European Psychiatry

BackgroundDepression and anxiety are common mental health conditions in the UK. NHS Talking Therapies offers evidence-based therapies and is the largest provider of treatment, yet, only 50% of patients recover. Accurate outcome prediction could identify those at risk of poor outcomes and support more personalised care. This study aimed to develop and internally validate multivariable prediction models using routinely collected data from a large, ethnically diverse sample to enable fair, data-driven treatment decisions. MethodsData included 30,999 adults who completed high-intensity therapy at a single NHS trust between 2018 and mid-2024. Seven NHS post-treatment outcomes were modelled: reliable improvement, recovery, and reliable recovery for both depression and anxiety, and also functional impairment at the end of treatment. Predictors measured at baseline included sociodemographic and clinical characteristics. Models were developed using elastic net logistic regression and internally validated using bootstrap resampling. ResultsThe sample was predominantly female (73%) with a median age of 34; 57% identified as White and 22% as Black. Models showed moderate to good discrimination (AUC 0.63-0.77) and strong calibration. Key predictors aligned with clinical expectations, including baseline symptom severity, unemployment, benefit receipt, reporting a disability or long-term condition, psychotropic medication use among other sociodemographic factors. ConclusionsThis study highlights the potential of data-driven tools to inform clinical decisions and treatment stratification in NHS Talking Therapies. Early identification of patients less likely to benefit from standard care could support timely review, monitoring, or tailored interventions. External validation and implementation research are needed to ensure generalisability and equity in care.

BackgroundProlonged waiting times for Child and Adolescent Mental Health Services (CAMHS) leave many young people without structured support while awaiting specialist treatment. Social prescribing has been proposed as a community-based adjunct within CAMHS pathways; however, evidence regarding its safety and clinical impact remains limited. MethodsWellbeing While Waiting was a multi-site non-randomised controlled trial embedded within a hybrid type II implementation-effectiveness evaluation conducted across 11 CAMHS in England. The protocol was prospectively published prior to recruitment (BMC Psychiatry; 10.1186/s12888-023-04758-0). Between May 2023 and March 2025, 558 young people aged 11-18 years referred to CAMHS were enrolled (225 usual care; 333 social prescribing). Primary outcomes were anxiety and depression symptoms, total emotional and behavioural difficulties, and perceived stress. Secondary outcomes included resilience and wellbeing. ResultsNo intervention-related adverse events were observed. On average, participants had 5 sessions with a Link Worker. Compared with usual care, no significant differences were observed in anxiety or depression symptoms. However, participants receiving social prescribing demonstrated significant improvements in total emotional and behavioural difficulties over six months, driven by reductions in conduct difficulties, hyperactivity and peer problems. Significant improvements for those receiving social prescribing were also found for prosocial behaviour and resilience. ConclusionsWithin routine CAMHS pathways, no intervention-related adverse events were observed for social prescribing, and social prescribing was associated with improvements in behavioural and resilience-related outcomes, although not in anxiety or depressive symptoms. Findings suggest social prescribing may offer a valuable adjunct during delayed access to specialist treatment, with effects distinct from symptom-focused clinical therapies.

BackgroundDepression is estimated to be the leading cause of disability in South Africa, yet data on depression prevalence and antidepressant use are inconsistent and fragmentary. We present a system dynamics modelling approach to integrate these data and assess trends and inequalities in depression prevalence and treatment access. MethodsWe developed a deterministic model of the South African population aged 15 and older, stratified by age, sex, HIV status/stage and susceptibility to depression. Individual transitions between depressed/healthy and treated/untreated states were simulated over time, from 1985. The model was calibrated to depression prevalence data from nine nationally representative household surveys (2002-2024) and ten smaller studies reporting prevalence of antidepressant use, using a Bayesian approach. ResultsThe model estimated a slight decline in depression point prevalence over time, from 5.1% (95% CI: 4.5-5.6%) in 2002 to 4.5% (95% CI: 4.0-5.0%) in 2024, although with a transient rise in depression prevalence during the COVID-19 period. In 2024, depression prevalence was higher in women (5.3%, 95% CI: 4.7-5.9%) than men (3.6%, 95% CI: 3.2-4.0%), and highest at ages 60 and older. The lifetime prevalence of depression was 70.6% (95% CI: 67.8-73.6); alternative model settings with a more concentrated distribution of depression risk were inconsistent with longitudinal data. The proportion of adults using antidepressants increased from 1.0% (95% CI: 0.8-1.2%) in 2008 to 2.8% (95% CI: 2.2-3.4%) in 2024. In 2024, antidepressant use was 11.0% (95% CI: 8.8-13.5%) in the private sector, compared to only 0.9% (95% CI: 0.7-1.1%) in the rest of the population, and the ratio of new antidepressant initiations to new cases of depression was 0.12 nationally. ConclusionThe prevalence of depression in South Africa has been relatively stable over the last two decades. Although antidepressant use has increased, overall use remains low, and substantial inequality remains in access to treatment in the public and private health sectors.

