Frontiers in Psychiatry

Background: Concerns about "AI psychosis" have swirled in the media since ChatGPT's release, but few systematic analyses exist. We therefore conducted an electronic health record (EHR) analysis to identify the frequency, clinical characteristics, and quality of AI interactions in patients experiencing psychosis treated in a medical center. Methods: AI keywords (e.g., ChatGPT, AI) were used to search Vanderbilt University Medical Center's EHR from 12/1/2022-4/1/2026. Records were discarded if they were not AI-related or if the primary diagnosis did not include psychosis. Three raters read notes to determine if a patient was experiencing AI psychosis and classified the interactions using 4 a-priori categories (Catalyst, Amplifier, Co-Author, Object) formulated to explain how AI-related negative outcomes emerge. Findings: 73 patients met our criteria. 28 patients were rated as experiencing AI psychosis, 17 had neutral interactions, and 28 expressed delusional content related to AI without documented evidence of conversational AI use. ChatGPT was the matching keyword for 53.6% patients experiencing AI psychosis. The majority of AI psychosis cases were documented after ChatGPT's "4o" model was released in May 2024. Notably, the AI Psychosis group had significantly more patients experiencing a first psychotic episode (60.7%) compared to the other two groups. Amplifier was the most common (64.3%) qualitative rating in the AI Psychosis group. Interpretation: "AI psychosis" is an infrequent but real phenomenon observed in clinical practice. Most affected patients were experiencing their first psychotic episode and presented with AI psychosis following the release of the more sycophantic GPT-4o. Among the affected patients, AI most often exacerbated an existing condition by reinforcing distorted ideas.

Background Multimorbidity is increasingly prevalent, and associated with worse clinical and psychosocial burdens. Interoception, the brain's ability to sense and interpret internal bodily signals, may contribute to multimorbidity, through its link with health behaviors, stress regulation, and mental health. This study examines whether self-reported interoceptive accuracy and attention is associated with multimorbidity, by identifying multimorbid subgroups and their interoceptive profiles. Methods Morbidity classes were identified through latent class analyses in two Dutch survey datasets, focusing on depression and alexithymia (DA-dataset; N = 671) and lifestyle factors (L-dataset; N = 1022). Linear regression analyses were used to assess interoceptive accuracy and attention (by the Interoceptive Accuracy Scale and Interoceptive Attention Scale respectively) among different subgroups. Results Multimorbid subgroups were characterized by older age, low socioeconomic position, and elevated physical, psychological, and behavioral problems. Multimorbid classes exhibited lower interoceptive accuracy (DA-dataset: B = -1.14, 95% CI = [-2.89, 0.62]; L-dataset: B = -2.36, 95% CI = [-3.83, -0.89]) and higher attention (DA-dataset: B = 3.62, 95% CI = [0.97, 6.27]; L-dataset: B = 1.07, 95% CI = [-1.42, 3.56]) compared to healthier classes. Conclusion Multimorbid populations demonstrated lower interoceptive accuracy and higher interoceptive attention. This highlights the psychosocial complexity of multimorbid populations which may impact their self-management and health behavior. These findings underscore the need to expand treatments to include psychosocial domains for multimorbid patients.

Background: Repetitive Transcranial Magnetic Stimulation (rTMS) is a promising treatment across addictive disorders including Cannabis Use Disorder (CUD). Targeting incentive-salience circuitry via the ventromedial prefrontal cortex (vmPFC) and central-executive circuitry via the left dorsolateral prefrontal cortex (LDLPFC) are both promising treatment approaches; however, to date structural targets have predominated whereas functional targeting may allow for more precision. In this pilot trial we adapted a functional Magnetic Resonance Imaging (fMRI) Regulation of Craving (ROC) task to generate fMRI-based rTMS targets in the vmPFC and LDLPFC. Methods: We recruited treatment-seeking participants with moderate or severe CUD as a part of an open-label trial and administered an adapted ROC-task during fMRI following 24-hours of cannabis abstinence. We identified sub-portions of maximal activation of the LDLPFC when participants thought of long-term consequences of cannabis use (Later) and of the vmPFC when participants thought of short-term positive aspects of cannabis use (Now). We hypothesized that our task would generate acceptable rTMS targets in >66% of baseline fMRI scans. Results: A total of 20-participants enrolled in the trial (50%F, age=33.3+9.8) and completed the baseline fMRI. The adapted ROC-task elicited group level activation in the LDLPFC and precuneus in the Later>Now and in the bilateral vmPFC, ACC, and striatum in the Now>Later contrast. Acceptable functional targets resolved in both the vmPFC and LDLPFC in 19 of 20 participants (one participant did not tolerate MRI). Conclusions: The adapted ROC-task elicits activation in incentive salience and central executive circuitry and can feasibly generate rTMS targets when using a cluster selection algorithm.

