IntroductionRecovery Colleges (RCs) are educational, recovery-oriented approaches in mental health. Differences in evaluation purposes and settings may lead to diverse outcome indicators, making it important to map their use and supporting measurement evidence. This scoping review aimed to identify the outcome indicators used in RC evaluations and clarify their measured constructs, patterns of use, and reporting of reliability and validity. Methods: The review followed JBI methodology and PRISMA-ScR reporting guidance. PubMed, Web of Science, CINAHL Ultimate, ERIC, and seven databases accessed through ProQuest were searched. English-language journal articles reporting quantitative RC evaluations, including quantitative components of mixed-methods studies, were eligible. Eligible data included questionnaire scores before and after RC participation and health service utilization indicators, such as hospital admissions and service contacts. Three reviewers independently screened titles and abstracts and assessed full texts. Data were extracted collaboratively by two reviewers and independently checked by a third. Measured constructs were classified using inductive content analysis. Results: Of 336 records identified, 149 remained after deduplication and 22 articles were included. Thirty-nine measure and indicator entries were identified across three domains: intra-personal and psychological changes, behavioral and social changes, and system and environment. The Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS), including its short version (SWEMWBS), appeared in 11 articles (50.0%) and the Questionnaire about the Process of Recovery (QPR) in four (18.2%); 28 entries appeared in one article only. Fifteen articles (68.2%) cited previous psychometric information or identifiable validation literature, two (9.1%) explicitly reported within-study reliability estimates, and six (27.3%) reported neither specific psychometric evidence nor an identifiable validation citation. One article was not applicable to scale psychometrics. Conclusion: RC evaluations used diverse measures, while direct assessment of educational processes and outcomes was comparatively limited. This review mapped measurement choices rather than RC effects. The findings can inform co-produced decisions about outcome selection and study design, alongside further evaluation of existing instruments’ suitability for the intended RC populations. Involving learners and other stakeholders in these decisions can help align evaluation with research purposes and RCs’ educational philosophy while ensuring that participants’ individual goals are also assessed.
Psychopathy is a key to integrating dimensional personality disorder constructs and psychotherapy: toward a reformulation of personality and its disruption
While the conceptualization of personality disorder (PD) moves toward a dimensional approach, the broader adoption within clinical practice appears slow. The lack of a unifying framework in diagnostic classifications might explain this issue. Here, psychopathy, arguably the most pervasive and treatment-resistant PD variant, is presented as a key to integrating dimensional PD constructs and psychotherapy. The Dynamic Model of Psychopathy Assessment and Treatment Framework (DMP-ATF) provides a coalescing structure that, by virtue of its characterization of pivotal developmental psychological processes, hypothetically transcends variations in population, age, and clinical severity, to situate PD within a universal context. The redefined and integrated psychopathy construct and its associated framework represent a meta-theoretical approach that can unify therapeutic models, techniques, and principles to advance psychotherapy integration based on dimensional PD constructs, while placing personality and its psychopathology within a common structure. A system for converting externalizing behaviors into self-conscious emotions and needs, while managing risk, is additionally provided. While these proposals are compatible with contemporary biopsychosocial and treatment-oriented PD models and a trending treatment optimism, they await empirical validation.
STAT+: Telehealth leapfrogs FDA approval with off-label GLP-1 prescriptions for addiction
For the popular diabetes and obesity medications known as GLP-1s, addiction medicine is one of many possible promising next acts.
Eli Lilly is investigating a new drug, brenipatide, and testing it in alcohol use disorder. A new company called Baseline Therapeutics is studying a GLP-1 receptor agonist in alcohol, cocaine, and methamphetamine use disorders; Altimmune is testing one called pemvidutide for alcohol. Addiction medicine specialists are hopeful that the Food and Drug Administration may soon approve a new medication for alcohol use disorder — the first in two decades.
But some telehealth platforms that specialize in treating addiction aren’t waiting. In the last year, a few companies have begun to market off-label prescriptions of GLP-1s, both branded and compounded, to treat alcohol use disorder and other addictions.
