study aims to characterize the causal and contemporaneous networks between these critical mental health factors in a cohort of first-year college students and then determine if observed results replicate in a second, distinct cohort. Methods: Ecological momentary assessments of depression, anxiety, stress, and self-esteem were obtained weekly from two cohorts of first-year college students for 40 weeks (1 academic year). We used the Peter and Clark Momentary Conditional Independence algorithm to identify the contemporaneous (t) and causal (t-1) network structures between these mental health metrics. Results: All reported results are significant at P<.001 unless otherwise stated. Depression was causally influenced by self-esteem (t-1 rp, cohort 1 [C1]=–0.082, cohort 2 [C2]=–0.095) and itself (t-1 rp, C1=0.388, C2=0.382) in both cohorts. Anxiety was causally influenced by stress (t-1 rp, C1=0.095, C2=0.104), self-esteem (t-1 rp, C1=–0.067, C2=–0.064, P=.002), and itself (t-1 rp, of C1=0.293, C2=0.339) in both cohorts. A causal link between anxiety and depression was observed in the first cohort (t-1 rp, C1=0.109) and only observed in the second cohort with a more liberal threshold (t-1 rp, C2=0.044, P=.03). Self-esteem was only causally influenced by itself (t-1 rp, C1=0.389, C2=0.393). Stress was only causally influenced by itself (t-1 rp, C1=0.248, C2=0.273). Anxiety had positive contemporaneous links to depression (t rp, C1=0.462, C2=0.444) and stress (t rp, C1=0.354, C2=0.358). Self-esteem had negative contemporaneous links to each of the other three mental health metrics, with the strongest negative relationship being stress (t rp, C1=–0.334, C2=–0.340), followed by depression (t rp, C1=–0.302, C2=–0.274) and anxiety (t rp, C1=–0.256, C2=–0.208). Depression had positive contemporaneous links to anxiety (previously mentioned) and stress (t rp, C1=0.250, C2=0.231). Conclusions: This paper is an initial attempt to describe the contemporaneous and causal relationships among these four mental health metrics in college students. We replicated previous research identifying concurrent relationships between these variables and extended them by identifying causal links among these metrics. These results provide support for the vulnerability model of depression and anxiety. Understanding how causal factors impact the evolution of these mental states over time may provide key information for targeted treatment or, perhaps more importantly, preventative interventions for individuals at risk for depression and anxiety.

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