Jmir Mental Health最新文献

{"title":"Temporal Patterns of Engagement and Sentiment in a Suicide Prevention Mobile App: Three-Year Observational Study.","authors":"Elia Gabarron, Nathan Massicot, Kerstin Denecke","doi":"10.2196/95374","DOIUrl":"10.2196/95374","url":null,"abstract":"<p><strong>Background: </strong>Temporal fluctuations in distress and suicidal ideation across daily, weekly, and seasonal cycles may influence the use and effectiveness of digital suicide prevention tools. Understanding patterns of app engagement, perceived suffering, and affective expression can inform the design of proactive, personalized digital interventions, thereby impacting adherence and efficacy.</p><p><strong>Objective: </strong>This study aimed to examine temporal patterns of engagement with 2 core components of the suicide prevention app SERO (Suicide Prevention: a Uniform Effort, Resource-Oriented; BFH, Lucerne Psychiatry), specifically the safety plan and the PRISM-S (Pictorial Representation of Illness and Self-Measure-Suicidality) self-assessment, using 3 years of interaction log data, assessing variations across circadian, weekly, and seasonal cycles, and evaluating the sentiment of free-text responses submitted immediately after PRISM-S self-assessments.</p><p><strong>Methods: </strong>We analyzed anonymized interaction logs from the SERO app collected over 3 years (November 2022 to December 2025). Engagement metrics included the frequency of use of the safety planning functionality and PRISM-S self-assessment entries. Free-text responses provided after PRISM-S assessments were analyzed using automated sentiment classification. Temporal analyses examined variations by the hour of the day, day of the week, and season. One-way ANOVAs, post hoc tests, and Pearson correlations were used to examine patterns and associations between perceived suffering and sentiment.</p><p><strong>Results: </strong>A total of 1076 users engaged with the safety planning functionality of the SERO app, generating 3502 entries, with coping strategies and warning signs showing the highest mean interactions and personal beliefs the lowest. Separately, 1212 app users accessed the PRISM-S self-assessment, producing 2329 entries (mean distance 12.91, 95% CI 12.39-13.42 cm), with most app users recording only 1 or 2 registrations. Safety planning engagement showed clear diurnal patterns, peaking in the afternoon (2 PM to 3 PM) and being lowest at night (midnight to 3 AM), whereas PRISM-S scores were stable across time. Sentiment analysis revealed predominantly negative affect (mean score of -0.41, SD 0.51, 95% CI -0.44 to -0.39), correlated with PRISM-S distance, and was most negative at night (specifically at 11 PM) and during the afternoon (2 PM to 5 PM). Seasonal effects were small but significant for PRISM-S, with the lowest perceived suffering in summer.</p><p><strong>Conclusions: </strong>Digital suicide prevention tools can support routine patterns of coping behavior, but periods of increased reported distress, particularly at night, may be underaddressed. Integrating automated sentiment analysis alongside self-assessments could potentially enable personalized, time-adaptive interventions that detect changes in emotional state and deliver timely, tailore","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e95374"},"PeriodicalIF":7.4,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13375210/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148473394","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":"A Self-Guided Mobile Mindfulness Intervention Embedded in Daily Routines for Adults With Mild to Moderate Psychological Distress: Randomized Controlled Trial.","authors":"Xichun Wu, Jackelyn De Alwis, Zenan Dou, Hoyin Lo, Sisi Wang, Jingyi Wu, Wei Xu","doi":"10.2196/98056","DOIUrl":"10.2196/98056","url":null,"abstract":"<p><strong>Background: </strong>Mobile mindfulness interventions have shown promise for reducing anxiety and depressive symptoms, but sustaining engagement remains a persistent challenge. Many digital programs still rely on formal practice that requires dedicated time, which may be difficult to integrate into daily life.</p><p><strong>Objective: </strong>This randomized controlled trial evaluated Habitual Mindfulness Practice (HMP), a self-guided mobile mindfulness intervention that embeds brief practices into recurring daily routines, among adults with mild to moderate psychological distress. Outcomes were compared with those of Traditional Mindfulness (TM), Mindfulness-Based Psychoeducation (MBP), and a waitlist control (WL).</p><p><strong>Methods: </strong>Adults aged 18 to 65 years with mild to moderate symptoms of anxiety or depression were randomly assigned in a 1:1:1:1 ratio to HMP, TM, MBP, or WL (N=686). All procedures were conducted online, and the intervention was fully self-guided, with outcomes assessed using self-report measures. The intervention lasted 21 days, with assessments conducted at baseline, postintervention, and 3-month follow-up. Primary outcomes were depressive and anxiety symptoms. Secondary outcomes included mindfulness, cognitive emotion regulation, affective balance, and interpersonal difficulties. Postintervention group differences were examined, controlling for baseline scores, and longitudinal trajectories were evaluated across the active intervention conditions.