Evaluating the PolarUs App in People With Bipolar Disorder
Conditions: Bipolar Disorder (BD); Quality of Life (QOL)
Interventions: Device: PolarUs Mobile App
Sponsors: University of British Columbia; Canadian Institutes of Health Research (CIHR)
Not yet recruiting
Interventions: Device: PolarUs Mobile App
Sponsors: University of British Columbia; Canadian Institutes of Health Research (CIHR)
Not yet recruiting
Assisting Screening of Adolescent Depression With Large Language Models as Symptom Detectors: Algorithm Development and Validation
<strong>Background:</strong> Depression prevalence is rising in adolescents and young adults (ages 10-24 years). Traditional screening methods for depression, such as the Patient Health Questionnaire (PHQ-9), are particularly challenging for adolescents. AI has potential to help with this, but the scarcity of annotated datasets highlights the need for off-the-shelf approaches. In this study, we investigate the feasibility of using state-of-the-art large language models (LLMs) to detect depressive symptoms in adolescent settings (ages 15-17 years). <strong>Objective:</strong> This study aimed to evaluate the feasibility of using in-context learning with LLMs to identify depressive symptoms in free-text clinical notes for adolescent populations, to evaluate the feasibility of off-the-shelf LLM configurations in detecting PHQ-9 symptom-related information under zero- and few-shot settings, and to demonstrate the potential clinical utility of LLM-driven evidence extraction through an interpretable AI-based depression screening tool. <strong>Methods:</strong> We examined free text of the electronic health records (EHRs) of adolescent patients with the diagnosis of depression or related mood disorders (age groups 15-17 years, 924 patients) from the Cincinnati Children’s Hospital Medical Center. We leveraged the combination of the Beck Depression Inventory (BDI) and the PHQ-9 to develop tailored categories suited for adolescent depression symptoms. We applied 3 state-of-the-art LLMs (Llama, smaller FLAN-T5, and Phi) to identify these symptom categories in zero- and few-shot configurations, allowing us to assess their performance without additional task-specific training. A word-search model was used as the baseline comparator. <strong>Results:</strong> We manually annotated clinical notes for 22 patients across 16 depression-related symptom categories. Our analysis shows that all LLMs substantially outperformed the word-matching baseline. Within the evaluated prompting configurations, FLAN-T5 achieved the highest precision (average <i>F</i><sub>1</sub>-score=0.65, precision=0.78) and strong performance in detecting rare symptoms such as sleep problems (<i>F</i><sub>1</sub>-score=0.92) and self-loathing (<i>F</i><sub>1</sub>-score=0.80). Phi offered a balanced performance (precision=0.44, recall=0.60), while Llama 3 achieved the highest recall (0.90) but tended to overgeneralize, making it less suitable for precise screening. Within this pilot study, the best-performing LLM exceeded the baseline <i>F</i><sub>1</sub>-score by 0.43. Finally, we demonstrate the clinical utility of FLAN-T5 annotations as features in a machine learning model, which distinguished depression cases from controls with high precision (0.78). <strong>Conclusions:</strong> We used a range of popular LLMs to identify indicators of adolescent (ages 15-17 years) depression symptoms in mental health notes. Within the evaluated configurations, FLAN-T5 demonstrated the most favorable balance between precision and recall. These results support the feasibility of using off-the-shelf LLMs for symptom detection in adolescent clinical notes, while future work using standardized prompting strategies and task formulations will help establish more definitive comparisons between model architectures. The computational efficiency of FLAN-T5 further supports its potential for deployment in resource-limited clinical settings. Our findings require further validation for broader populations and other mental health conditions.