Background: Repetitive Transcranial Magnetic Stimulation (rTMS) is a promising treatment across addictive disorders including Cannabis Use Disorder (CUD). Stimulation of two rTMS-targets, the ventromedial prefrontal cortex (vmPFC) and the left dorsolateral prefrontal cortex (LDLPFC), limbic and executive control network hubs respectively, may yield differential effects. In this pilot trial, we explored the differential effects of 36-sessions of rTMS applied to either the vmPFC or LDLPFC. Methods: Treatment-seeking participants with moderate or severe CUD (n=20, 10F, age=33.3+9.8SD) were randomized to 36-sessions of open-label rTMS (two sessions-per-visit, two or three visits-per-week) to either the LDLPFC (3000-pulses; 10Hz) or vmPFC (900-pulses; 1Hz) using personalized functional Magnetic Resonance Imaging (fMRI) targets along with three-sessions of Motivational Enhancement Therapy. At baseline and following rTMS, the Time-Line Follow-Back was used to measure Days-per-week of cannabis use and the fMRI Regulation of Craving (ROC) task was used to measure network activation to cues associated with long-term negative ('Later') and short-term positive ('Now') consequences of cannabis use. Results: Eighty percent of participants completed study-rTMS. There was a significant decrease in days-per-week of cannabis use in both groups (vmPFC: d=7.9; DLPFC, d=3.1) between the four-weeks of baseline and seven-weeks of follow-up. LDPFC-rTMS reduced fMRI BOLD signal magnitude and increased LDLPFC functional connectivity in response to cues, while vmPFC-TMS reduced functional connectivity. Conclusions: Treatment-seeking participants with CUD reduced the number of days-per-week they used cannabis when receiving rTMS applied to either the LDPFC or vmPFC, while fMRI effects differed by treatment target. Future larger sham-controlled trials are needed for efficacy and biomarker determination.

Objectives To explore caregiver and clinicians perspectives on implementing mental health conversations and supports for caregivers of children with chronic conditions in paediatric outpatient clinics. Specifically, views were sought on (a) screening approaches and measures (phase 1) and (b) how feedback and support could be provided to caregivers experiencing mental health difficulties (phase 2). Methods Caregivers and clinicians from two outpatient clinics (neuromuscular and diabetes) at a tertiary paediatric hospital in Melbourne, Australia participated in online focus groups in July and August 2024. Caregivers were recruited from outpatient clinics and clinicians were recruited via email. Both groups were combined for phase 1 before separating into breakout rooms for phase 2. Two authors conducted reflexive thematic analysis of transcripts using NVivo. Results Sixteen participants (caregivers n = 8; and clinicians n = 8) took part in in two semi-structured focus groups. Analysis generated two overarching domains, each comprising multiple themes. Domain 1, Addressing caregiver mental health, captured themes of overwhelm and invisibility, diverse caregiving roles, and the need for time and resources to support wellbeing conversations. Domain 2, Housing the mental health conversation, encompassed themes of screening preferences, caregiver agency in confidentiality, delivery of feedback, and access to tailored supports. Conclusions Caregivers and clinicians support routine caregiver mental health discussions in paediatric outpatient settings. Caregivers favour screening at diagnosis and key transitions, with clear, and actionable feedback delivered away from the child. Questions about record-keeping warrant further exploration, as do the perspectives of fathers.

