Background: Design research on AI technologies for mental health has expanded rapidly, yet existing work has largely focused on practitioners’ perspectives within isolated therapeutic stages or specific services. As a result, there is limited understanding of how practitioners view the role of AI across the full therapeutic journey, including assessment, diagnosis, and treatment, or how these perspectives can be translated into actionable and ethically grounded design guidance. This lack of stage-specific guidance introduces several risks: (1) the development of AI tools that practitioners may not trust or adopt, (2) heightened ethical concerns, particularly in diagnosis where bias and erosion of human judgment are most likely, and (3) missed opportunities to leverage AI to support ongoing assessment and treatment adaptation. Objective: This study aimed to explore mental health practitioners’ perspectives on how AI may support or hinder therapeutic practice across all 3 therapeutic stages, with particular attention to their ethical considerations. Methods: We conducted semistructured interviews with 18 mental health practitioners to explore how AI may support or hinder therapeutic practice across assessment, diagnosis, and treatment. Data were analyzed thematically, and ethical challenges were organized using 4 biomedical principles. This study received approval from the Lancaster University Institutional Ethics Committee (ID 3530). Results: Findings suggest a stage-specific pattern: practitioners identified valuable roles for AI in supporting clinical assessment and treatment, while expressing strong resistance to autonomous AI diagnosis, which was regarded as the most ethically sensitive stage. Across contexts, AI was seen as supporting and validating, rather than replacing, clinical judgment. Ethical concerns were organized using these principles, with key issues including data validity, inclusivity, privacy, transparency, and explainability. Grounded in these findings, four design directions are proposed: (1) AI-enabled clinical assessment hubs for analyzing multimodal patient data to support transparent decision-making; (2) natural language processing-based tools to enable richer understanding of patients’ lived experiences; (3) new models of trust to support ethically sensitive AI-assisted diagnostic decision-making; and (4) large language model–powered personalized and adaptive mental health support systems that maintain human-AI partnership and preserve practitioners’ central role in care. Conclusions: This study provides a stage-specific understanding of practitioners’ perspectives on AI use across assessment, diagnosis, and treatment and systematically frames ethical challenges using biomedical principles. The findings translate practitioner insights into actionable design guidance for ethically informed AI-supported mental health practice.
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Outcomes of the Integrated Scaling Approach: scaling an evidence-based employment intervention in public mental health systems
Evidence-based practices (EBPs) in supported employment (SE) improve vocational outcomes for individuals with serious mental health conditions, yet their implementation and sustainment at scale remain limited. Thinking Skills for Work (TSW), a cognitive remediation intervention, is an EBP that increases vocational outcomes for SE participants. This study evaluated the Integrated Scaling Approach (ISA), designed to increase adoption of EBPs, such as TSW, across service systems. A field trial of ISA was conducted across SE programs in a single U.S. state. ISA strategies addressed scale-up by building stakeholder engagement and staff-organizational-system capacity, across three phases (preparation, implementation, and sustainment). Using a concurrent mixed-methods design, quantitative data assessed TSW implementation, while qualitative interviews and focus groups examined facilitators and barriers to scaling and sustainment. Nine agencies, managing twelve SE sites, enrolled in the study. Eight completed all ISA phases. Nineteen staff achieved TSW certification, and sixteen completed a Train-the-Trainer program. Eighty-five clients received TSW during the trial. The state modified its evaluation process to monitor TSW implementation. Qualitative findings indicated that structured training, implementation team engagement, and intervention flexibility, facilitated adoption. Long term sustainment was not achieved due to workforce shortages, resource constraints, and the absence of sustained system-level support, exacerbated by the COVID-19 pandemic. The ISA promoted short-term adoption and workforce capacity for an evidence-based employment intervention across multiple organizations, but not long-term sustainment. These findings underscore the necessity of integrating long term system-level policies and funding mechanisms with implementation strategies to achieve sustainable scale-up of EBPs in mental health systems.