An Education and Support Chatbot for Postpartum Mothers With Opioid Use Disorder: Qualitative Needs Assessment
Background: The prevalence of opioid use disorder (OUD) among women giving birth in US hospitals continues to rise. Increasing fatalities due to perinatal drug overdose have in part been attributed to decreased access to social support and treatment services. In recent years, mobile health (mHealth) technologies have been used to provide care to patients outside of traditional clinical settings. Given that perinatal OUD treatment works best when there is frequent contact between patient and clinician, harnessing mHealth could be valuable for improving patient engagement in perinatal OUD care. Objective: To address the increasing epidemic of perinatal OUD, which is compounded by loneliness and social isolation, this study aimed to adapt an existing mHealth chatbot intervention for postpartum individuals by developing educational and supportive content relevant to people in the postpartum period experiencing OUD and recovery. Methods: We used a participatory design to conduct a needs assessment via in-depth qualitative interviews with patients (n=12) and providers (n=11). Interview data were analyzed using NVivo software (Lumivero) according to a priori codebooks and using inductive coding, which identified major themes to address in a future adaptation of an interactive chatbot. An advisory board was convened to review the data and contribute to content generation that would be most useful for perinatal mothers who are in treatment for OUD. Results: Patients and providers agreed that an interactive chatbot would be useful for patients seeking information on childbirth recovery, substance use recovery, pain management, and infant care, including feeding. Patients specifically wanted a chatbot that felt personal and addressed their individual and specific needs. Providers indicated that the chatbot should address topics that came up frequently in after-hours phone calls to reduce provider burden. Conclusions: Conducting an in-depth participatory-driven needs assessment will support the refinement of an existing chatbot to better meet the needs of a high-risk, difficult-to-reach population. As we move forward to test the chatbot for acceptability and feasibility, data from the needs assessment will support ongoing iterative enhancement of the content, delivery, and safety of the chatbot.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/4711641658d6f7798d35a50de0518027" />
Depressive symptoms and occupational correlates among psychiatric nurses in northern Jiangsu: an explanatory sequential mixed-methods study
BackgroundPsychiatric nurses manage aggression, interrupted recovery and emotionally demanding care. Surveys quantify distress but rarely show how these experiences accumulate during routine work.AimWe aimed to estimate the prevalence of a positive depressive-symptom screen among psychiatric nurses and to quantify its associations with four prespecified occupational exposures: workplace violence, night-shift burden, occupational strain and psychological resilience. A longitudinal qualitative phase then examined how nurses experienced these same exposures during routine work.MethodsFour tertiary public psychiatric hospitals in northern Jiangsu participated from January 2025 to March 2026. A convenience sample of 357 nurses completed the survey. Workplace violence during the preceding 12 months was assessed with Wang’s Workplace Violence Scale; at least one physical, verbal or psychological, or sexual incident perpetrated by a psychiatric inpatient or visiting family member defined exposure. Modified Poisson regression with hospital fixed effects estimated prevalence ratios (PRs) for an SDS-positive screen. A purposive subsample of 20 nurses completed interviews, diaries and observation over three months. Colaizzi’s method and a joint display supported qualitative analysis and integration.ResultsOf 357 nurses, 138 (38.7%) screened positive. Nurses reporting violence had a higher screening prevalence (PR 1.65, 95% CI 1.31–2.08). PRs per SD were 1.48 (95% CI 1.33–1.66) for night-shift burden and 1.45 (95% CI 1.28–1.65) for occupational strain. Resilience showed the opposite pattern (PR 0.79 per SD, 95% CI 0.70–0.88). Qualitative accounts centered on repeated strain, a value–recognition mismatch, unequal recovery resources and support considered generic or poorly timed.ConclusionsDepressive symptoms were common. Nurses identified practical targets: safer work organization, rapid post-incident contact and support tailored to individual circumstances. Cross-sectional estimates do not establish diagnosis or causation.