Background Little is known about the provision of diagnoses to young people with mental health disorders. We investigated diagnosis provision by NHS mental health services, focusing on 17-year-olds in South London between 2009-2024, and compared with estimated disorder prevalence. Methods To examine diagnosis provision in the population, we extracted diagnosis data from records of the NHS mental healthcare provider serving South London, using the Maudsley Biomedical Research Centre Clinical Record Interactive Search application; we then compared these data with the corresponding population size, obtained from the Office for National Statistics. To assess diagnosis provision in those with mental health disorders, we compared diagnosis data with the number of young people estimated to have met criteria for a disorder, derived from epidemiological interview data collected in the Environmental Risk (E-Risk) Longitudinal Twin Study and weighted according to characteristics of 17-year-old South Londoners. To assess diagnosis provision in those with mental health disorders within health services, we compared diagnosis data with the number estimated to have met criteria for a disorder and used any health service for their mental health, again derived from weighted E-Risk Study data. Findings Of 17-year-olds from South London in 2009-2024, 4.0% (n=8,958/223,404) had a diagnosis in mental health records during the previous year. This diagnosis provision covered <1 in 16 of those estimated to have had a mental health disorder, and <1 in 4 of those estimated to have also used health services. Diagnosis provision was lower in girls than boys and in young people with Black/Asian/Mixed/Other ethnicity than those with White ethnicity, in those estimated to have had a mental health disorder and used health services. Interpretation These findings demonstrate gaps and biases in mental health diagnosis provision for young people, including within health services, and reveal the imperative need to strengthen young people's mental healthcare.

Objective. Persistent, distressing psychotic-like experiences (PLEs) are associated with neurobiological alterations and increased psychosis risk. We combined individual-level neuroimaging measures with effect sizes from large neuroimaging studies to create a summary score ('Psychosis Neuroscore') reflecting neuroanatomic liability for psychosis, and examined its ability to predict PLE trajectories in young adolescents. Method. Using latent growth mixture models, we estimated PLE trajectories from four annual visits of the Adolescent Brain Cognitive Development Study (N=9584, ages 9-10 at baseline). Using baseline T1-weighted and diffusion-weighted imaging data, we calculated Psychosis Neuroscores, as well as Neuroscores for two psychiatric disorders with late adolescent/adult onset (Major Depressive Disorder, Bipolar Disorder). We compared Psychosis Neuroscores to i) other psychiatric Neuroscores, ii) modifiable risk factors, and iii) established risk factors in predicting trajectory membership. Results. We identified four trajectories of distressing PLEs: Persistent Elevated (N=1,968, 21%), Gradual Decreasing (N=3,424, 36%), Rapid Decreasing (N=1,593, 17%) and Low/No Distress (N=2,599, 27%). Adolescents with Persistent Elevated PLEs had significantly higher Multimodal (combined T1 and diffusion-weighted) and T1-weighted Psychosis Neuroscores than all other trajectories (Odds Ratios [ORs] 1.27-1.34,pFDR<.01). Bipolar Disorder Neuroscores showed a similar pattern (ORs 1.16-1.23,pFDR<.01). Psychosis Neuroscores showed comparable associations with established risk factors in predicting trajectory membership, but smaller associations than modifiable risk factors, including screen time, physical activity, and sleep disturbances. Conclusion. Psychosis Neuroscores differentiate youth with persistent PLEs from those with decreasing, remitting or low PLEs, demonstrating their potential utility for early risk stratification. Integration with established risk factors may enhance psychosis risk prediction in youth.

Introduction: While growing evidence suggests that music training supports child development, few long-term randomized controlled trials (RCTs) have rigorously tested these claims. Moreover, it remains unclear whether the benefits are confined to music-specific domains or extend to higher-order cognitive functions such as inhibitory control (IC), a core executive function associated with long-term outcomes in academic achievement, career success, socio-emotional health, and physical well-being. This paper presents the protocol for the Extracurricular Activity and Child Early Learning and Development (EXCEL) trial, an RCT designed to assess the feasibility of a long-term music training program focusing on the brain and behavioral correlates of IC. Methods: A total of 126 children, aged 6 to 8 years and residing in neighborhoods with limited resources in Los Angeles, were individually randomized to either a music (intervention) or theatre (active control) after-school program. Both programs were delivered over 24 months by established community arts organizations. Eligibility criteria included: average intellectual functioning, no major medical or psychiatric conditions, and MRI eligibility. Children with prior formal music training exceeding six months or severe hearing impairment were excluded. Before the intervention began, all participants completed baseline behavioral and neuroimaging assessments. The primary trial aim was to assess the effects of extended music training, relative to theatre training, on changes in measures of IC (i.e., Go/No-Go task and delayed gratification) and related neural functional activation. A secondary interim aim of the trial was to evaluate the feasibility of conducting a long-term RCT of music education in a first cohort, measured by participant retention, adherence to the program, willingness to continue at the 12-month mark, and fidelity. Progress: Recruitment, screening, baseline testing, randomization, and program enrollment began in August 2022, and after-school programming began in October 2022. The randomized interventions and all data for the first cohort (N = 42) have been collected. Intervention and active control programs for a second cohort are ongoing and will end in Fall 2026. Discussion: This paper reports the EXCEL trial protocol and provides feasibility estimates for implementing a long-term randomized controlled trial of music training in real-world, community-based settings with children. While similar neuroimaging RCTs are currently underway in Europe, the EXCEL trial is among the first in the United States to integrate longitudinal neuroimaging with arts intervention. Findings will inform the viability of scaling such programs and contribute to our understanding of how sustained music engagement may influence the development of inhibitory control circuitry in childhood.