Sumud as a framework for collective resilience: a systematic review of implications for transcultural psychiatry and psychotherapy
BackgroundResilience is increasingly understood as a dynamic, ecological process; however, prevailing psychiatric models continue to emphasize individual traits, thereby neglecting collective and culturally embedded forms of endurance. Sumud (Arabic: صمود), broadly translating as steadfastness, perseverance, and endurance, sustains identity, dignity, and daily life under chronic adversity across the Arab world and functions as a relational and ethical orientation. This review examines sumud as a resilience framework for transcultural psychiatry and psychotherapy.AimsTo synthesize conceptualizations of sumud in relation to resilience, coping, and adaptation, and to evaluate implications for narrative, family-based, group, community-oriented, and arts-informed therapeutic approaches.MethodsA PRISMA 2020-guided systematic narrative review was conducted. Four electronic databases (PubMed, Scopus, Web of Science, and Embase) were searched covering publications up to 1 June 2026. English-language studies were eligible if they explicitly examined sumud as a cultural, psychological, or collective construct with relevance to resilience, coping, or psychotherapy. Eligible publication types included qualitative, quantitative, and mixed-methods empirical studies; theoretical and conceptual papers; ethnographies; narrative analyses; and reviews. Data were thematically synthesized using a predefined extraction matrix. The review was registered with PROSPERO (CRD420261279052).ResultsThirty-nine studies met the inclusion criteria. Descriptively sumud emerged as a multilevel, collective form of resilience enacted through family systems, intergenerational narratives, cultural practices, and institutional structures. Substantively, it supported meaning-making, emotional regulation, and identity continuity. Critically, ethical tensions and cumulative burdens were documented, particularly for women, caregivers, and professionals., and rigorously evaluated, sumud-informed psychotherapeutic interventions remain scarce, notwithstanding a general preference in mental health studies for social-ecological models and narrative, family-based, group, and arts-based therapeutic approaches.ConclusionsTheoretically, sumud challenges individualistic psychiatric frameworks by offering a culturally embedded, collective model of resilience. Clinically, it urges clinicians to engage with patients’ narratives, relational worlds, and cultural practices, while remaining attentive to the costs of endurance. Prospectively, in the context of ongoing conflicts and humanitarian crises affecting parts of the Middle East and Gulf region, sumud warrants renewed scholarly and clinical attention for the development of culturally responsive, resilience-informed psychotherapies.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD420261279052.
Context presentation and native conversation structure in large language model responses to escalating suicide risk: a controlled multimodel evaluation
BackgroundLarge language models are increasingly used for informal mental health support, yet their safety during escalating suicide-risk conversations may depend on how prior information is presented. Native multi-turn conversations and reconstructed cumulative prompts differ not only in the presence of prior model responses but also in prompt reconstruction, information concentration, message positioning, explicit integration cues, and conversation-state processing.ObjectiveThis study compared suicide-risk recognition, direct safety inquiry, response urgency, and timely real-world intervention across isolated current-turn prompts, reconstructed cumulative user-only prompts, and native continuous multi-turn conversations.MethodsWe conducted a controlled repeated-measures evaluation of ChatGPT, Gemini, and Doubao using 12 standardized five-turn trajectories: 4 direct suicide-risk trajectories, 4 implicit or internally inconsistent risk trajectories, and 4 non-suicidal high-distress controls. Each trajectory was evaluated under three context-presentation formats. The 24 model-trajectory combinations were treated as matched repeated-measures units nested within 8 independent risk-trajectory blocks. Primary contrasts were estimated using exact trajectory-level sign-flip tests and trajectory-block bootstrap confidence intervals. Turn-level outcomes were analyzed using multilevel mixed-effects models. Exploratory condition-by-model heterogeneity was assessed using a trajectory-blocked exact permutation sensitivity analysis, with a trajectory-clustered interaction model used only as a secondary asymptotic check.ResultsTimely appropriate intervention occurred in 10/24 isolated current-turn observations (41.7%), 21/24 reconstructed cumulative observations (87.5%), and 12/24 native continuous observations (50.0%). On average across the three systems, reconstructed cumulative presentation exceeded isolated input by 45.8 percentage points (95% trajectory-block bootstrap CI, 25.0 to 66.7; Holm-adjusted exact P = .031), whereas native continuous performance was 37.5 percentage points lower than reconstructed cumulative performance (95% trajectory-block bootstrap CI, −50.0 to −25.0; Holm-adjusted exact P = .031). Exploratory model-specific analyses indicated substantial heterogeneity: the native-versus-reconstructed contrast was largest for Doubao, smaller and statistically imprecise for Gemini, and absent for ChatGPT.ConclusionsOn average across the three evaluated systems, reconstructed cumulative user-only prompts outperformed native continuous conversations, although exploratory model-specific patterns were heterogeneous. Because the formats also differed in prompt reconstruction, information salience, message positioning, explicit integration instructions, and native conversation-state processing, the contrast cannot isolate the causal effect of prior model responses.
