Jmir Mental Health最新文献

{"title":"Association of Daily Step Count With Depressive Symptoms in Patients With Major Depressive Disorder Using a Smartphone App (ReMAP): Longitudinal Study.","authors":"Alexander Refisch, Lara Gutfleisch, Daniel Emden, Vincent Holstein, Marius Gruber, Janik Goltermann, Maike Richter, Janette Ratzsch, Anna Fleuchhaus, Elisabeth Leehr, Susanne Meinert, Tiana Borgers, Kira Flinkenfügel, Frederike Stein, Florian Thomas-Odenthal, Paula Usemann, Lea Teutenberg, Nina Alexander, Ronny Redlich, Igor Nenadić, Tilo Kircher, Udo Dannlowski, Tim Hahn, Nils Opel","doi":"10.2196/81120","DOIUrl":"10.2196/81120","url":null,"abstract":"<p><strong>Background: </strong>The benefits of physical activity (PA) for both physical and mental health, including major depressive disorder (MDD), are well established. Mobile devices, such as smartphones, offer a scalable way to monitor PA and its relationship with depressive symptoms in daily life.</p><p><strong>Objective: </strong>This study aimed to investigate the association between passive smartphone-recorded step counts and current depressive symptoms in individuals with and without a lifetime diagnosis of MDD, using a naturalistic bring-your-own-device approach.</p><p><strong>Methods: </strong>We used the Remote Monitoring Application in Psychiatry (ReMAP) to collect passive step count data from participants' personal smartphones. The sample included 181 individuals with a lifetime MDD diagnosis, assessed via the structured clinical interview for the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition; DSM-IV), and 195 healthy controls (HCs). Current depressive symptoms were assessed using the Beck Depression Inventory. PA was operationalized as daily and weekly step counts, passively recorded via smartphone sensors. Hierarchical models were applied to examine the association between PA and depression severity.</p><p><strong>Results: </strong>Patients with MDD exhibited significantly lower daily step counts (mean 3454, SD 2683) compared to HCs (mean 4699, SD 3175; P<.001) and showed reduced diurnal variability (β=-0.36; P=.003). Higher daily step counts were associated with lower Beck Depression Inventory scores across the full sample (β=-0.06, 95% CI -0.09 to -0.02; P=.002), with similar trends in both MDD and HC groups. Weekly step counts also significantly predicted lower concurrent depressive symptoms (β=-0.29, 95% CI -0.43 to -0.14; P<.001), while patients with MDD displayed less variability in weekly activity levels than HCs (β=-0.75; P=.001).</p><p><strong>Conclusions: </strong>These findings underscore the potential of mobile devices to be used as effective tools for monitoring PA in patients with MDD, supporting more customized and adaptive approaches to prevention and treatment. They also emphasize the importance of incorporating PA into the clinical management of depression.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e81120"},"PeriodicalIF":5.8,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12894579/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146167365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resilience as a Mediator in a Web-Based Intervention (MINDxYOU) to Reduce Stress Among Health Care Professionals: Stepped-Wedge Cluster Randomized Trial.","authors":"Gloria Guerrero-Pertiñez, Vera Carbonell-Aranda, Gloria Pérez-Guerrero, Jonathan Joseph Dawood-Hristova, Adrián Pérez-Aranda, Selene Fernández-Martínez, Alicia Monreal-Bartolomé, Alberto Barceló-Soler, Javier García-Campayo, Yolanda López Del Hoyo, Jesús Herrera-Imbroda, Jessica Marian Goodman-Casanova, Jose Guzman-Parra","doi":"10.2196/82905","DOIUrl":"10.2196/82905","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The mechanisms through which mindfulness and third wave-based digital programs exert their effects on stress reduction remain poorly understood. Identifying these mediators is essential to optimize their implementation, particularly in health care settings. This approach is particularly relevant for health care professionals, who are constantly exposed to high levels of emotional demands, work overload, and risk of burnout, especially in the aftermath of the COVID-19 pandemic. Despite the growing need for scalable and accessible mental health support in this population, such digital programs remain scarce and underused.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The primary aim of this study was to analyze the psychological mechanisms through which the MINDxYOU online program may contribute to stress reduction among health care professionals, focusing on a mediation model. Specifically, we explored if variables such as resilience and facets of mindfulness, compassion, and acceptance mediated the effects of the intervention on perceived stress.