IntroductionDespite evidence supporting child and adolescent cognitive behavioural therapy (CBT) globally, interventions remain largely unavailable within public systems. This gap requires implementation models integrating development, training, and scalability research within real-world settings and changes in management structures. Here we developed and implemented manualised psychotherapeutic protocols through a national capacity-building initiative in Greece. MethodsWe designed a structured implementation pathway conducted through the Child and Adolescent Mental Health Initiative (CAMHI), a public-private partnership involving clinical and academic institutions across Greece: (1) pre-implementation research through national reviews and national surveys of health professionals; (2) co-development and iterative pilot implementation of evidence-based interventions through supervised practice within the National Health System; and (3) dissemination research supporting scalability and institutionalisation within public structures. ResultsPre-implementation research identified gaps in the availability of clinical protocols in Greek services; a survey of 120 psychologists and psychiatrists indicated the need for psychotherapeutic training. Three evidence-based protocols were co-developed: CBT for anxiety (6-12 years), CBT for depression (12-17 years), and behavioural parent training (BPT) for disruptive behaviour (4-14 years). During a three-stage pilot, 45 clinicians delivered interventions to 140 cases (anxiety n=52; depression n=25; BPT n=63); 117 (83{middle dot}5%) completed treatment. Significant symptom reductions were observed for anxiety (d=-2{middle dot}92; RCADS-25), depression (d=-1{middle dot}79, RCADS-25), and disruptive behaviour (d=-2{middle dot}3, SNAP-IV), with 63%, 38% and 44% showing reliable improvement at the treatment endpoint. A train-the-trainer model is under implementation for national scale-up. Institutionalisation includes integration into child and adolescent psychiatry curricula. Sustainability safeguards were established through Law 5015/2023, with the Ministry of Health assuming operations by 2027. DiscussionPilot results demonstrate the feasibility of evidence-based psychotherapeutic interventions embedded within real-world child and adolescent services in Greece. Integrated implementation approaches provide a viable pathway for developing, refining, and scaling clinical manuals within public health provision.

BackgroundLongitudinal measurement of depression severity in outpatient psychiatric care is limited by infrequent standardized assessments. Although psychiatric clinical notes capture illness burden and functional impairment, this information is rarely quantified for analysis. ObjectiveTo evaluate whether large language models (LLMs) can infer clinically meaningful measures of depression severity from outpatient psychiatry notes. MethodsWe sampled 91,651 outpatient psychiatry notes from 8,287 adult patients across 58 clinics within a large academic medical center between 2015 and 2021. A HIPAA-compliant LLM (OpenAI GPT-5.2) was prompted to independently estimate three depression severity scores (Patient Health Questionnaire-9 [PHQ-9], Hamilton Depression Rating Scale [HAM-D], and depression-specific Clinical Global Impression-Severity [CGI-S]) from notes, with patient-reported PHQ-9 content within notes redacted to prevent biasing. Convergent validity was assessed against patient-reported PHQ-9 (n=3,757), study-clinician chart review (n=125), and treating-clinician suicide risk assessments (SRA; n=2,985). Predictive validity was evaluated using survival models of antidepressant switching and psychiatric emergency visits. Discriminant validity across diagnoses and consistency across demographic groups and clinics were also evaluated. Results10.8% of eligible visits had a PHQ-9 recorded within 7 days before the encounter. LLM-inferred PHQ-9 scores showed moderate agreement with patient-reported PHQ-9 (Cohens {kappa}=0.64, 95%CI:0.62-0.66; Pearson r=0.67, 95%CI: 0.65-0.68). Stronger agreement was found between LLM CGI-S and study-clinician chart review ({kappa}rater1=0.79, 95%CI: 0.70-0.85; {kappa}rater2=0.67, 95%CI: 0.58-0.77; r=0.86 with mean rating, 95%CI: 0.80-0.90). In prospective analyses, LLM CGI-S predicted antidepressant switching (C-index=0.60; CI95%: 0.58-0.62) and psychiatric emergency visits (C-index=0.63; 95%CI: 0.57-0.68), which was comparable to the predictive performance of patient-reported PHQ-9 and treating-clinician SRA. Correlations between LLM CGI-S and patient-reported PHQ-9 were consistent across clinics (I2<0.1) but significantly lower among Black (r=0.48, 95%CI: 0.38-0.57) and Hispanic (r=0.43, 95%CI: 0.27-0.56) patients. ConclusionsLLM-inferred depression severity scores from psychiatric outpatient notes support longitudinal, standardized phenotyping of depression severity, such as for routine outcome monitoring. These results have implications for facilitating genetic, pharmacoepidemiologic, and antidepressant treatment effectiveness studies using real-world evidence.

