IntroductionAutism Spectrum Disorder (ASD) is a neurodevelopmental condition requiring long-term, coordinated, and multidisciplinary care. Although ASD services in Tunisia have improved, coordination across health, education, and social sectors remains limited, affecting equitable access and continuity of care. This study aimed to develop a national, evidence-based clinical practice guideline for the screening, diagnosis, and management of children and adolescents with ASD adapted to the Tunisian healthcare context.Assessment of guideline development and practice implicationsThe guideline was developed by the Tunisian Society of Child and Adolescent Psychiatry and accredited by the National Authority for Evaluation and Accreditation in Health. Using the ADAPTE framework, a multidisciplinary panel adapted international ASD guidelines to the Tunisian context. After systematic searches and AGREE II appraisal, the 2023 Singapore ASD guideline was selected as the main source document. Recommendations were adopted, adapted, or newly developed according to contextual relevance and applicability. An additional literature search was performed to incorporate high-level evidence published between June 2023 and January 2025.Actionable recommendationsThe final guideline includes 96 evidence-based recommendations and 87 good practice points organized into ten chapters, covering the screening, diagnosis, intervention, and follow-up of autism spectrum disorder in children and adolescents across all levels of care in Tunisia. This article summarizes the key practice-oriented recommendations across these chapters.ConclusionThis first Tunisian ASD guideline aims to harmonize practices, improve the quality of care, and strengthen integrated care pathways.
Incorporating Data From Text Messages and Email Into Psychotherapy: Randomized Controlled Trial
Background: As digital communication becomes central to daily life, psychotherapy increasingly has access to patients’ electronic media data. Although digital phenotyping has been widely studied, less is known about whether incorporating personal communication data, such as text messages, improves clinical outcomes in psychotherapy. Objective: This study aimed to determine whether integrating personalized text message data into psychotherapy improves depression, anxiety, health-related quality of life, and therapeutic alliance and to examine whether increased access to collateral information influences clinical decision-making. Methods: The Electronic Media and its Impact on Psychotherapy (EMAP) study was a randomized controlled trial conducted in adult and geriatric outpatient and partial hospitalization settings at an academic psychiatric hospital. Participants receiving psychotherapy for primary depression or anxiety (n=101) were randomized to electronic media–enhanced therapy (EME; n=52) or treatment as usual (TAU; n=49). In EME, research staff reviewed participants’ text messages prior to sessions using personalized mood-related key terms and presented aggregated findings on a Health Insurance Portability and Accountability Act (HIPAA)–compliant clinician dashboard. TAU participants received standard care without message review. Outcomes included change scores for the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), the 36-item Short Form Health Survey (SF-36), and the Working Alliance Inventory–Short Revised (WAI-SR). Linear regression and nonparametric tests compared groups. Moderation analyses assessed whether the frequency of information access influenced treatment changes. Results: No statistically significant between-group differences were observed in anxiety or working alliance. Among participants with SF-36 follow-up data (n=65), EME participants demonstrated greater improvement in the pain subscale. Greater frequency of information access was associated with increased treatment-related changes in the EME group. Access to additional collateral information was associated with more clinical actions but not with improved distal outcomes. Conclusions: Integrating personalized text message data into short-term psychotherapy did not significantly improve depression or anxiety, and it neither improved nor worsened therapeutic alliance. However, access to greater amounts of collateral information, including electronic media, influenced clinical decision-making, suggesting nuanced and context-dependent effects. Trial Registration: ClinicalTrials.gov NCT03712267; https://clinicaltrials.gov/study/NCT03712267