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In a stepped-wedge cluster randomized design, 357 health professionals from health centers in Aragon and Málaga, Spain, were recruited. They were divided into 6 clusters, 3 per region, and randomly assigned to one of the 3 sequences, each starting with a control phase and then transitioning to the intervention phase (the MINDxYOU program) after 8, 16, or 24 weeks. This self-guided, web-based program, designed to be completed over 8 weeks, included weekly contact (via WhatsApp, call, or email) from the research team to promote adherence. Participants were assessed on the web every 8 weeks for 5 assessments. Perceived stress was the study's primary outcome, with additional measures of clinical factors (anxiety, depression, and somatization) and process variables (resilience, mindfulness, compassion, and acceptance). Mediation models using mixed-effects regressions and bootstrap resampling (1000 iterations) were applied to analyze the direct and indirect effects of the treatment on psychological outcomes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Resilience emerged as the most consistent and significant mediator, exerting a relevant indirect effect on reducing stress (β=-1.41; P=.02), anxiety (β=-0.88; P=.03), and depression (β=-0.97; P=.01), even in multivariate models. Mindfulness facets such as observing, describing, and nonreacting also showed significant, albeit less consistent, mediating effects. In contrast, compassion and acceptance were weakly associated and did not play a significant mediating role.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;These results demonstrate resilience as the key psychological mediator. Strengthening resilience through online interventions appears to be a crucial pathway for reducing stress and emotional symptoms in this population. Specific mindfulness skills may also contribute to the intervention's therapeutic effect, although with le","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e82905"},"PeriodicalIF":5.8,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12885452/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146151174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing Psychiatric Safety With the Predictive Risk Identification for Mental Health Events Tool: Retrospective Cohort Study.","authors":"Elham Dolatabadi, Valentina Tamayo Velasquez, Abdul Hamid Dabboussi, David Wen, Jennifer Crawford, Andrea E Waddell, Christo El Morr","doi":"10.2196/84318","DOIUrl":"10.2196/84318","url":null,"abstract":"<p><strong>Background: </strong>Patient safety incidents are a leading cause of harm in psychiatric settings, yet early warning systems (EWS) tailored to mental health remain underdeveloped. Traditional risk tools such as the Dynamic Appraisal of Situational Aggression-Inpatient Version (DASA-IV) offer limited predictive accuracy and are reactive rather than proactive.</p><p><strong>Objective: </strong>We introduce the Predictive Risk Identification for Mental Health Events (PRIME) tool, a deep learning-based EWS trained on longitudinal psychiatric electronic medical record (EMR) data to anticipate adverse events in 24-hour windows.</p><p><strong>Methods: </strong>A retrospective cohort study using routinely collected EMR data to train and validate machine learning (ML) models for short-term risk prediction was conducted. This study took place at Waypoint Centre for Mental Health Care, a large inpatient psychiatric hospital in Ontario, Canada, serving both high-security forensic and nonforensic patient populations. A total of 4651 patients and 403,098 encounters from January 2020 to August 2024 were included. For model evaluation, the 2024 test set included 900 patients and 48,313 encounters. PRIME was trained using recurrent neural networks with attention mechanisms on multivariate time-series data. The model used an autoregressive design to forecast risk based on 7 days of prior patient data and was benchmarked against the DASA-IV clinical tool and other ML baselines. The primary outcome was the occurrence of an adverse mental health event recorded in the EMR within the following 24 hours. Model performance was assessed using area under the receiver operating characteristic curve (AUC) and recall, alongside subgroup analyses and interpretability assessments using integrated gradients.