BackgroundDepression is associated with an increased risk of subsequent Parkinsons disease. Neuroimaging studies suggest a neurobiological overlap in mechanisms underlying Parkinsons disease and psychomotor retardation in depression. Our aim was to investigate whether, among individuals with depression, the presence of psychomotor retardation was associated with the development of subsequent Parkinsons disease. MethodsIn a retrospective cohort study, electronic healthcare records from individuals diagnosed with depression at age 40 or over in a large mental health service in London, UK were examined for the presence of psychomotor retardation. Linkage to general hospital records was used to ascertain diagnoses of Parkinsons disease between 2007 and 2023. Cox regression was used to compare the hazard of Parkinsons disease in individuals with depression with and without psychomotor retardation. ResultsAmong 6327 patients with depression, 2402 (38.0%) had psychomotor retardation. The adjusted hazard ratio for development of Parkinsons in those with psychomotor retardation was 1.43 (95% CI 1.02 - 2.01, p = 0.04). Secondary analyses demonstrated a significant difference in psychomotor retardation incidence at least 10 years before Parkinsons diagnosis. ConclusionsPsychomotor retardation in later-life depression is associated with increased risk of subsequent Parkinsons diagnosis over an extended period of time, suggesting that the relationship cannot solely be explained by misdiagnosis. Psychomotor retardation may therefore serve as a marker of prodromal Parkinsons disease. HighlightsO_LIPsychomotor retardation was associated with later Parkinsons disease. C_LIO_LIPsychomotor retardation may present >10 years prior to Parkinsons diagnosis. C_LIO_LIDepression with psychomotor retardation may be a prodrome for Parkinsons disease. C_LI

Background Escalating mental health service demands have created a need to better identify young people most likely to require continued support from mental health services at the transition between childhood and adulthood. Anxiety is the most common adolescent mental health condition, yet its clinical significance and prognosis are not well understood. We aimed to examine the risk of young adult-onset psychiatric disorders in individuals with an adolescent anxiety disorder, and identify stratifiers of risk of subsequent psychiatric disorders in this group. Methods Individuals from the Norwegian Mother, Father, and Child Cohort Study (MoBa) with linked health records and aged 18 or over as of the 31st December 2023 were included. Those diagnosed with any ICD-10 anxiety disorder when aged 10-17 years were defined as having an adolescent anxiety disorder (n=2107, controls n=47,582). Polygenic scores (PGS) for psychiatric and neurodevelopmental conditions were calculated using LDpred2. Anxiety, comorbidities, and parental psychiatric history were defined through linked ICD-10 diagnoses. Sex was defined through linked records. Individuals were defined as having a young adult-onset psychiatric disorder if they first received any new psychiatric diagnosis aged 18-24. Results Adolescent anxiety diagnosis was associated with increased risk of all adult-onset psychiatric disorders (HR= 2.33-8.65). Post-traumatic stress disorder PGS, parental history of severe mental illness, and female sex were associated with increased risk of transition to a young adult-onset psychiatric disorder in people with an adolescent anxiety disorder. Conclusions Adolescent anxiety greatly increases the risk of a psychiatric disorder during the transition to adult life. Clinicians should consider female sex and parental psychiatric history when prioritising young people with anxiety for adult mental health service support. Future research needs to further consider whether polygenic scores would aid risk stratification in clinical practice.