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/83d4b3baa71dab46e45ae5a24d70bd35" />
Symptom Trajectories and Attendance in Face-to-Face and Online Psychiatric Follow-Up for Major Depressive Disorder and Anxiety Symptoms: Prospective Observational Cohort Study
<strong>Background:</strong> Major depressive disorder is a leading cause of disability, and access to specialist psychiatric follow-up remains limited in many settings. Telepsychiatry may reduce logistical barriers to care, but data on video-based follow-up under routine outpatient conditions in Türkiye are scarce, and comparisons of delivery modalities are frequently limited by baseline imbalance between self-selected groups. <strong>Objective:</strong> The aim of the study is to describe symptom trajectories and attendance over 6 months of routine psychiatric follow-up delivered either face-to-face or online and to examine whether outcomes differed between modalities after adjustment for baseline severity. <strong>Methods:</strong> In this prospective, nonrandomized observational cohort study, 120 adults with <i>Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition</i> (DSM-5) major depressive disorder were followed for 6 months at a university hospital psychiatry department in Ankara, Türkiye (September 2021 to May 2022). Participants entered face-to-face (n=60) or online (n=60) follow-up according to their own preference. Seven sessions were scheduled at approximately 4-week intervals; the Hamilton Depression Rating Scale (HAM-D; primary outcome), the Hamilton Anxiety Rating Scale, and DSM-5 Level 1 and Level 2 measures were administered at baseline and at sessions 1, 2, 4, and 6. Attendance was recorded at all sessions. Between-group comparisons used analysis of covariance adjusted for the corresponding baseline score and for prespecified covariates. Linear mixed models incorporating a group-by-time interaction were fitted to all available observations, and multiple imputation (<i>m</i>=20) was performed as a sensitivity analysis. <strong>Results:</strong> Depressive symptoms decreased substantially in both groups: mean HAM-D fell from 26.6 to 5.0 in the face-to-face group (81.2% reduction; Cohen <i>d</i>=4.86; <i>P</i><.001; n=43) and from 24.1 to 3.3 in the online group (86.3% reduction; Cohen <i>d</i>=6.06; <i>P</i><.001; n=49). Response rates were 41 of 43 (95.3%) and 48 of 49 (98%; <i>P</i>=.60), and remission rates were 32 of 43 (74.4%) and 43 of 49 (87.8%; <i>P</i>=.11). Unadjusted between-group differences at sessions 4 and 6 did not persist after adjustment for baseline severity (session 4: –0.47, 95% CI –1.71 to 0.77; <i>P</i>=.46; session 6: –0.79, 95% CI –2.22 to 0.65; <i>P</i>=.28), and the group-by-time interaction was not significant (<i>χ</i><sup>2</sup><sub>3</sub>=1.9; <i>P</i>=.59). Anxiety scores did not differ at any time point. Findings were unchanged under multiple imputation, and prescribing patterns were comparable. Attendance across all 7 scheduled sessions was higher in the online group overall (373/420, 88.8% vs 319/420, 76%; <i>P</i><.001), with differences at sessions 2 through 5. <strong>Conclusions:</strong> Both modalities were followed by large reductions in depressive symptoms, and between-group differences did not persist after adjustment for baseline severity. The study was not designed as an equivalence trial and cannot establish equivalence. The most consistent difference favoring online follow-up was attendance, although its reasons could not be determined. These findings characterize online psychiatric follow-up as a feasible means of maintaining continuity of routine care rather than as a more effective one.