</p><p><strong>Results: </strong>The long short-term memory with attention mechanism achieved the highest predictive performance (AUC=0.83), outperforming existing tools such as DASA-IV by 0.20 AUC (0.81 vs 0.61) and demonstrating the potential of ML-based models to support proactive risk management in mental health settings.</p><p><strong>Conclusions: </strong>The PRIME tool is one of the first developed and evaluated deep learning-based EWS for psychiatric inpatient care. By outperforming existing clinical tools and providing interpretable, rolling predictions, PRIME offers a pathway toward safer, more proactive mental health interventions. Future work should assess its equity implications and integration into routine psychiatric workflows.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e84318"},"PeriodicalIF":5.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12924039/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146133341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detecting Pediatric Emergency Service Use for Suicide and Self-Harm: Multimodal Analysis of 3828 Encounters.","authors":"Juliet Beni Edgcomb, Angshuman Saha, Alexandra Klomhaus, Elyse Tascione, Chrislie G Ponce, Joshua J Lee, Theona Tacorda, Bonnie T Zima","doi":"10.2196/82371","DOIUrl":"10.2196/82371","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Suicide is the second-leading cause of US childhood mortality after 9 years of age. The accurate measurement of pediatric emergency service use for self-injurious thoughts and behaviors (SITB) remains challenging, as diagnostic codes undercount children. This measurement gap impedes public health and prevention efforts. Current research has not established which combination of electronic health record data elements achieves both high detection accuracy and consistent performance across youth populations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to (1) compare the detection accuracy of electronic health record-based methods for identifying SITB-related pediatric emergency department (ED) visits: basic structured data (International Classification of Diseases Version 10, Clinical Modification codes, chief concern), comprehensive structured data, clinical note text with natural language processing, and hybrid approaches combining structured data with notes; and (2) for each method, measure variability in detection by youth demographics and underlying mental health diagnosis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Multiple human experts reviewed clinical records of 3828 pediatric mental health emergency visits (28,861 clinical notes) to a large health system with 2 EDs (June 2022-October 2024). The reviewers used the Columbia Classification Algorithm for Suicide Assessment to label the presence of SITB at the visit. Random forest classifiers were developed using 3 data modalities: (1) structured data (low-dimensional [International Classification of Diseases codes and chief concerns], medium-dimensional [adding Columbia Suicide Severity Rating Scale screening or mental health diagnoses], and high-dimensional [all structured data or augmented case surveillance, aCS]); (2) text data (general-purpose natural language processing, medical text-specific trained natural language processing, and Large Language Model Meta AI-derived scores), and (3) hybrid data (combining aCS with each text approach). Model performance was evaluated using area under the receiver operating characteristic curve (AUROC).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of the 3828 visits, 1760 (n=1760, 46.0%) were SITB-related. Detection performance improved with dimensionality: low-dimensional (AUROC=0.865), medium-dimensional (AUROC=0.934-0.935), and high-dimensional (AUROC=0.965). Low-dimensional structured (International Classification of Diseases codes and chief concerns) showed high variability in detection, with lower accuracy among preadolescents (AUROC=0.821 vs 0.880 for adolescents); male participants (AUROC=0.817 vs 0.902 for females); and patients with neurodevelopmental (AUROC=0.568-0.809), psychotic (AUROC=0.718), and disruptive disorders (AUROC=0.703). Hybrid modality (aCS+Large Language Model Meta AI) achieved optimal performance (AUROC=0.977), with AUROC ≥0.90 for all 20 demographic and 12/15 diagnostic subgroups.