BackgroundAI-powered cognitive behavioural therapy (AI-CBT) tools hold significant promise for addressing the global mental health treatment gap, yet sustained user engagement remains critically low. While patient attitudes and experiential factors have been qualitatively documented, the psychological mechanisms through which AI literacy translates into long-term engagement remain poorly understood. Existing systematic evidence highlights trust, perceived therapeutic alliance, and stigma as salient themes, but no large-scale quantitative study has modelled these as a mediated pathway. ObjectiveThis study aimed to (1) examine whether trust in AI systems and perceived therapeutic alliance mediate the relationship between AI literacy and sustained AI-CBT engagement, and (2) determine whether mental health stigma moderates these mediated pathways. MethodsA cross-sectional national online survey was conducted in the United Kingdom (N = 1,247). Eligible adults (18+) with a history of anxiety or depression who had used an AI-CBT tool in the preceding 12 months were recruited via stratified random sampling. Structural equation modelling (SEM) with moderated mediation was conducted in R (lavaan 0.6-17). Moderated mediation was evaluated using the PROCESS macro framework adapted for SEM, with 5,000 bootstrap replications for bias-corrected confidence intervals. Model fit was assessed using CFI, TLI, RMSEA, and SRMR indices. ResultsThe final SEM demonstrated excellent fit (CFI = 0.967, TLI = 0.959, RMSEA = 0.043 [90% CI: 0.036-0.051], SRMR = 0.052). AI literacy exerted a significant indirect effect on sustained engagement through trust in AI ({beta} = 0.213, SE = 0.031, p < .001) and perceived therapeutic alliance ({beta} = 0.187, SE = 0.028, p < .001). Mental health stigma significantly moderated the trust[-&gt;]engagement pathway ({Delta}R2 = 0.042, p = .003), with the indirect effect being stronger among individuals with lower stigma scores. The total indirect effect accounted for 58.4% of the total effect of AI literacy on engagement. ConclusionsAI literacy promotes sustained AI-CBT engagement primarily through its effects on trust and perceived therapeutic alliance, pathways that are attenuated by mental health stigma. These findings underscore the need for stigma-reduction interventions and AI literacy programmes as implementation strategies. Findings have direct implications for the design and deployment of AI-CBT tools across UK NHS digital mental health services.

ObjectivePosttraumatic stress disorder (PTSD) after a traumatic birth is a serious but overlooked maternal morbidity, affecting [~]20% of women following medically complicated deliveries. PTSD can undermine maternal caregiving. Rapid screening tools suited to busy obstetric settings are lacking. We developed and evaluated a brief screener, derived from the 20-item PTSD Checklist for DSM-5 (PCL-5), to identify PTSD related to childbirth. Study DesignWe enrolled 107 women with traumatic childbirth. Participants completed the PCL-5 and the gold-standard clinician diagnostic interview for PTSD (CAPS-5); depression was measured with the Edinburgh Postnatal Depression Scale (EPDS). Bootstrap resampling with LASSO regression identified PCL-5 items most associated with PTSD. Firth logistic regression models estimated diagnostic accuracy. Sensitivity, specificity, area under the ROC curve (AUC), and Youdens J statistic determined performance and optimal cut-off. ResultsA six-item version of the PCL-5 (PCL-5 R6), statistically derived from the full scale, showed excellent discrimination for PTSD compared with clinician evaluation (AUC = 0.95; 95% CI, 0.89-1.00). A cut-off score of 7 yielded high sensitivity (0.96) and good specificity (0.83), with an overall diagnostic efficiency of 0.86, detecting most PTSD cases while minimizing false positives. The PCL-5 R6 correlated moderately with the EPDS (rho = 0.53), showing that a depression screen alone cannot reliably detect PTSD. ConclusionsA short, 6-item PCL-5 provides a valid, efficient tool for detecting childbirth PTSD. Its brevity and accuracy make it practical for integration into routine postpartum care, enabling timely mental health screening.

ObjectiveTo charactertise emergency department (ED) use among young people with bipolar disorder (BD) and compare patterns to those observed in anxiety, depressive, and psychotic disorders. Design, setting and participantsData linkage study using administrative ED presentation records (January 2020 to October 2020) and a transdiagnostic youth mental health cohort of 2243 individuals aged 12-30 years in New South Wales, Australia. Main outcome measuresED presentation patterns (any presentation, frequency, and rates) and reasons for presentation (mental health-related and non-mental health-related). ResultsOf the 354 young people with BD, 309 (87.3%) presented to an ED at least once. ED presentation rates were higher for BD than for anxiety (incidence rate ratio [IRR]=1.82, p<.001) and depressive disorders (IRR=1.32, p<.001), but similar to psychotic disorders (IRR=0.91, p=.379). Differences were primarily driven by mental health-related presentations. Recurrent mental health presentations were associated with illness progression (clinical stage and functional impairment) rather than diagnosis. However, the likelihood of mental health-related presentations remained higher in BD compared with anxiety and depressive disorders after adjustment. ConclusionsYoung people with BD have high rates of ED use, comparable to those with psychotic disorders. Although mental health-related presentations are more common in BD than in anxiety and depressive disorders, recurrence is largely explained by markers of illness progression. These findings highlight the need for community-based services that provide continuous and coordinated care for young people with complex mental health needs.