</p><p><strong>Results: </strong>At postintervention, significant group effects were observed for depressive symptoms (F3,681=28.67, P<.001, ηp²=0.11) and anxiety symptoms (F3,681=30.11, P<.001, ηp²=0.12). Both HMP and TM showed lower depressive and anxiety symptom scores than MBP and WL. TM showed lower postintervention anxiety than HMP (P=.04), whereas depressive symptoms did not differ significantly between HMP and TM (P=.63). The mindfulness practice conditions also showed more favorable postintervention outcomes for mindfulness, affective balance, interpersonal difficulties, and emotion regulation. Improvements in depressive and anxiety symptoms were generally maintained at follow-up among the active intervention conditions, although maintenance of secondary outcomes varied across measures. Postintervention outcome data were available for 55.2% (379/686) of randomized participants, and follow-up outcome data were available for 24.1% (124/515) of participants in the active intervention conditions. HMP and TM did not differ significantly in practice duration, engagement, or satisfaction.</p><p><strong>Conclusions: </strong>A routine-embedded, self-guided mobile mindfulness intervention may be a feasible approach for reducing mild to moderate psychological distress. HMP produced benefits broadly comparable to those of traditional app-delivered mindfulness, but it did not confer advantages in engagement or short-term efficacy.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e98056"},"PeriodicalIF":7.4,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13372293/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148457365","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":"Active Ingredients in Digital Cognitive Interventions: Integrating Dismantling Designs With Mechanistic Neuroscience.","authors":"Sarah Shizuko Morimoto, Cutter Augustus Lindbergh, Alexander Conley, Dusti R Jones, David C Steffens","doi":"10.2196/94246","DOIUrl":"10.2196/94246","url":null,"abstract":"<p><strong>Unlabelled: </strong>Digital cognitive interventions (DCIs) have emerged as scalable approaches for treating cognitive dysfunction across psychiatric, neurological, and aging populations. Despite growing evidence of efficacy, little is known about which intervention components drive therapeutic effects or through which neurocognitive mechanisms they operate. As a result, null findings are often difficult to interpret, making it unclear whether interventions failed to engage their intended targets, or whether the targets themselves are not causally related to meaningful outcomes. This limits intervention refinement, comparative evaluation, and precision personalization. Here, we argue that DCI research should shift from broad efficacy testing toward mechanistic trials designed to identify active ingredients-the intervention components responsible for engaging prespecified neurocognitive targets and producing clinically meaningful benefits. We propose adapting dismantling design methodology from psychotherapy research in order to integrate Research Domain Criteria constructs, mechanistic neuroscience, and high-resolution digital behavioral data to identify factors driving cognitive and functional outcomes. This approach aligns with the National Institute of Mental Health experimental therapeutics framework by explicitly linking target specification and target engagement with downstream clinical and functional outcomes. Mechanistic dismantling trials can determine whether specific DCI features, including adaptive difficulty, reward schedules, feedback contingencies, task variability, cognitive targets, and human support, are necessary, sufficient, or synergistic for engaging neural circuitry and producing durable and clinically meaningful transfer. Beyond optimizing intervention design, such studies may transform null or negative trials into mechanistically interpretable findings, while clarifying disease mechanisms and supporting the development of personalized, optimized, and usable DCIs.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e94246"},"PeriodicalIF":7.4,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13373463/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148457352","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":"Supportive Text Messaging was Associated with Reduced Health Service Utilization Costs in the 6 Months Following Psychiatric Admission: An Exploratory Secondary Analysis of a Stepped-Wedge Cluster Randomized Trial.","authors":"Vincent Israel Opoku Agyapong, Lola Ibraimova, Reham Shalaby, Belinda Agyapong, Wanying Mao, Ernest Owusu, Hossam Eldin Elgendy, Ejemai Eboreime, Peter H Silverstone, Pierre Chue, Wesley Vuong, Shireen Surood, Frank McMaster, Andrew J Greenshaw, Arto Ohinmaa","doi":"10.2196/93954","DOIUrl":"10.2196/93954","url":null,"abstract":"<p><strong>Background: </strong>Psychiatric hospitalizations are a major driver of mental health-related healthcare costs, with readmission risk and service utilization highest in the months following discharge. Scalable, low-cost post-discharge interventions that reduce inpatient utilization are therefore of high policy relevance.</p><p><strong>Objective: </strong>This secondary exploratory economic study used linked administrative healthcare utilization data to evaluate the economic impact of supportive text messaging, alone and in combination with peer support, following discharge from acute psychiatric care.</p><p><strong>Methods: </strong>This secondary exploratory economic evaluation was conducted alongside a pragmatic stepped-wedge cluster-randomized trial in Alberta, Canada. Adults discharged from acute psychiatric inpatient care received treatment as usual (TAU), supportive text messaging (SMS), or supportive text messaging with or without peer support (SMS with or without PSS). Direct health system costs, including hospital care and physician costs, were assessed using administrative data for 6-monthsand 12-months before and after the index admission. Difference-in-differences analyses were used to estimate cost changes between groups.