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/st","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e82371"},"PeriodicalIF":5.8,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12871580/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146120585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digitally-Delivered Cognitive-Behavioral Interventions for Alcohol and Other Drug Use: A Meta-Analysis across Consumption and Psychosocial Outcomes.","authors":"Brian Kiluk, Lara Ray, Omeed Tartak, Lovisa Werner, Thomas Trikalinos, Molly Magill","doi":"10.2196/82370","DOIUrl":"https://doi.org/10.2196/82370","url":null,"abstract":"<p><strong>Background: </strong>Cognitive-behaviorally-based interventions (CBI) have broad appeal and potential for impact when treating adult alcohol and other drug use (AOD). CBIs delivered through digital platforms (dCBIs) may offer this impact with the benefit of increased accessibility. Although prior reviews have indicated benefits of dCBIs on substance use outcomes, the extension to psychosocial functioning outcomes is unknown.</p><p><strong>Objective: </strong>The current meta-analysis provides an overview of dCBI effects across a range of functional endpoints.</p><p><strong>Methods: </strong>A literature search was conducted through October of 2024. All primary and secondary reports of clinical trials of dCBI were obtained and all available study endpoints were eligible for meta-analysis. Descriptive data were extracted and categorized into one of thirteen different outcome types (eg, abstinence, quantity, cognitive, quality of life), and into two broader outcome classes (ie, consumption; psychosocial). Robust variance estimation was used to conduct hypothesis tests on random effects pooled estimates with outcome class and comparison type as the primary sub-group variables of interest.</p><p><strong>Results: </strong>The study sample included 65 randomized trials (K = 110 publications; 753 effect sizes) of dCBI for adult AOD. With respect to efficacy, dCBI as a stand-alone treatment in contrast to a minimal treatment control showed positive and statistically significant effects for consumption (g = 0.27, P < .001; I2 = 85.1%; k = 31, kes = 134) and psychosocial (g = 0.16, P = .008; I2 = 75.2%; k = 16, kes = 60) outcomes. As an addition to usual care, efficacy was demonstrated for consumption (g = 0.23, P < .001; I2 = 9.8%; k = 20, kes = 65), but not psychosocial functioning. Efficacy compared to another digital or in person intervention or CBI delivered by a therapist was not observed. Within dCBI condition, large effect sizes were observed for both outcome classes (ie, 60%-80% of participants showed improvement relative to baseline), and effect size magnitude and statistical heterogeneity varied by the type of outcome examined.</p><p><strong>Conclusions: </strong>These results show a benefit for dCBI as a stand-alone therapy and an addition to usual care. Importantly, stand-alone effects were observed for both consumption and some psychosocial outcomes. This study is the first to offer a comprehensive look at dCBI intervention effects across a range of functional endpoints.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":" ","pages":""},"PeriodicalIF":5.8,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147475928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"\"It Felt Good to Be Able to Say That Out Loud\"-Therapeutic Alliance and Processes in AVATAR Therapy for People Who Hear Distressing Voices: Peer-Led Qualitative Study.","authors":"Emily Rutter-Eley, Thomas Craig, Philippa Garety, Mar Rus-Calafell, Hannah Ball, Moya Clancy, Jeffrey McDonnell, Andrew Gumley, Gillian Haddock, Sandra Bucci, Miriam Fornells-Ambrojo, Nerys Baldwin, Jed Harling, Alie Phiri, Charlie MacKenzie-Nash, Nicholas Hamilton, Amy Grant, Clementine Edwards, Thomas Ward","doi":"10.2196/77566","DOIUrl":"10.2196/77566","url":null,"abstract":"<p><strong>Background: </strong>AVATAR therapy is a novel psychological therapy that aims to reduce distress associated with hearing voices. The approach involves a series of therapist-facilitated dialogues between a voice-hearer and a digital embodiment of their main distressing voice (the avatar), which aim to increase coping and self-empowerment.</p><p><strong>Objective: </strong>This study explored therapeutic processes that are distinctive to AVATAR therapy, including direct early work with voice content and the role of the therapist in dialogue enactment.</p><p><strong>Methods: </strong>People with lived experience relating to psychosis (peer researchers) contributed to each stage of the study. Peer researchers led semistructured interviews, which were conducted with 19 participants who received AVATAR therapy as part of the AVATAR2 trial, including 3 participants who dropped out of therapy. Data were analyzed using interpretative phenomenological analysis (n=5) and template analysis (n=14).