Background: Major depressive disorder (MDD) is clinically heterogeneous, hindering identification of reproducible biomarkers. Using a semi-supervised machine learning approach, HYDRA, we previously identified two neuroanatomical dimensions from structural MRI in medication-free MDD from COORDINATE-MDD consortium. These dimensions (D1, D2) showed differential responses to selective serotonin reuptake inhibitor (SSRI) antidepressants and placebo. External replication in UK Biobank linked D2, characterized by widespread subtle neuroanatomical reductions, to an immuno-metabolic profile. Here, we examined whether these dimensions are detectable early in the course of illness. Methods: We applied the pre-trained model to structural MRI data from the multisite PRONIA cohort, comprising individuals with recent-onset depression (ROD; n = 377; mean age 25.8 years, SD 6.0; 51.3% female) and healthy controls (n = 267; mean age 25.5 years, SD 6.4; 61.0% female). Participants were assigned to clusters (C1, C2) corresponding to the previously identified dimensions (D1, D2). Clusters were compared on clinical symptom profiles, peripheral inflammatory markers, and in a subset (n = 107), proteomic ageing indices. Results: Two neuroanatomical clusters were identified in PRONIA. C1 (n = 265) showed higher negative symptom severity and elevated interleukin-2 levels. C2 (n = 140) was associated with higher residual proteomic age. Overall depressive symptom severity did not differ significantly between clusters. Conclusions: Neuroanatomical dimensions of MDD are reproducible and detectable at illness onset. Associations with negative symptom severity, inflammatory signalling, and proteomic ageing suggest these dimensions capture biologically meaningful heterogeneity early in depression. These findings support a biologically informed framework for stratified treatment approaches in MDD.

Introduction Gender norms and roles are important determinants of physical and mental health in the key period of adolescence. Yet, the gendered pathways to mental health in adolescents are not fully understood. Using a conceptual framework for global adolescent mental health that we developed based on a Delphi process, we empirically investigated the associations between six gender-related constructs and adolescent mental health. Methods We used cross-sectional Gender and Adolescence: Global Evidence (GAGE) data from Ethiopia (2020) to explore the associations between sex, gender norms, psychological competencies, gender attitudes, gender roles, with the latter two also serving as mediators, and psychological distress (GHQ-12), using Structural Equation Modelling (SEM). Results The SEM model contained measurements from 1,584 adolescents, including 843 girls and 741 boys, with a median age of 13 years. Out of 14 pathways tested, we found statistically significant associations between psychological competencies and psychological distress; sex and gender attitudes; and between gender norms and psychological competencies, gender attitudes, and gender roles. Hence, the gender-related constructs were mostly associated with each other, rather than with psychological distress. Conclusion The gender-related constructs are strongly interrelated, thereby attenuating their individual effects on psychological distress. The interplay of gender-related constructs should be considered when developing interventions to promote mental health in adolescents.

Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) frequently co-occur in Veterans, producing overlapping symptoms and shared autonomic dysregulation. Heart rate variability (HRV) offers a noninvasive measure of autonomic function. Univariate HRV analyses often fail to capture complex, multivariate patterns associated with comorbidity. This study applied machine learning to HRV features extracted from MEG-derived electrocardiogram (M-ECG) signals to differentiate Veterans with TBI alone (TBI-alone; n = 42) from those with comorbid PTSD (TBI+PTSD; n = 40). Time-domain, frequency-domain, geometric, and nonlinear HRV metrics were analyzed using nested cross-validated Random Forest and XGBoost classifiers, with Boruta-based feature selection and SHapley Additive exPlanations for model interpretability. Both classifiers achieved above-chance discrimination (Random Forest AUC = 0.663; XGBoost AUC = 0.635). Multivariate models identified distributed autonomic signatures in TBI+PTSD, including altered sympathovagal balance, increased low-frequency proportion, and greater heart rate complexity. In contrast, univariate HRV differences were subtle and did not survive correction for multiple comparisons. These findings demonstrate how using multivariate machine learning HRV analysis could help with detecting comorbidity-specific autonomic patterns, suggesting that HRV-derived signatures may serve as exploratory biomarkers for risk assessment and targeted interventions in Veterans with TBI and PTSD.

Objective: To evaluate whether a locally hosted open-weight large language model (LLM) can extract documented psychosocial factors from pediatric psychiatric intake notes and apply validated extraction to a large emergency psychiatry cohort. Materials and Methods: We identified emergency department presentations at Cincinnati Children's Hospital Medical Center from January 1, 2016, through December 31, 2024, among patients younger than 18 years with psychiatric billing diagnoses. Using full-text intake notes, gpt-oss:120b classified peer conflict, sleep disruption, and school-related academic, attendance, and disciplinary issues as detected, negated, or indeterminate. Four human raters independently reviewed 50 notes. We compared Fleiss' kappa among humans alone versus humans plus the LLM, assessed repeated-query stability across 50 independent calls per note, and applied the workflow to all eligible notes. Results: Among 37,315 eligible admissions, 22,284 had eligible intake notes; 22,270 produced parseable JSON. In detected-versus-not-detected coding, human-plus-LLM reliability did not differ significantly from human-only reliability across measures (human {kappa} 0.71-0.94; human-plus-LLM {kappa} 0.70-0.93). Stability was associated with human agreement: mean LLM-human agreement increased from 42.6% for classifications with less than 80% stability to 82.7% for classifications with 100% stability (Pearson r = 0.36). Full-cohort extraction showed frequent and overlapping documented factors: sleep disruption was most frequently detected (57.7%), followed by peer conflict (47.2%), academic issues (43.4%), disciplinary issues (43.3%), and attendance issues (16.9%). Discussion: Agreement varied by construct and was strongest when repeated model outputs were stable. Conclusion: Locally hosted open-weight LLMs can support scalable structured extraction of documented psychosocial factors from pediatric psychiatric intake notes after local validation.

Background: Adults with severe mental health conditions (often referred to as severe mental illness, SMI) experience 15 to 20 year mortality gap relative to the general population, with lung cancer a significant contributor. National cancer policy targets earlier diagnosis but does not explicitly address how pathways function for this group. Aims: This study aimed to describe lung cancer risk, prevalence, screening eligibility, referral activity and diagnostic pathway performance for adults with SMI in South East London (SEL), and to examine where along the pathway inequalities arise. Methods: Co-designed with experts with lived experience and voluntary sector, this exploratory mixed-methods service evaluation combined quantitative analysis of routinely collected data from the Quality Outcomes Framework (QOF), SMI Register and Cancer Waiting Times Record (April 2023-March 2024) with semi-structured qualitative interviews (n=11 clinical staff) and focus groups (n=6 adults with lived experience of SMI). Quantitative and qualitative data were analysed using descriptive statistics and framework-based thematic analysis respectively, and findings were integrated using a joint display approach, organised by the Consolidated Framework for Implementation Research (CFIR). Results: Lung cancer prevalence was approximately double among adults with SMI (0.17% vs 0.09% in the general population). Despite Urgent Suspected Cancer (USC) referral rates being more than twice as high in the SMI population (63 vs 28 per 100,000), fewer cancers were detected via planned general practice (GP) routes (11% vs 20%), the 28-day Faster Diagnosis Standard was not met for any SMI patient diagnosed with lung cancer during the study period; overall FDS performance was 76% in the SMI population compared with 84% in the general population; and appointment non-attendance was more than double that in the general population (6% vs 3%). Qualitative findings identified individual, service and system-level mechanisms, including stigma, diagnostic overshadowing, fragmented coordination, and rigid pathway protocols, that compound disadvantage across lung cancer pathway stages. Conclusions: Inequality in lung cancer outcomes for adults with SMI accumulates across the pathway rather than arising at a single point of failure. Addressing this requires proportionate adaptations within existing cancer pathways, alongside routine reporting of cancer outcomes stratified by SMI population. Keywords: severe mental health conditions, lung cancer, health inequalities, cancer screening, diagnostic pathway, mixed methods