Background: The NHS Improving Access to Psychological Therapies (IAPT) programme, now rebranded as NHS Talking Therapies, faces persistent capacity constraints with average wait times exceeding 90 days for cognitive behavioral therapy (CBT) in many Clinical Commissioning Group areas. AI-powered CBT platforms have been introduced as a digital adjunct within stepped care, yet longitudinal evidence on anxiety symptom trajectories and their predictors in routine NHS settings remains limited. Objective: To model individual anxiety symptom trajectories among patients referred to an AI-powered CBT platform within NHS primary care, identify distinct trajectory classes, and examine patient-level and practice-level predictors of differential treatment response using multilevel growth curve modeling. Methods: A prospective cohort study was conducted using linked clinical and administrative data from 6,284 patients (aged 18-65) referred to the CalmLogic AI-CBT platform across 187 general practices in four NHS England Integrated Care Systems (ICSs) between April 2023 and September 2025. Patients completed GAD-7 assessments at baseline, 4 weeks, 8 weeks, 12 weeks, and 24 weeks. Three-level growth curve models (assessments nested within patients nested within practices) with random intercepts and random slopes were fitted. Growth mixture modeling (GMM) was subsequently applied to identify latent trajectory classes. Predictors were examined at Level 2 (patient demographics, baseline severity, comorbidities, digital literacy, engagement intensity) and Level 3 (practice deprivation index, list size, urban/rural classification, and IAPT wait time). Results: The unconditional growth model revealed a significant average linear decline in GAD-7 scores of -0.94 points per month (p < .001), with substantial between-patient variation in both intercepts (variance = 14.82, p < .001) and slopes (variance = 0.38, p < .001). Significant between-practice variation accounted for 8.7% of intercept variance (ICC = 0.087). Growth mixture modeling identified four distinct trajectory classes: Rapid Responders (28.4%, steep early decline stabilising by week 8); Gradual Improvers (34.1%, steady linear decline through 24 weeks); Partial Responders (22.8%, modest early improvement followed by a plateau at clinically significant levels); and Non-Responders (14.7%, minimal change or slight deterioration). Higher baseline severity, female gender, and greater module completion predicted membership in the Rapid Responder class. Practice-level IAPT wait times exceeding 90 days independently predicted faster improvement trajectories (coefficient = -0.31, p = .003), suggesting that AI-CBT has its greatest incremental value in capacity-constrained areas. Patients in the most deprived quintile showed slower trajectories (coefficient = 0.22, p = .011) despite equivalent engagement levels, indicating a deprivation-related treatment response gap. Conclusions: AI-powered CBT platforms integrated within NHS primary care produce significant anxiety symptom reduction on average, but treatment response is heterogeneous, with four distinct trajectory classes identified. The finding that longer IAPT wait times predict better AI-CBT outcomes supports the platform's positioning as a scalable bridge intervention for capacity-constrained services. The deprivation-related response gap warrants targeted support strategies for patients in the most disadvantaged communities.

BackgroundMost studies seeking to identify youth at increased risk for depression have developed prediction models using a limited set of risk factors in general population samples. It is unclear whether these models generalize to high-risk youth. Here, we developed machine learning algorithms to predict first-onset depression in youth from the general population and high-risk youth with attention-deficit/hyperactivity disorder (ADHD). MethodsParticipants were 4803 unrelated children from the ABCD study with no prior mood disorder and complete data at baseline (age 9-10 years) and 2-year follow-up. Support Vector Machine, Random Forest, and Elastic Net models were used to predict first-onsets from clinically-relevant risk factors spanning mental and physical health, cognitive, dispositional, interpersonal, and socio-environmental domains. Predictive performance was evaluated in the full sample and separately in participants with ADHD (N=584, 12.16%). ResultsModels trained on the full sample achieved good discriminative predictive power (area under the curve [AUC]=0.70 and accuracy=0.70-0.82). Predictors that replicated across models included earlier pubertal development, higher behavioral inhibition and aggression, and more time spent passively watching media content. In the ADHD subsample, model performance declined (AUC=0.46-0.61) and predictors only partly overlapped with those identified in the full sample. ConclusionsModels effectively predicted depression in the general population but showed poor generalization to high-risk youth with ADHD, suggesting different risk factors in this group. These findings highlight that models trained in general population samples may not generalize to high-risk groups, pointing to the need for more tailored efforts to predict depression in youth at increased risk.