</p><p><strong>Results: </strong>Participants described the initial challenges of experiential work with distressing voice content; however, most reported a meaningful increase in power and control over the course of dialogues and improvements with voices in daily life. A strong therapeutic alliance was experienced by all participants, including those who chose to discontinue therapy, often mitigating the discomfort associated with initial challenges by enhancing their sense of safety. Several important themes relating to individual engagement were highlighted, such as the emotional intensity of the experience and the importance of participants' determination and open-minded attitudes despite initial doubts. Those who decided not to continue with therapy described challenges with the realism of working dialogically with a digital representation of their distressing voice.</p><p><strong>Conclusions: </strong>This study has provided a deeper understanding of the experience of engaging in AVATAR therapy, in particular the challenges and opportunities of direct work with voice content. The importance of therapeutic alliance and establishing a sense of voice presence has been emphasized. Implications for the planned optimization and wider implementation of AVATAR therapy in routine care settings are discussed.</p><p><strong>Trial registration: </strong>ISRCTN Registry ISRCTN55682735; https://www.isrctn.com/ISRCTN55682735.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e77566"},"PeriodicalIF":5.8,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12895157/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146195858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retention and Engagement in Culturally Adapted Digital Mental Health Interventions: Systematic Review of Dropout, Attrition, and Adherence in Non-Western, Educated, Industrialized, Rich, Democratic Settings.","authors":"Tanya Tandon, Rajashree Biswas, Quentin Meteier, Karl Daher, Omar Abou Khaled, Björn Meyer, Thomas Berger, Rashmi Gupta, Chantal Martin Soelch","doi":"10.2196/80624","DOIUrl":"10.2196/80624","url":null,"abstract":"<p><strong>Background: </strong>Digital mental health interventions (DMHIs) offer scalable and cost-effective support for mental health but are predominantly developed in WEIRD (western, educated, industrialized, rich, democratic) contexts, raising questions about their global applicability. Dropout, attrition, and adherence rates critically influence DMHI effectiveness yet remain poorly characterized in culturally adapted formats.</p><p><strong>Objective: </strong>This systematic review aimed to (1) synthesize evidence on dropout, attrition, and adherence in culturally adapted DMHIs delivered to non-WEIRD adult populations and (2) assess the methodological quality of the included studies.</p><p><strong>Methods: </strong>PsycINFO, PubMed, and ScienceDirect were systematically searched for randomized controlled trials published in English between January 2014 and April 2024. Screening and data extraction followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, and methodological quality was evaluated using the Appraisal Tool for Cross-Sectional Studies tool. Extracted variables included dropout, attrition, adherence, adaptation techniques, and clinical outcomes.</p><p><strong>Results: </strong>Twenty-three randomized controlled trials (n=4656) from diverse regions met inclusion criteria. Attrition ranged from 5.3% to 87% (median 18.4%), dropout from 0% to 66% (median 18.7%), and adherence from 26.3% to 100% (median 71%). Deep, participatory adaptations-such as language translation combined with culturally resonant content, stakeholder engagement, and iterative refinement-were consistently associated with lower dropout (<11%) and higher adherence (>75%). In contrast, surface-level adaptations (eg, translation only) showed higher dropout (up to 56%). Studies that incorporated both cultural tailoring and human support reported the most favorable engagement and clinical outcomes (eg, reductions in insomnia, depression, and anxiety). Most studies (91%) were rated as \"Good\" quality, although some lacked representative sampling or objective engagement metrics.</p><p><strong>Conclusions: </strong>Comprehensive and participatory cultural adaptation is associated with engagement and effectiveness of DMHIs among non-WEIRD populations. Future research should integrate hybrid human-digital delivery models, objective engagement metrics, and larger multicenter trials to improve generalizability and scalability.