</p><p><strong>Results: </strong>At six months post-discharge, the period of greatest new costs, participants receiving SMS experienced a significant reduction in hospital care costs compared with TAU (mean difference-in-differences -$7,147; 95% CI -$12,388 to -$1,906; p = 0.01). Total healthcare costs were also significantly lower in the SMS group at six months (-$8,160) relative to TAU. Sensitivity analyses demonstrated that the direction and statistical significance of the primary findings remained stable across alternative intervention costing assumptions and analytic specifications. No significant cost differences were observed at 12- months. The addition of peer support did not result in incremental cost savings at either time point.</p><p><strong>Conclusions: </strong>Supportive text messaging was associated with significant reductions in hospital care and total healthcare utilization costs during the 6-month post-discharge period compared with treatment as usual These findings support the integration of cost-effective and scalable digital interventions into routine psychiatric discharge pathways to help improve system efficiency in publicly funded health systems.</p><p><strong>Clinicaltrial: </strong>ClinicalTrials.gov NCT05133726.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":" ","pages":""},"PeriodicalIF":7.4,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13495993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148438501","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":"AI Agents Are Coming: 5-Stage Taxonomy of Language-Based AI Systems for Psychiatry, Psychotherapy, and Counseling.","authors":"Raphael Schuster, Constantin Yves Plessen, Per Carlbring, Andreas Walther","doi":"10.2196/91746","DOIUrl":"10.2196/91746","url":null,"abstract":"<p><p>The rapid evolution of large language models has accelerated the development of agentic artificial intelligence (AI) systems capable of pursuing autonomous goals, creating an urgent need for structural frameworks in psychiatry and psychotherapy. While existing classifications often draw parallels to autonomous driving, this paper argues that the mental health domain requires a distinct, domain-specific theoretical foundation, as the 2 domains differ fundamentally in their semantic, ideographic, and epistemological demands. Furthermore, they differ in their end goals, for which we introduce terms such as agentic guidance capability. To guide clinicians and researchers through these developments, we propose a 5-stage taxonomy for language-based AI systems that differentiates technical functionality from clinical effectiveness. The taxonomy progresses from level 1 (knowledge level), in which systems perform static benchmark tasks, to level 2 (elementary level), characterized by dynamic engagement in specific therapeutic microskills. At level 3 (integration level), systems achieve consistency across and within modules, as well as basic case-level conceptualization suitable for blended therapy under human oversight. Level 4 (saturation level) describes therapist-in-the-loop systems capable of autonomous functioning with minimal supervision, whereas level 5 (mastery level) represents AI systems that are technically capable of performing autonomous therapy. By distinguishing technical functionality from clinical effectiveness, we conclude that level 4 or level 5 performance does not automatically translate into full treatment effectiveness, even if high treatment fidelity can be achieved. We conclude by emphasizing the need to shift benchmarking from static knowledge tests to dynamic evaluations of therapeutic capabilities in order to safely navigate the transition toward autonomous care.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e91746"},"PeriodicalIF":7.4,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13408468/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148431311","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":"Digital Mental Health Research Priorities, Revisited for the AI and Large Language Model Era.","authors":"Max Valentin Birk, Shruti Kochhar, Keris Myrick, Stephen M Schueller, John Torous","doi":"10.2196/104118","DOIUrl":"10.2196/104118","url":null,"abstract":"<p><strong>Unlabelled: </strong>Digital mental health has become an established part of mental health care, but the rapid arrival of large language models and other artificial intelligence (AI) tools has refocused attention on the evidence needed to guide the field. This editorial updates the research priorities articulated by JMIR Mental Health in 2023, while reaffirming their emphasis on equity, replicability, privacy, efficacy, and engagement. While the importance of these priorities has not changed in recent years, the urgency with which they must now be applied has. As digital tools become more clinically consequential, research must move beyond demonstrating that a technology is feasible, usable, or novel. The field now needs studies that clarify how these tools work, for whom they are beneficial, under what conditions they may cause harm, and how they can be ethically integrated into care. We call for research that is transparent about the technologies being studied, grounded in meaningful clinical questions, attentive to safety, and designed to produce knowledge that remains useful as specific products and models change.