Content, Engagement, and Information Quality of Borderline Personality Disorder Videos on TikTok: Mixed Methods Analysis
Background: TikTok has become a major source of mental health information, yet concerns persist regarding the quality and reliability of psychiatric content disseminated on the platform. While misinformation has been documented for several mental disorders, no study has specifically examined how borderline personality disorder (BPD) is portrayed on TikTok. Objective: This study aims to characterize TikTok content related to BPD by describing its thematic content, engagement patterns, presenter characteristics, and indicators of information quality using a mixed methods secondary analysis. Methods: This mixed methods observational study performed a secondary analysis of a previously established dataset of publicly available TikTok videos related to mental health. A total of 207 videos addressing BPD or BPD-like traits were included. Quantitative analyses summarized video characteristics, engagement metrics, presenter backgrounds, content type, intent, and authenticity indicators using descriptive statistics. Qualitative data were analyzed using reflexive thematic analysis following Braun and Clarke’s methodology to identify recurrent narratives related to BPD. Results: Among the 207 included videos, 185 (89.4%) were in English and 199 (96.1%) targeted the general public. Most creators (n=124, 59.9%) did not disclose professional credentials, whereas psychiatrists (n=18, 8.7%) and psychologists (n=16, 7.7%) represented the largest identified professional groups. Seven overarching themes were identified: understanding personality disorders, treatment and management, interpersonal relationships, myths and misconceptions, co-occurring disorders, personal experiences, and diagnosis and classification. Videos focused on personal experiences generated the highest audience engagement (mean weighted likes 2389, SD 6529; favorites 333, SD 707; shares 117, SD 287), whereas treatment-focused videos demonstrated substantially lower engagement (mean weighted likes 222, SD 360; favorites 54, SD 77; shares 19, SD 40). Opinion-based or mixed-content formats predominated across most themes. Reference-based information remained limited, ranging from 0% to 33.3% depending on thematic category, while misinformation was observed across multiple themes, particularly understanding personality disorders (20/81, 24.7%) and diagnosis and classification (14/48, 29.2%). Experiential and relational narratives were substantially more prominent and engaging than evidence-based psychoeducational content. Conclusions: TikTok discourse surrounding BPD is dominated by experiential narratives that foster engagement but frequently rely on opinion-based rather than evidence-based information. Although many videos may provide validation and reduce stigma, the limited use of references and the persistence of misinformation highlight the need for the greater involvement of mental health professionals in producing accessible, accurate, and engaging digital content. To our knowledge, these findings provide the first focused overview of BPD-related content on TikTok and may inform future strategies to improve the quality of online mental health information.
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Supporting Older Adults Remotely
Conditions: Severe Mental Illness
Interventions: Behavioral: Supporting Older Adults Remotely (SOAR); Behavioral: Peer support as usual
Sponsors: Dartmouth-Hitchcock Medical Center; National Institute of Mental Health (NIMH)
Not yet recruiting
Interventions: Behavioral: Supporting Older Adults Remotely (SOAR); Behavioral: Peer support as usual
Sponsors: Dartmouth-Hitchcock Medical Center; National Institute of Mental Health (NIMH)
Not yet recruiting
Understanding the Influence of Substance Use, Mental Health, and Stigma on Smoking Behavior Among People Living With HIV: Rapid Qualitative Analysis
Background: In Vietnam, an upper-middle-income country, the majority of people living with HIV smoke. Vietnam has established quitline services to support this population, but they remain underused. Text messaging is widely used in Vietnam, and studies in other countries have shown that text messaging interventions can promote smoking cessation. Our goal was to conduct a formative study to inform the development of a text messaging intervention to increase access to quitline services and promote smoking cessation among people living with HIV who smoke in Vietnam. Objective: This study aimed to identify factors influencing smoking behaviors among people living with HIV in Vietnam through qualitative interviews to inform a tailored text messaging intervention. Methods: In October 2022, study