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e80624"},"PeriodicalIF":5.8,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12850045/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146067817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote Measurement-Based Care Interventions for Mental Health: Systematic Review and Meta-Analysis.","authors":"Felix Machleid, Twyla Michnevich, Leu Huang, Louisa Schröder-Frerkes, Caspar Wiegmann, Toni Muffel, Jakob Kaminski","doi":"10.2196/63088","DOIUrl":"10.2196/63088","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Poor management of mental health conditions leads to reduced adherence to treatment, prolonged illness, unnecessary rehospitalization, and a significant financial burden to the health care system. Recognizing this, ecological momentary assessment (EMA) and remote measurement-based care (RMBC) interventions have emerged as promising strategies to address gaps in current care systems. They provide a convenient means to continuously monitor patient-reported outcomes, thereby informing clinical decision-making and potentially improving outcomes such as psychopathology, relapse, and quality of life.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This systematic review and meta-analysis aims to comprehensively appraise and analyze the existing evidence on the use of EMA and RMBC for people living with mental illness.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The study was conducted according to PRISMA-P (Preferred Reporting Items for Systematic Review and Explanation Meta-Analysis Protocols) guidelines and preregistered with the PROSPERO systematic review registry. A comprehensive search was conducted in 4 online databases using Medical Subject Headings terms related to mental disorders and digital technologies. Studies were included if they included adults with a formally diagnosed mental disorder and measured symptoms using EMA or RMBC. Studies were independently reviewed by subgroups of authors, and data were extracted focusing on symptom-focused or disease-specific outcomes, relapse, recovery-focused outcomes, global functioning, quality of life, and acceptability of the intervention. We performed a descriptive analysis of demographic variables and a meta-analysis of randomized controlled trials (RCTs). Risk of bias was assessed using the Cochrane risk-of-bias tool for randomized trials version 2 (RoB-2).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The systematic review included 103 studies, of which 15 used RMBC. Of these, 9 were RCTs that were meta-analyzed. RMBC interventions varied in effectiveness, generally showing small but significant effects on symptom-specific outcomes, with notable effects on mania symptoms and empowerment. The mean adherence rate across studies to all tracking items was 74.5% (SD 13.98; n=38). More prompts per day, but not more items per prompt, were associated with lower adherence. Adverse effects were infrequently reported and included technical problems and psychological distress. Concerns about bias were raised, particularly regarding participants' awareness of the interventions and potential deviations from the intended protocols.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Although RMBC shows growing potential in improving and tailoring psychiatric care to individual needs, the evidence of its clinical effectiveness is still limited. However, we found potential effects on mania symptoms and empowerment. Overall, there were only a few RCTs with formal psychiatric diagnoses to be included in our analyses, and these had moderat","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e63088"},"PeriodicalIF":5.8,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12849610/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146067794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Smartphone-Tracked Behavioral Markers to Recognize Depression and Anxiety Symptoms: Cross-Sectional Digital Phenotyping Study.","authors":"George Aalbers, Andrea Costanzo, Raj Jagesar, Femke Lamers, Martien J H Kas, Brenda W J H Penninx","doi":"10.2196/80765","DOIUrl":"10.2196/80765","url":null,"abstract":"<p><strong>Background: </strong>Depression and anxiety are prevalent but commonly missed and misdiagnosed, an important concern because many patients do not experience spontaneous recovery, and the duration of untreated illness is associated with worse outcomes.</p><p><strong>Objective: </strong>This study aims to explore the potential of using smartphone-tracked behavioral markers to support diagnostics and improve recognition of these disorders.