Background Slow walking in older adults with mild parkinsonian signs (MPS) is a complex, multifactorial phenomenon arising from the cumulative burden of subclinical age-associated pathologies. This decline reflects age-associated neuronal loss in the dopaminergic system. A recent study suggests that levodopa treatment may enhance gait parameters. The goal of this small pilot study is to explore the effect of levodopa treatment on slow walking gait in older adults with MPS. Method This study was a randomized, placebo-controlled clinical pilot trial. Slow walking older adults without clinical evidence of PD were recruited and randomized into 2 groups (active treatment group or placebo control group). Participants in the active group were pre-treated with carbidopa for three days, followed by carbidopa-levodopa for seven days. Spatiotemporal gait parameters were evaluated at baseline and post-intervention. Results Gait factor analysis identified three main factors explaining gait characteristics at baseline, which included gait efficiency, gait rhythmicity, and gait turning.No effect of treatment was observed in the placebo group (p=0.111, p=0.616), no group difference was observed between the placebo and active group at baseline ({beta}=0.310, p=0.547), but a strong trend for a treatment-related increase was observed in the active treatment group ({beta}=0.506, p=0.076). Conclusion Our preliminary data suggest that sustained levodopa treatment (one week) in conjunction with carbidopa pre-treatment and concomitant carbidopa supplementation is feasible in slow walking older adults with MPS. Moreover, the data indicate potential efficacy, showing improvements in cadence, and step durations.

Background: Most approaches to suicide risk assessment consider clinical conditions as independent risk factors, potentially overlooking prognostic information in the order in which conditions accumulate. We applied temporal sequence mining to linked claims and mortality data to identify ordered clinical diagnostic trajectories associated with suicide death. Results: The cohort included 3 647 059 insured Maryland residents aged 10 years or older with available claims records in the Maryland Suicide Data Warehouse from January 1, 2016, to December 31, 2020, among whom 768 suicide deaths were ascertained through medical examiner linkage. Sequential pattern mining of ICD-10-CM diagnoses grouped into Clinical Classifications Software Refined categories identified 89 221 candidate sequences, of which 1 816 remained significantly associated with suicide death in time-varying Cox models. Adjusted hazard ratios (AHRs) ranged from 2.4 to 134.1. Two-thirds of significant trajectories ended in physical conditions, and approximately half crossed from psychiatric to physical endpoints. Among suicide decedents, 62% were exposed to at least 1 significant sequence (median, 16 per case); median sequence duration was 18.7 months, and median time from completion to death was 13.1 months. In landmark analyses, among patients with depression who later developed suicidal ideation (n = 26 356), the path through anxiety, then anemia, was associated with higher risk (AHR, 4.6; 95% CI, 2.2-9.5), whereas the anxiety-only path was not (AHR, 1.3; 95% CI, 0.8-2.1). Among patients with anxiety who later developed hypertension (n = 149 215), the path through history of self-harm was associated with higher risk (AHR, 32.0; 95% CI, 16.6-61.6). Associations were generally consistent across sex and age. Conclusions: Temporal ordering of clinical conditions may carry prognostic information for suicide death. Clinical trajectories incorporating physical illness within psychiatric sequences identified higher-risk groups. These findings suggest that opportunities for risk detection may extend beyond psychiatric settings and that suicide risk signals may be fragmented across care settings and not apparent within isolated encounters.