Background Treatment guidelines for borderline personality disorder (BPD) recommend assessment, diagnosis, and psychoeducation. We report on the feasibility and safety of a randomized controlled trial protocol of online psychoeducation, assessment, and personalized feedback as an immediate first step of care for BPD. Methods Newly diagnosed participants were randomized to receive 10 videos about BPD or general mental health for two weeks. Half the participants receiving BPD videos were randomized to receive personalized feedback on changes in symptom ratings and cognitive performance. Ecological momentary assessment (EMA) evaluated interpersonal interactions, emotions, and behaviors for 30 days. BPD symptoms, depression, and personality functioning were assessed at baseline, after videos, after feedback, and one month later. Results Eighty-two participants were randomized into three conditions that did not differ significantly in terms of demographics or baseline variables. Dropout occurred for 32.9% of the sample. No differences in rate of emergency room visits, hospitalizations, or other escalations in level of care were reported among groups. Satisfaction was higher for those receiving psychoeducational videos about BPD. Improvement in BPD knowledge in the psychoeducation conditions was significantly greater than the control condition. No statistically significant differences were found regarding reduction of BPD symptoms. The psychoeducation with feedback arm showed significantly greater improvements in self-impairment compared to controls with medium effect size at the final timepoint. Modeling of the relationship between time spent alone and BPD symptoms showed a positive correlation in the control condition, but in the group receiving both psychoeducation about BPD and feedback, this relationship was negative. Conclusion Online psychoeducational videos and assessment were safe, feasible, and acceptable to participants with newly diagnosed BPD. Psychoeducation with personalized feedback appears to be more effective than either BPD or general psychoeducation alone in improving deficits in self-functioning, which may relate to an increased capacity to be alone with fewer symptoms. The protocol was registered with ClinicalTrials.gov (NCT05358925, https://clinicaltrials.gov/study/NCT05358925) on April 28th, 2022.

Objective: Major depressive episodes frequently show limited response to first-line treatments, motivating the search for objective biomarkers. EEG/ECG-based support tools aggregating electrophysiological predictors may guide treatment selection. We examined whether antidepressant treatments concordant with an EEG/ECG-biomarker report were associated with higher response rates. Methods: We retrospectively analyzed adults with ICD-10 depressive disorder or bipolar depression treated with electroconvulsive therapy (ECT), repetitive transcranial magnetic stimulation (rTMS), (es)ketamine, or selective serotonin reuptake inhibitors (SSRIs) between 2022 and 2024. Resting-state EEG with simultaneous ECG generated individualized biomarker reports with modality-specific response likelihoods. Treatment chosen by clinical teams was classified as concordant or non-concordant; response was derived from routinely collected clinical scales. Results: Among 153 patients (ECT n=53, rTMS n=48, (es)ketamine n=36, SSRIs n=16), response rates were higher for concordant vs non-concordant treatments: ECT 70% vs 50%, rTMS 30% vs 13%, (es)ketamine 31% vs 10%, and SSRIs 100% vs 11%. Overall, 46% (42/92) of concordant vs. 26% (14/54) of non-concordant patients responded (absolute difference +20 percentage points; relative increase {approx}77%; number needed to treat {approx}5). Conclusion: Concordance with EEG/ECG biomarkers correlated with higher treatment response, warranting confirmation in prospective trials. Significance: EEG/ECG-based decision support may enhance antidepressant treatment response in everyday clinical practice.