</p><p><strong>Methods: </strong>We used the dedicated Behapp digital phenotyping platform to passively track location and app usage in 217 individuals, comprising symptomatic (n=109; depression/anxiety diagnosis or symptoms) and asymptomatic individuals (n=108; no diagnosis/symptoms). After quantifying 46 behavioral markers (eg, % time at home), we applied a machine learning approach to (1) determine which markers are relevant for depression/anxiety recognition and (2) develop and evaluate diagnostic prediction models for doing so.</p><p><strong>Results: </strong>Our analysis identifies the total number of GPS-based trajectories as a potential marker of depression/anxiety, where individuals with fewer trajectories are more likely to be symptomatic. Models using this feature in combination with demographics or in isolation outperformed demographics-only models (area under the receiver operating characteristic curveMdn=0.60 vs 0.60 vs 0.51).</p><p><strong>Conclusions: </strong>Collectively, these findings indicate that smartphone-tracked behavioral markers have limited discriminant ability in our study but potential to support future depression/anxiety diagnostics.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e80765"},"PeriodicalIF":5.8,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12836477/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146054559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating a Culturally Tailored Digital Storytelling Intervention to Improve Trauma Awareness in Conflict-Affected Eastern Congo: Quasi-Experimental Pilot Study.","authors":"Achille Bapolisi, Jennifer Foucart, Déborah Kabambi, Raïssa Mirishe, Elvis Musa, Aline Ruvunangiza, Joyce Bosomi, Victor Bulabula, Marc Ilunga, Emmanuel Kajibwami, Odile Bapolisi, Arsene Daniel Nyalundja, Marie-Hélène Igega, Pacifique Mwene-Batu, Philippe de Timary, Yasser Khazaal","doi":"10.2196/81291","DOIUrl":"10.2196/81291","url":null,"abstract":"<p><strong>Background: </strong>Posttraumatic stress disorder (PTSD) is highly prevalent in conflict-affected regions like eastern Democratic Republic of Congo; yet, cultural stigma and lack of psychoeducation limit public understanding and help-seeking behaviors.</p><p><strong>Objective: </strong>This study evaluates the effect of a short, culturally adapted animated video on mental health perception, knowledge, and attitudes toward trauma.</p><p><strong>Methods: </strong>A community-based quasi-experimental pre-post design was implemented among 239 participants from South Kivu. The intervention involved viewing a 3-minute animated psychoeducational video portraying locally relevant PTSD symptoms and resilience strategies. Perception, knowledge, and attitude scores were measured before and after the intervention, alongside PTSD prevalence and video appreciation.</p><p><strong>Results: </strong>Out of 239, 40% (n=96) of the participants screened positively for PTSD. Post intervention, significant improvements were observed in perception (P=.01), knowledge (P<.001), and attitudes (P=.001) toward trauma. Appreciation was high; 82% (n= 195) expressed empathy for the characters, and 74% (n= 176) were likely to share the video. Linear regression showed that having PTSD symptoms (β coefficient=3.29, SE=1.09; P=.003), years of education (β coefficient=0.54, SE=0.08; P<.001), empathy toward the portrayed situations (β coefficient=5.07, SE=0.56; P<.001), perceived acquisition of new knowledge (β coefficient=2.58, SE=0.59; P<.001) and willingness to share the video (β coefficient=1.75, SE=0.50; P=.001) predicted stronger positive effect. A multiple linear regression including all predictors revealed that PTSD symptoms (β coefficient=1.93, SE=0.90; P=.03), years of education (β coefficient=0.47, SE=0.07; P<.001), empathy toward the portrayed situations (β coefficient=3.50, SE=0.55; P<.001), and willingness to share the video (β coefficient=1.75, SE=0.50; P=.001) remained significant predictors of video impact. Age and perceived acquisition of new knowledge were not significant in the multivariate model. This model accounted for 44.6% of the variance in video impact scores (R²=0.446, F_6,231=30.99, P<.001).</p><p><strong>Conclusions: </strong>This study highlights the effectiveness of culturally grounded, low-cost digital media for improving mental health literacy in postconflict settings. Video-based tools may serve as scalable components of trauma-informed care and public health communication in low-resource, high-need areas.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e81291"},"PeriodicalIF":5.8,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12887569/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146054549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}