Background: Electrolyte replacement is ubiquitous in the acute care setting, but its familiarity cannot belie that even small dosing errors with potassium can cause lethal cardiac arrhythmias. Recently, MedAgentBench offered a benchmark for agentic artificial intelligence (AI) including the ability to correctly dose potassium based on a single rule; however, this does not adequately reflect the clinical complexity or safety concerns of an agent that has been used as the lethal injection. The purpose of this analysis was to a probe leaderboard large language model (LLM) capabilities to follow basic dosing rules to safely replace potassium in a series of clinician-annotated cases. Methods: Using a clinician panel, we developed a series of dosing principles and 20 clinical cases reflective of the complexity of potassium replacement. External clinicians were surveyed to assess practice variability and agreement to clinician panel answers. We tested GPT-5-chat with each case in triplicate, with and without the clinician curated dosing principles, and prompted the model to answer six questions involving potassium goals, dosing, route, lab frequency, concurrent interventions, and the model's perceived level of confidence for the output and complexity of the case. The primary outcome was the rate of appropriate recommendations in comparison to clinician answers. Results: A total of 54 clinicians reviewed the 20 hypokalemia cases and hypokalemia dosing guideline. Clinicians expressed "highly agree" or "somewhat agree" for 66.8% of the cases evaluated when asked if they agree with the guideline-recommended management. When given the potassium dosing guideline, total errors dropped from 165 to 104, and average accuracy improved from 45% to 65% with GPT-5-Chat. GPT-5-Chat conveyed a high level of confidence for 100% of responses, while labeling 80% and 76% of cases as highly complex with and without the criteria, respectively. Potential harm scores were considerable in both groups, however, a notable reduction in severity scores occurred with the dosing guidance document. Recommendations on concurrent interventions and dosing had the highest rate of errors in both groups. Conclusions: Benchmarks must appropriately reflect clinical complexity to be considered valuable for the deployment of agentic artificial intelligence tools in the healthcare domain. GPT-5-Chat assessment on a comprehensive medication management task for potassium replacement showed improvement with dosing guidance, yet unfit benchmarking performance.

Introduction Education is a core social determinant of health for children and adolescents. Unfortunately, academic achievement, health, and wellbeing of adolescents have decreased in many developed countries in the past decade. The purpose of the Wellbeing and Education linkages in school-aged children (WELL-ED) study is to examine associations of school absences and academic achievement with use of school-based and community-based health and social welfare services. In addition, we will assess user experiences and multi-sector services pathways of school-aged children for a better understanding of how the service system could respond to the needs of children. Methods and analysis WELL-ED is a large population-based study that combines register data on school absences and educational support from municipalities with register data on healthcare and social service use collected from wellbeing services counties in Finland. The study cohort includes all children who attended mandatory education in public schools in Southern Finland in school year 2023-2024. A smaller cohort of adolescents in school year 8 was invited to complete a user experience survey. The primary outcomes of this study are related to equity of service use. Ethics and dissemination The Regional Committee on Medical Research Ethics of the Helsinki and Uusimaa Hospital District (2803/2024) has approved the WELL-ED study protocol. For the survey, adolescents in year 8 and parents of adolescents younger than 15 provided informed consent. Results will be published in peer-reviewed journals, summaries will be sent to participating municipalities and wellbeing services counties and press releases will be written on key findings.

Background: Obsessive-compulsive disorder (OCD) is characterized by disturbing thoughts (obsessions) that initiate anxiety-reducing thoughts or behaviors (compulsions). For patients with treatment-resistant OCD (tr-OCD), neuromodulation techniques, like capsulotomy (a lesion in the anterior limb of the internal capsule) and deep brain stimulation (DBS), have emerged as interventions that likely regulate connectivity between the prefrontal cortex (PFC) and subcortical targets. Three patients (Cap-DBS1-3) underwent a failed capsulotomy followed by successful DBS. Here, we aimed to understand the brain connections disrupted by failed capsulotomy vs modulated by successful DBS. Methods: We used diffusion-weighted magnetic resonance imaging (dMRI) tractography in a control cohort with tr-OCD (n=12) and in two of the Cap-DBS patients themselves to determine connectivity profiles of the capsulotomy, volume of tissue activated (VTA), and potentially necessary tracts (VTA minus capsulotomy tracts). We used whole-brain, PFC-focused, and subcortically-focused tractography algorithms to fully explore the space of possible connections. Results: Capsulotomy regions-of-interest (ROIs) connected with a variety of PFC and subcortical regions. VTA ROIs and potentially necessary tracts had limited and inconsistent PFC connectivity but substantial subcortical connectivity. While correlated to the average OCD connectome (r = 0.214, 95% CI [0.177, 0.251]; r = 0.756, 95% CI [0.739, 0.772]), the Cap-DBS connectomes had many edges that were stronger (z-score > 3). Conclusions: The connectivity profile of potentially necessary tracts for successful DBS treatment after failed capsulotomy revealed a surprising proportion of subcortical regions and inconsistent PFC involvement, highlighting an often-ignored set of connections that may be critical to effective DBS.