BackgroundA study conducted in Norway showed that the association between pupil mental health diagnoses and educational attainment has weakened over time. One possible explanation is that earlier detection of mental health problems in recent years has facilitated earlier treatment, intervention, and educational support that might improve academic outcomes. We investigated whether the weakening association between mental health and attainment could be replicated in England, and explained by earlier age at first diagnosis. MethodsThis was a secondary longitudinal data analysis of de-identified records from a secondary mental healthcare provider in England, which have been linked to the Department for Educations National Pupil Database. We included n=149,841 pupils residing in South East London, born 1993-2003, who completed their end-of-school exams 2009-2019. The main exposure variables were ADHD and internalising disorder diagnosis. In linear regressions, we investigated their associations with Year 11 attainment (typically assessed age 15-16 years), whether this was modified by birth year, and the role of age at first diagnosis. ResultsOn average, ADHD (n=844, 0.6%) and internalising disorder (n=2,523, 1.7%) were associated with lower Year 11 attainment. However, significant interactions between diagnosis and birth year suggested that pupils with these disorders showed increases in standardised exam scores over successive birth cohorts, resulting in a closing attainment gap over time. While age at first diagnosis became younger over the period, this did not confound the observed associations. ConclusionsWe replicated findings from Norway that suggest a narrowing attainment gap between those with and without ADHD and internalising disorder diagnoses. Building on this, we ruled out earlier age of diagnosis as a possible explanation for this phenomenon. With administrative data research growing internationally, we are increasingly able to replicate mental health and education trends in different countries, opening more opportunities for international collaboration.

BackgroundIntermittent theta burst stimulation (iTBS) and H-coil repetitive transcranial magnetic stimulation (rTMS) are FDA-cleared treatments for major depression; yet their comparative effectiveness in treatment-resistant depression (TRD) has not been evaluated in randomized trials. This pilot randomized trial was designed to obtain preliminary comparative estimates and to explore whether baseline cognitive functioning relates to early remission. MethodsTwenty-eight adults with TRD were randomized to six weeks of iTBS delivered to the dorsolateral prefrontal cortex (DLPFC) using a figure-8 coil (n=15) or H-coil rTMS delivered to the dorsomedial prefrontal cortex (DMPFC) using a H7-coil (n=13). The primary outcome was change in 17-item Hamilton Depression Rating Scale (HRSD-17) score from baseline to week 6, analyzed with ANCOVA. Additional outcomes included response, remission, and symptom trajectories through week 18. Exploratory analyses examined the association between baseline cognitive functioning, such as executive functions and memory, and remission. ResultsTwenty-five participants completed all 30 sessions. Adjusted week-6 HRSD-17 scores did not differ between groups (mean difference -0.40, 95% CI -5.23 to 4.43; p=.865). Response rates were 40.0% for iTBS and 50.0% for H-coil (p>.60), and remission rates were identical across groups (20.0%). Remitters showed higher baseline executive functioning than non-remitters in exploratory analyses, although these associations were not confirmed in adjusted models. ConclusionIn this pilot trial, iTBS and H7-coil rTMS showed symptom improvement, with no clear between-group pattern. Exploratory findings suggest a potential signal involving executive functioning that warrants further investigation. These results inform the feasibility and design of larger comparative trials. Trial registrationClinicalTrials.gov (NCT05902312)

Background: The incidence of antidepressant withdrawal reactions in longer-term users and the influence of dosage is insufficiently understood. Objectives: Informed by neuropharmacological models and user surveys, this study examined symptom change during tapering and if increases were specifically associated with reductions below 75% of the minimum effective dose. Design: This was a prospective longitudinal cohort study with seven assessments over six months. Methods: Altogether 32 Swiss adult primary care patients who were on antidepressants for at least six months and in stable remission were assessed at baseline (week 0) before they started tapering and after 2, 4, 6, 8, 16, and 26 weeks. Withdrawal symptoms were measured repeatedly using an adapted version of the Discontinuation-Emergent Signs and Symptoms Scale (DESS) and the main outcome was intra-individual symptom change during intervals. Antidepressant dose was standardized relative to the minimum effective dose in the treatment of depressive and anxiety disorders. Results: Across intervals, reductions below 75% of the minimum effective dose were associated with symptom increases, while reductions above that threshold or no reductions were associated with symptom decreases. After adjusting for potential confounders, the rate of clinically relevant symptom increases contingent on dose reductions below 75% of the minimum effective dose was 33%, as compared to 13% during intervals with no dose reductions (OR=3.2, 1.4 to 7.4). We thus estimated that 60% of the risk of clinically relevant symptom increases was attributable to pharmacological withdrawal effects. The adjusted incidence rates for clinically relevant and severe withdrawal reactions were 32% and 11%, respectively. Conclusions: Consistent with neuropharmacological research findings, we found that antidepressant withdrawal symptoms emerge mostly following reductions below 75% of the minimum effective dose, affecting about one-third of patients. Even small reductions may trigger clinically relevant withdrawal reactions in this lowest dose-range, stressing the need for personalized tapering plans.