staff conducted 30- to 45-minute qualitative interviews with 20 people living with HIV from clinics in Hai Phong and Quang Ninh provinces, Vietnam. Interviews explored factors that influenced smoking, such as substance use, mental health, HIV stigma, social context, and health. A rapid qualitative analysis approach was used to synthesize themes from the data, including identifying key domains based on prior literature, developing a semistructured interview guide, and organizing data within domains to support iterative theme development. These interviews were used to develop prompts to guide people living with HIV who smoke in writing peer messages for a text messaging intervention. Results: Across 6 themes, participants described smoking as part of their everyday lives, shaped by social situations, stress, alcohol use, and their experiences living with HIV. Social smoking and early initiation were important influences on smoking behaviors, whereas financial concerns and protecting family members and others from secondhand smoke promoted cessation. Some participants used smoking to cope, whereas others wished to quit for better health. HIV stigma was a major contributor to smoking, with many participants describing increased smoking after diagnosis. Participants suggested that cessation support should be better tailored to their needs. Conclusions: Smoking behaviors among people living with HIV are shaped by overlapping influences, including societal norms, mental health, HIV-related stigma, and other structural stressors. An understanding of these overlapping factors can inform the development of text-based interventions that offer effective cessation support tailored to this population. Trial Registration: ClinicalTrials.gov NCT05863923; https://clinicaltrials.gov/study/NCT05863923
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App-Based Stabilization Phase Within Blended Trauma-Focused Cognitive Behavioral Therapy With Compassion for Adolescents With Posttraumatic Stress Disorder: Formative Qualitative Study
Background: Digital tools may support early phases of trauma therapy for adolescents, yet little is known about how an app-based stabilization phase functions in routine child and adolescent psychiatry clinics. To our knowledge, no previous study has qualitatively examined a compassion-integrated, app-based stabilization phase delivered before trauma processing within trauma-focused cognitive behavioral therapy (TF-CBT) for adolescents. Objective: This formative qualitative pretrial study explored the acceptability, feasibility, and contextual fit of an app-based stabilization phase within blended TF-CBT with compassion (bTF-CBT-C) for adolescents with posttraumatic stress disorder (PTSD). The aim was to inform the refinement of intervention content, caregiver support, and clinical workflow prior to a planned pilot randomized controlled trial (RCT). Methods: Four adolescent girls with PTSD (aged 14‐16 years) completed a 5-week app-based stabilization program integrating TF-CBT coping skills and compassion-focused practices, while 5 caregivers received parallel content in a nonapp format. Three adolescents and 4 caregivers participated in postintervention semistructured interviews, and 4 clinicians completed a brief open-ended survey. Data were analyzed using reflexive thematic analysis. Results: One overarching theme, Navigating digital stabilization within shifting conditions,” captured how engagement fluctuated with emotional capacity, cognitive load, relational dynamics, and logistical stability. Adolescents and caregivers experienced the intervention content as grounding and meaningful but difficult to sustain amid fatigue, school pressure, neurodivergent attention patterns, and family strain. Clinicians similarly noted varying capacity, the need for scaffolding, and the importance of reminders and smooth access. Clear content could exceed users’ cognitive bandwidth; adolescents preferred autonomy, while caregivers were unsure how to support them; and technical friction sometimes disrupted momentum. Across the groups, participants described grounding and compassion-based practices as supporting emotional safety, shared understanding, and readiness for trauma-focused work. Conclusions: The findings suggest that app-based stabilization within bTF-CBT-C may be acceptable and potentially feasible for adolescents with PTSD, their caregivers, and clinicians. Feasibility appears to depend on flexible pacing, cognitive accessibility, caregiver guidance, and technical reliability. The study identifies candidate refinements to be evaluated in the pilot RCT and provides preliminary insight into how compassion-integrated digital stabilization may support preparation for trauma-focused therapy.