Bridgedd, a Health Care Staff–Facing Community Resource Navigation Tool for an Urban Safety-Net Hospital: Cross-Sectional Formative Pilot Study
Background: Health care professionals in safety-net settings often rely on lengthy and inconsistently maintained community health resource lists when connecting patients with services. Bridgedd is a health care staff–facing web application designed to generate geographically and categorically filtered community resources in a unique format that makes information about each resource more accessible. Objective: This formative pilot study aimed to characterize the perceptions of behavioral health professionals toward Bridgedd’s usability, comparative value relative to existing community resource filtering and communication tools, and their intent to use it with patients if made available. Methods: We conducted a single-site, cross-sectional formative pilot of the web-based tool we developed, Bridgedd, within Grady Health System’s Integrated Behavioral Health Program between April 23 and May 14, 2026. All 21 program team members attending an all-staff meeting received a presentation about Bridgedd and were given the opportunity to try the tool and ask questions. Then, they independently evaluated it using a self-generated hypothetical patient scenario. Eleven completed an investigator-developed anonymous feedback survey assessing perceived ease of use, comparative value relative to existing tools, intent to use the tool with patients, and open-ended feedback. Quantitative responses were summarized using raw counts, and open-ended responses were summarized as descriptive observations. A post hoc descriptive analysis excluded 2 potentially direction-confused response patterns. The post hoc descriptive analysis did not materially change the overall interpretation. Results: Eleven behavioral health professionals (therapists, n=4; licensed professional counselors, n=3; social workers, n=2; mental health counselor, n=1; certified peer specialist–mental health, n=1) completed the survey. Of the 11 respondents, 9 rated the tool as very easy to use, none reported technical problems, 8 agreed or strongly agreed that Bridgedd was better than the tools they currently use to help patients navigate community health resources, and 8 reported an intent to use the tool with patients if it were made available. In the open-ended responses, 7 of the 11 respondents suggested that nothing was missing or offered no additional suggestions for improvement, while the remaining 4 open-ended responses centered on expanding mental or behavioral health resources, providing additional county coverage, including more resources within each category, and building a mechanism for updating resource information. Conclusions: In this small, single-setting formative pilot study using hypothetical patient scenarios, participating behavioral health professionals generally reported favorable perceptions of Bridgedd’s usability and potential utility. Further evaluation during routine clinical care is needed to assess actual use, workflow effects, patient experience, referral completion, and patient-level outcomes.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/a8c6492be29f23ca898f5ed912520f71" />
“There is a Place for it”—Practitioners’ Perspectives on Situated Ethical Acceptability of AI Technologies for Mental Health Practice: Qualitative Study
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.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/e0b7a00e31b823d08a966ec23073fab6" />
In-person UCLA-PEERS® program for adolescents with autism spectrum disorder in Italy: study protocol for a pilot and feasibility randomized controlled trial with pragmatic features and exploratory EEG markers of treatment response
BackgroundAdolescents with Autism Spectrum Disorder (ASD) Level 1 frequently experience persistent difficulties in peer relationships and social functioning that become more evident as social demands increase. Group-based social skills trainings represent a key evidence-based intervention for this population, yet its availability in routine clinical services is still limited. The Program for the Education and Enrichment of Relational Skills (PEERS®) is one of the most empirically supported interventions for autistic adolescents. In Italy, telemedicine delivery has shown promising results, but the effectiveness and implementation of the in-person format in real-world services have not yet been evaluated. In addition, predictors of individual response to psychosocial interventions remain largely unknown.MethodsThis study is designed as a two-arm pilot and feasibility randomized controlled trial incorporating pragmatic features, including delivery within a routine tertiary clinical service, comparison with Treatment as Usual (TAU), and allowance for ongoing concomitant clinical, educational, and pharmacological treatments. It will compare the in-person Italian adaptation of UCLA PEERS® with Treatment as Usual (TAU) at IRCCS Fondazione Stella Maris (Pisa, Italy). Thirty-six adolescents aged 11–13 years with ASD (DSM-5-TR) and Full-Scale IQ >85 will be assessed at baseline (T0) and after the 16-week intervention (T1). Randomization will use block allocation with allocation concealment until completion of baseline assessments; outcome assessors and independent ADOS–BOSCC video coders will remain blind to group assignment. The intervention includes sixteen weekly 90-minute group sessions delivered by certified providers, with parallel caregiver sessions and structured teacher contacts to promote generalization. The primary focus of this pilot trial is feasibility, assessed through recruitment, retention, session attendance, and treatment fidelity. Clinical outcomes will be examined exploratorily to provide preliminary estimates of treatment effects. The QSQ-R will serve as the prespecified principal clinical outcome for estimating change in social functioning from baseline to T1. Parent- and adolescent-report versions will be analyzed separately, considering the Social Initiative and Social Reciprocity dimensions as distinct outcomes rather than deriving a composite total score. Key secondary outcomes include social knowledge (TASSK-R), autism-related social responsiveness (SRS-2), social motivation (SSDS), social anxiety (SAS), and observational change in social-communication behaviors (ADOS–BOSCC). Emotional–behavioral functioning (CBCL; YSR) will be explored as additional secondary outcomes. Baseline electroencephalography (EEG) recorded during a gesture–word integration task will be used to derive the N400 congruency effect and to explore whether individual differences in this measure are associated with treatment response. As a pilot and feasibility trial, the study is not powered for definitive efficacy testing and will estimate feasibility, acceptability, fidelity, and preliminary effect sizes to inform future multicenter trials.DiscussionThis study will provide the first evaluation of in-person PEERS® in the Italian clinical context and test the generalizability of previous telemedicine findings in routine care. The integration of clinical and behavioral outcomes may contribute to mechanism-informed, personalized psychosocial interventions for autistic adolescents and guide the design of future confirmatory studies.Trial registration(ClinicalTrials.gov – NCT07207213 – October, 3, 2025).