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e104118"},"PeriodicalIF":7.4,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13354120/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148425519","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":"From Alliance to Nexus: Rethinking Digital Therapeutic Relationships.","authors":"Daniela B Cadena, Juliane U Walther, Christian A Brünahl","doi":"10.2196/89378","DOIUrl":"10.2196/89378","url":null,"abstract":"<p><p>In traditional human psychotherapy, the therapeutic alliance (TA) is regarded as a fundamental factor that describes the client-therapist relationship, mainly due to strong evidence demonstrating its impact on treatment outcomes regardless of theoretical orientation. More recently, advances in artificial intelligence (AI) and other technologies have led to the emergence of the concept of digital TA, used to characterize the relationship between clients and AI-based therapeutic systems. This approach replicates human dynamics but overlooks key differences between human therapists and digital agents. Prematurely translating the concept of TA into the digital context fails to address issues such as the sycophantic tendencies of current systems and the inherent limitations of algorithmic interaction. We propose the digital therapeutic nexus, a framework that recognizes these differences and provides a set of structured criteria for categorizing digital interactions into 3 progressive levels. This Viewpoint argues that only at the highest level can parallels be drawn to the human TA and stratifies the main risks associated with each nexus level. Transitioning from the concept of alliance to that of a nexus offers a more precise conceptual basis for describing and evaluating digital therapeutic relationships, with implications for research, design, and the ethical development of AI-based mental health interventions.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e89378"},"PeriodicalIF":7.4,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13376847/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148377447","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":"Use of a Conversational Agent for Training Mental Health Professionals in Suicide Safety Planning: Pilot Feasibility and Acceptability Study.","authors":"Bénédicte Nobile, Zohar Elyoseph, Elia Gourguechonbuot, Josselin Guyodo, Jordi Garcia, Inbar Levkovich, Emilie Olie, Yuval Haber, Yossi Levi-Belz, Philippe Courtet","doi":"10.2196/88440","DOIUrl":"10.2196/88440","url":null,"abstract":"<p><strong>Background: </strong>Safety planning is recognized as one of the most effective interventions for reducing suicidal behaviors. The quality of safety plans strongly depends on professional training, and traditional methods, such as role-playing, are time-consuming and offer limited opportunities for repetition across diverse patient profiles. Generative artificial intelligence (GenAI) may provide innovative solutions by offering accessible, flexible, and realistic training environments.</p><p><strong>Objective: </strong>This pilot study aimed to evaluate the acceptability and feasibility of a GenAI-based simulator designed to train mental health professionals in safety planning.</p><p><strong>Methods: </strong>Twenty nurses and nursing assistants from psychiatric units in a French university hospital participated in a pre-post, single-session evaluation. After self-rating their ability, competence, and willingness to manage patients experiencing suicidal ideation, participants interacted individually with the text-based simulator for 20 minutes to perform a safety plan with a chatbot, then completed postsimulation acceptability items, and open-ended feedback. Composite scores were computed: acceptability (eg, helpfulness; 0-40), realism (eg, looking like real interaction with patient; 0-20), and challenge (eg, emotional challenge; 0-30). Pre-post changes were tested (Wilcoxon signed-rank test), and age-group comparisons were performed.</p><p><strong>Results: </strong>Acceptability was high (mean 31.9/40, SD 5.3; median 32, IQR 7), realism moderate-to-high (mean 15.1/20, SD 4.1; median 15, IQR 5.25), and challenge manageable (mean 17.0/30, SD 8; median 18, IQR 12.5). Participants rated usefulness (mean 7.65/10, SD 1.57; median 8, IQR 1.57), perceived learning (mean 7.6/10, SD 1.79; median 8, IQR 2), recommendation to use the chatbot for training (mean 8.3/10, SD 1.59; median 9, IQR 2.25), and feedback quality (mean 8.35/10, SD 1.27; median 8.5, IQR 1.25) favorably. Willingness to actively manage patients experiencing suicidal ideation significantly increased postsimulation (P=.03). Younger participants reported higher acceptability (P=.04) and realism (P=.03). Participants reported minimal concerns regarding the simulator's use.</p><p><strong>Conclusions: </strong>This pilot study demonstrates that a GenAI-based simulator for safety planning is feasible and highly acceptable among experienced mental health professionals. The findings are promising and warrant larger, controlled trials to assess impacts on training effectiveness and patient outcomes.