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A Digital Tool for Culturally Responsive Reflection and Case Conceptualization in First-Line Services to Support Children With a Refugee Background: Development and Usability Study
Background: In 2023, over 117 million people were forcibly displaced worldwide, 40% of them children. Refugee children are at higher risk for posttraumatic stress disorder, depression, and anxiety, while professionals may struggle to address mental health and trauma-related concerns across unfamiliar cultural contexts. The Psychiatry Assisting the Culturally Diverse Community in Creating Healing Ties (PACCT) approach supports culturally responsive care for culturally diverse families, but first-line professionals often lack practical support to apply such an approach in routine care. Objective: The study aimed to (1) identify professionals’ support to inform the development of Implementing PACCT through a Culturally Contextualized Tool (IMPACCT), a digital decision-support tool; (2) map these needs onto the initial IMPACCT conceptualization; and (3) gather initial feedback from professionals to guide further refinement. Methods: We conducted a qualitative descriptive study in 3 phases. First, we analyzed 905 anonymized help desk questions submitted between May 2021 and November 2023 to Solentra, a Belgian center of expertise providing transcultural mental health support and consultation for refugees and other vulnerable migrant populations. Questions were coded using a predeveloped framework to identify recurrent professional needs. Second, we mapped all help desk question categories onto the different components of the first conceptualization of IMPACCT to ensure that its content reflected users’ questions and expectations. Third, 19 professionals working with refugee and migrant populations in Belgium were recruited through an open call between December 2024 and February 2025 using convenience sampling. After hands-on experience with a first iteration of IMPACCT, they provided feedback during semistructured interviews. These interviews were subsequently analyzed using deductive qualitative content analysis. Results: In the help desk questions, trauma-related concerns were the most common, followed by anxiety/stress and depressive symptoms. Acculturation was the most dominant culture-migration category. Most contexts were family- and school-oriented, and professionals were primarily asking for supervision or concrete next-step guidance. The interviews (N=19) found that the professionals thought that IMPACCT provided them with better-structured and early reflection, lessened some of the decision-making burden, and enabled a more structurally informed understanding of culture in the context of migration. Reported barriers included the time required and a lack of adaptation in workflow, with more experienced professionals reporting less perceived value. Additionally, participants suggested using IMPACCT as a training and/or supervision aid in first-line services and as standard decision support in ambulatory and inpatient care. Conclusions: The study offers first insights into the possible conceptualization of a digital decision-support tool for first-line professionals to help them support children with a refugee background. Further technical optimization of the tool, also taking into account first-user feedback, is, however, necessary before subsequently exploring its efficacy as well as effectiveness in strengthening first-line professionals’ competencies in working with the vulnerable population.
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Child and Adolescent Mental Health Misinformation on TikTok: Cross-Sectional Mixed Methods Study
<strong>Background:</strong> TikTok is an important source of mental health information for children, adolescents, and young adults, but the accuracy of psychoeducational content remains uncertain. Misleading information may be particularly consequential for younger users, who may have limited digital and health literacy. <strong>Objective:</strong> This study aimed to characterize misinformation and disinformation in TikTok content related to child and adolescent mental health, identify mental health topics disproportionately represented in misleading content, examine whether platform-observable video characteristics could discriminate videos containing misinformation, and explore how viewers responded to this content. <strong>Methods:</strong> We conducted a cross-sectional mixed methods secondary analysis of 122 child and adolescent mental health videos identified from a previously collected dataset of 1000 publicly available TikTok videos. Videos were independently coded for content, intent, authenticity, clinical topic, presenter characteristics, and engagement. An L2-penalized logistic regression using only platform-observable characteristics was evaluated using stratified 5-fold cross-validation; 95% CIs for predictive metrics were estimated using 5000 stratified bootstrap resamples of out-of-fold predictions. Disinformation was analyzed descriptively because only 2 cases were identified. An exploratory thematic analysis was conducted on 116 selected viewer comments. <strong>Results:</strong> Misinformation was identified in 21 of 122 (17.2%; 95% CI 11.5%-24.9%) videos, whereas disinformation occurred in 2 of 122 (1.6%; 95% CI 0.5%-5.8%). Misinformation was most frequent among videos addressing autism spectrum disorders (11/27, 40.7%), impulse control disorders (1/3, 33.3%), and mood disorders (4/13, 30.8%). Professional credentials were not disclosed in 63 of 122 (51.6%) videos, and only 9 of 122 (7.4%) referenced an external scientific source. The observable-feature model demonstrated modest discrimination, with an area under the receiver operating characteristic curve of 0.70 (95% CI 0.56-0.82), balanced accuracy of 0.69 (95% CI 0.58-0.79), recall of 0.67 (95% CI 0.48-0.86), and <i>F</i><sub>1</sub>-score of 0.44 (95% CI 0.32-0.56). Qualitative analysis identified 5 recurring patterns in viewer responses: sharing and validation of lived experiences, discussion of diagnosis and misdiagnosis, frustration with mental health care, peer support and encouragement, and exchanges about treatment and medication experiences. <strong>Conclusions:</strong> A substantial minority of the analyzed TikTok videos contained misinformation, with particularly high proportions among some neurodevelopmental and mood-related topics. Platform-observable characteristics provided only modest discrimination of misinformation, underscoring the difficulty of identifying misleading mental health content from surface-level features alone. Viewer comments further showed that TikTok mental health content is embedded within broader processes of self-interpretation, diagnostic discussion, peer validation, and treatment-related exchange. These findings support the need for developmentally appropriate digital health literacy initiatives and accurate, transparently sourced psychoeducational content for young social media users. <strong>Trial Registration:</strong>