The association between cognitive disengagement syndrome and language in children with attention-deficit/hyperactivity disorder
AimThis study aims to explore the association between cognitive disengagement syndrome (CDS) and three aspects of language (narrative coherence, core language, and pragmatic language) in children with ADHD, and to examine whether these associations differ from those observed in neurotypical children.MethodsIn this cross-sectional study, parents completed questionnaires about their child’s CDS and pragmatic language, while children with ADHD (n = 45) and neurotypical children (n = 38), aged 7–11 years, completed tasks of narrative coherence and core language.ResultsCDS, after adjusting for age and sex, was significantly associated with pragmatic language in children with ADHD with a large effect (β = -0.51, p = .001), while CDS was significantly associated with core language in neurotypical children with a medium effect (β = -0.34, p = .04). There was a significant group difference in the association between CDS and pragmatic language (χ²(1) = 4.44, p = .04), with a stronger association in the ADHD group. After performing sensitivity analyses including inattention as an additional covariate, the associations ceased to be significant in both groups and there were no longer significant between-group differences.ConclusionThis study examined the association between CDS and language in children with and without ADHD. The findings suggest that there may be an association between CDS and pragmatic language in children with ADHD. However, sensitivity analyses including inattention as a covariate suggest that this association may largely reflect variance shared with inattention. Consequently, the association between CDS and language may partly reflect their shared association with ADHD symptoms. As this, to our knowledge, is the first study to investigate language in relation to CDS in children with ADHD, further research is warranted.
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.
Repetitive negative thinking as a transdiagnostic bridge between childhood trauma and depression: Integrating emotion regulation flexibility, stress sensitization, and neurocognitive mechanisms
Childhood trauma is a major risk factor for depression; however, not every affected individual develops clinically significant depressive symptoms. This underscores the importance of identifying transdiagnostic mechanisms that account for vulnerability and resilience. Repetitive negative thinking (RNT), which includes both rumination and worry, has recently been framed as a more general cognitive process that may help clarify how early adverse experiences contribute to the emergence and persistence of depression. This narrative review integrates current evidence regarding RNT as a possible transdiagnostic link connecting childhood trauma to depression, with particular focus on its interactions with emotion regulation flexibility, stress sensitization, and neurocognitive processes underlying self-referential cognition, cognitive control, and threat processing. Findings from developmental psychopathology, cognitive neuroscience, and affective science indicate that childhood trauma is often associated with persistent RNT, diminished regulatory flexibility, and increased sensitivity to stress—factors that are each independently related to depressive symptoms. Emerging evidence also suggests that these mechanisms are likely interrelated and may collectively increase susceptibility to depression across diagnostic categories. Nonetheless, substantial variability in trauma features, developmental timing, outcome measures, and study designs along with the dominance of cross-sectional research, limits the ability to draw definitive causal conclusions. Taken together, the existing literature indicates the value of a transdiagnostic perspective while highlighting important methodological and conceptual shortcomings. Future longitudinal and mechanistic studies are required to specify causal pathways and to test whether interventions aimed at RNT and related regulatory processes can meaningfully enhance the prevention and treatment of depression associated with trauma.
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.