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e88440"},"PeriodicalIF":7.4,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13317675/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148363307","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":"Governing Ethical Tensions in Youth Digital Mental Health Research.","authors":"Kristin Berre Ørjasæter, Stefan Rennick-Egglestone, Kristin Øksendal Børresen, Cathrine Fredriksen Moe, Anna Leiler, Helga DI Sigurdardóttir, Victor Manuel Pèrez Colado, Malle Vogelsang, Teddy Nambazira, Jone Trovåg, Victor Valderaune, Ingunn Skjesol, Fiona Ng, Ottar Ness, Mike Slade","doi":"10.2196/88622","DOIUrl":"10.2196/88622","url":null,"abstract":"<p><strong>Unlabelled: </strong>As mental health research increasingly aims to generate societal impact, researchers operate at the intersection of innovation and ethical responsibility. Drawing on experiences from the cocreated NEON Young Norway Study on youth recovery narratives, this viewpoint identifies four ethical tensions that arise from the existing governance frameworks in youth digital mental health research: (1) balancing safeguarding against harm with youth participation, (2) protecting privacy without undermining authentic storytelling, (3) governing unpredictable outcomes of cocreated research, and (4) meeting ethical and legal standards while ensuring youth-friendly communication. These tensions highlight limitations in mental health research that adopts participatory and digital approaches, as this often struggles to accommodate iterative designs, narrative data, and cross-sector collaboration. We argue that responsible youth mental health research requires ethics to be understood as a dynamic, participatory practice that supports safe and equitable inclusion, rather than having a focus on risk prevention. Ethical governance, therefore, needs to evolve toward proportionate, context-sensitive approaches that can enable innovation while protecting young people's rights, agency, and voices.</p>","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e88622"},"PeriodicalIF":7.4,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13318201/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148363223","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":"Coproduction Without Youth? Closing the Participation Gap in Digital Mental Health Research.","authors":"Charlotte Blease, Maria Tibbs, Andreas Balaskas, Shaun Liverpool, Josefin Hagström, Amanda Fitzgerald","doi":"10.2196/91739","DOIUrl":"10.2196/91739","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Young people are among the most intensive users of digital and generative artificial intelligence (GenAI)-enabled mental health tools, yet they remain underrepresented in the research and design processes that shape these technologies. Although participatory approaches such as co-design and patient and public involvement are widely endorsed as best practices, youth involvement in digital youth mental health (DYMH) research is often inconsistent, superficial, or limited to late-stage consultation. This participation gap risks producing interventions that are misaligned with young people's lived experiences, priorities, and vulnerabilities, particularly in the context of rapidly evolving and scalable GenAI systems. This Viewpoint aims to reexamine the underlying drivers of the participation gap in DYMH research; clarify how participation is conceptualized and implemented across disciplines; and propose concrete, actionable recommendations to support more meaningful and consistent youth involvement across the research life cycle. We draw on interdisciplinary literature from digital mental health, human-computer interaction, child-computer interaction, and health research policy. Our Viewpoint integrates conceptual frameworks (eg, Lundy's model of participation), existing reviews of co-design practices, and emerging evidence on GenAI in mental health. We adopt a life cycle-oriented perspective to examine how youth participation is distributed across stages of research and development, including problem formulation, design, implementation, and evaluation. We identify 3 interrelated drivers of the participation gap. First, conceptual and linguistic fragmentation obscures what participation entails in practice, with terms such as co-design, participatory design, user-centered design, and patient and public involvement used inconsistently across disciplines. Second, youth involvement is uneven across the research life cycle, with participation often concentrated in early ideation or usability testing but largely absent from upstream decision-making and downstream evaluation. Third, institutional barriers-including ethics review processes, consent requirements, funding constraints, and adult-centric research norms-systematically limit meaningful youth partnership. These challenges are amplified in the context of GenAI, where opaque \"black box\" systems, simulated therapeutic interactions, and rapid deployment cycles introduce distinct risks if youth perspectives are not integrated. We propose a set of minimum expectations to address these gaps, including explicit specification of participatory models, life cycle mapping of youth involvement, reporting of youth influence on decisions, dedicated funding for participation, proportional ethics frameworks, and mechanisms for youth-informed governance of GenAI systems. Closing the participation gap in DYMH research is both an ethical imperative and a practical necessity. Moving beyond aspirational commitme","PeriodicalId":48616,"journal":{"name":"Jmir Mental Health","volume":"13 ","pages":"e91739"},"PeriodicalIF":7.4,"publicationDate":"2026-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13347077/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148320015","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}