Psychiatric service dogs reduce loneliness and improve social functioning in adults with mental health conditions: a qualitative study from South Africa
IntroductionLoneliness and impaired social functioning are clinically significant features of mental illness. Psychiatric service dogs (PSDs) are individually trained to perform tasks that mitigate the functional impact of psychiatric disability and have been proposed as an intervention for loneliness and impaired social functioning for their handlers living with mental illness. However, the mechanisms through which they may reduce loneliness and improve social functioning are poorly understood and evidence from low-middle income contexts is almost entirely absent.MethodsThis qualitative study aimed to explore the experiences of PSD handlers in South Africa regarding the impact of their PSD on loneliness, social functioning, and psychosocial well-being across a diverse range of mental illnesses. PSD handlers were recruited through purposive sampling via three South African PSD training organisations. Data were collected through semi-structured individual interviews and analysed using reflexive thematic analysis following the six-phase framework described by Braun and Clarke.ResultsReflexive thematic analysis of participants’ accounts generated six themes describing the psychosocial impact of PSD partnership. Three themes capture the primary mechanisms through which PSD partnership improved social functioning and reduced loneliness: (1) alleviation of loneliness through non-judgmental companionship; (2) PSDs as social catalysts: from brief encounters to sustained relationships; and (3) gains in independence and expanded community participation. Two additional themes describe internal psychological mechanisms: (4) restoration of purpose, meaning, and structured routine; and (5) caregiving as a mechanism of self-regulation and re-engagement. A sixth theme addresses the social costs and challenges of PSD partnership: (6) access discrimination, public scrutiny, and the burden of visibility.DiscussionTogether, these themes describe a multi-layered set of psychosocial processes through which PSD partnership both expanded participants’ social worlds and imposed new burdens upon them. The findings suggest that PSDs may serve as a meaningful adjunctive intervention for loneliness and social isolation in adults with mental illness. Mental health professionals would benefit from greater awareness of PSDs and the psychosocial benefits and challenges associated with their use.
Beyond diagnostic categories: transdiagnostic psychological mechanisms associated with suicidal ideation among university students: a systematic review (2021–2025)
IntroductionConventional diagnostic categories may not fully capture the psychological processes associated with suicidal ideation among university students. This systematic review synthesized recent evidence on candidate transdiagnostic psychological mechanisms, distinguishing ideation-specific findings from broader suicide-related outcomes.MethodsScopus, Web of Science, PubMed, and PsycINFO via EBSCOhost were searched for peer-reviewed observational studies published between January 1, 2021, and December 18, 2025. Study selection followed PRISMA 2020, and methodological quality was assessed using design-specific Joanna Briggs Institute checklists. A narrative synthesis distinguished separately assessed suicidal ideation from complementary findings involving broad death/self-harm indicators, suicide-related cognitions, and composite suicide-risk scores. Classification depended on the outcome analyzed rather than instrument length.ResultsOf 327 records identified, 68 studies were included; 58 were cross-sectional and 10 used longitudinal, prospective, or ecological momentary assessment designs. Findings were organized into cognitive–affective, emotional, behavioral, interpersonal–contextual, and protective domains. Ideation-specific analysis reported associations with hopelessness, repetitive negative thinking, perfectionistic concerns, depressive symptoms, perceived burdensomeness, and entrapment. Associations varied by outcome definition, statistical adjustment, and study design. Inverse or conditional associations involving psychological and interpersonal resources were reported in selected analysis. Complementary findings concerned broader suicide-related outcomes and were interpreted separately rather than as independent replication of ideation-specific associations.DiscussionThe evidence identifies candidate psychological processes for further investigation, but predominantly cross-sectional designs and heterogeneous outcome measures limit causal and temporal interpretation. The proposed framework organizes observational findings rather than validating a causal model. Future prospective research should distinguish outcome constructs, address confounding, and test whether modifying candidate processes reduces suicidal ideation.
Simultaneous measurement of Midbrain and Striatal Dopamine in Schizophrenia using an agonist radiotracer
Imaging studies showing greater amphetamine-induced dopamine release in patients with schizophrenia (SCZ) compared to matched healthy controls (HC) have been repeatedly replicated, but these studies all used radiotracers that were dopamine D2 receptor antagonists. A more recent study using an agonist radiotracer did not detect this increase, raising a question whether the difference in radiotracer pharmacology affected the result. Another study examining the extrastriatal response to the amphetamine challenge with an antagonist tracer observed a blunted effect in SCZ in the midbrain, suggesting mechanisms local to the striatum might have contributed to the striatal imaging results independent of midbrain dopamine availability.