Background: Post-stroke apathy (PSA) is a common, disabling syndrome with few evidence-based treatment options. We evaluated the safety, feasibility, acceptability, and evidence of effects of a three-day accelerated intermittent theta burst stimulation-repetitive transcranial magnetic stimulation (iTBS-rTMS) protocol targeting the left dorsomedial prefrontal cortex (dmPFC) in chronic stroke survivors with apathy. Methods: Stroke survivors with symptomatic apathy received open-label iTBS-rTMS at the left dmPFC (21,600 pulses across 36 sessions; 3 treatment days; 12 sessions/day within one week). Safety endpoints included adverse events, neuroradiological findings, and objective cognitive performance. Secondary outcomes included measures of apathy and other neuropsychiatric symptoms as well as psychosocial functioning, including quality of life and caregiver burden. Participants were followed up for one month. Results: Fourteen participants (mean age = 61.8 {+/-} 14.0 years; mean time since stroke = 55.6 {+/-} 31.6 months) completed the iTBS-rTMS treatment course. No serious adverse events occurred. Participants rated the treatment as highly acceptable, and cognitive performance was stable from pre- to post-rTMS with no treatment-related changes on structural MRI. Regarding apathy, participants had significant improvements with moderate to large effect sizes on the Lille Apathy Rating Scale (LARS), on both self (d = 0.78) and caregiver-rated versions (d = 1.28), p<0.05 pretreatment-to-one-month follow-up. In addition, secondary measures of psychosocial function also showed improvement with moderate to large effect sizes (Stroke Specific Quality of Life Scale: d = 0.62; Zarit Burden Interview: d = 0.72), and the Brief Inventory of Psychosocial Function: d = 0.89). Conclusions: In chronic stroke survivors with PSA, accelerated iTBS-rTMS targeting the left dmPFC appears to be safe, feasible, tolerable, and highly acceptable, with preliminary evidence suggesting a potential role in reducing apathy and secondarily promoting improvements in quality of life, caregiver burden, and broader psychosocial function.

Background. Psychotic-like experiences (PLEs) index early risk for psychotic disorders and are consistently associated with childhood trauma, yet underlying biological mechanisms remain poorly understood. DNA methylation (DNAm) may capture the biological embedding of early adversity, while adolescent exposures such as cannabis use may modify these processes. We examined epigenome-wide associations of childhood trauma and PLEs, tested the moderating role of early cannabis use, and evaluated DNAm as a potential mediator. Methods. We analysed data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a UK population-based birth cohort. Childhood trauma was assessed prospectively and retrospectively. Epigenome-wide DNAm was measured in peripheral blood at ~17 years using the Illumina 450K array, and PLEs were assessed at 18 using a structured interview. Epigenome-wide association studies were conducted for trauma-DNAm and DNAm-PLEs associations in the final sample (n = 1,457), adjusting for demographic, biological, and technical covariates. Differentially methylated regions (DMRs) were identified using DMRff, followed by functional enrichment analyses. Cannabis use at 15.5 was modelled as a moderator with multiple imputation for missing data. Mediation was tested using the Divide-Aggregate Composite-null Test (DACT). Results. Childhood trauma was associated with widespread DNAm differences, primarily at the regional level, with enrichment in pathways related to cellular stress responses. In contrast, DNAm associated with PLEs was more limited and implicated loci involved in epigenetic regulatory processes. These signatures were largely distinct, and there was no evidence supporting mediation after multiple testing correction. Incorporating cannabis use altered the pattern and extent of DNAm associations, with stronger and more significant signals observed at both CpG and regional levels, although these did not translate into evidence of mediation. Conclusion. Childhood trauma and PLEs show distinct DNAm signatures in adolescence, with trauma-related DNAm reflecting broad stress-related processes and PLE-associated DNAm implicating regulatory mechanisms. We found little evidence that DNAm mediates the trauma-PLE association. Instead, adolescent exposures, particularly cannabis use, may distinctly influence trauma-related epigenetic variation with limited detectable downstream effects on PLEs. These findings support a context-dependent model of epigenetic risk and highlight the need for larger longitudinal studies to clarify causal pathways linking early adversity to psychosis.