Background: Participants in the ReINVEST randomised placebo-controlled trial of sertraline, conducted among men with high trait impulsivity and histories of violent offending, received structured clinical contact throughout the trial, including psychiatric assessments, nursing consultations, crisis support, and referrals to mental health and external services. We estimated the effect of placebo trial participation, compared with non-participation after baseline and single-blind run-in, on violent and domestic-violence reoffending. Methods: This prespecified secondary analysis included men from the ReINVEST trial pathway who completed baseline assessment and entered the single-blind run-in phase but did not proceed to randomisation, to inform the counterfactual. Violent and domestic-violence offences were identified from linked administrative records over 12- and 24-month follow-up periods. The adjusted difference in offending was estimated using two independent analytical approaches accounting for baseline differences. Additional analyses examined whether the effect varied by baseline clinical and criminal-history characteristics, whether pre-randomisation external referrals explained selection into placebo participation, and whether post-randomisation external referrals accounted for any part of the estimated effect. Results: Placebo trial participation was associated with lower offending across both outcome domains and follow-up periods. Placebo-standardised mean count differences for violent offending were -0.19 (95% confidence interval [CI] -0.38, -0.04) at 12 months and -0.22 (95% CI -0.51, -0.05) at 24 months. Corresponding differences for domestic-violence offending were -0.37 (95% CI -0.81, -0.14) at 12 months and -0.49 (95% CI -0.92, -0.22) at 24 months. The association was more apparent among men with a documented psychiatric history and, for domestic-violence offending, among those with higher baseline anger, irritability and aggression. Pre-randomisation referrals did not explain selection into placebo participation or materially alter the estimates. Post-randomisation referrals were observed in both groups, remained more common in the placebo group, and did not account for the observed association. Conclusion: Placebo participation in this trial involved sustained clinical contact and psychosocial support beyond exposure to inactive medication, and these non-pharmacological components may have contributed to lower reoffending. In placebo-controlled trials involving populations with high psychiatric morbidity and limited continuity of coordinated care, the clinical content of placebo participation should be explicitly characterised in trial design and interpretation.

Abstract Introduction: Over 30% of adults with Attention-Deficit/Hyperactivity Disorder (ADHD) show an insufficient response to standard pharmacological treatments, which underscores the need for evidence-based alternative interventions. Methods: In this sham-controlled study, 30 adult outpatients with ADHD were randomized to 12 weeks of active or sham transcranial direct current stimulation (tDCS) as add-on to a digital cognitive behavioral therapy application (dCBT app). Participants received either active (2 mA, 20 min/day, 5 days/week) or sham tDCS with anodal (left) and cathodal (right) stimulation applied over the dorsolateral prefrontal cortex (DLPFC). In parallel, access to the dCBT app was provided for three months. ADHD symptoms were measured before and after treatment and after a three-month follow-up using the Adult Self-Report Scale (ASRS v1.1). Results: All scales showed an improvement over time with medium-to-large within-subjects effects (Cohens d: -.48 to -.75), irrespective of group allocation. Two additional sensitivity analyses including (1) participants with over 75% of planned (sham)-tDCS sessions and (2) those who logged into the dCBT app on at least 5 days (median split) confirmed results. Response was observed in 1/15 (6.7%) of the tDCS group and 2/15 (13.3%) of the sham-tDCS group, with no difference between groups (p = .543, phi = -.111). Compliance to (sham-)tDCS was high. tDCS usability was rated marginally lower in the tDCS group. Conclusions: tDCS as an add-on therapy could not produce additional improvement in ADHS symptoms. The results are discussed in terms of contextual and patient-related aspects. ClinicalTrials.gov Identifier: NCT06766214.

ImportanceSuicide is a leading cause of death in the United States with risk strongly influenced by Interpersonal trauma, contributing to treatment resistance and clinical complexity. ObjectiveTo assess clinical and genetic factors in individuals who died from suicide, with and without interpersonal trauma exposure. DesignIndividuals who died from suicide with and without trauma were compared in a retrospective case-case design. Prevalence of 19 broad clinical categories was assessed between groups. Results directed selection of 42 clinical subcategories, and 40 polygenic scores (PGS) for further assessment. Multivariable logistic regression models, adjusted for critical covariates and multiple tests, were formulated. Models were also stratified by age group (<26yo and [&ge;]26yo), sex, and age/sex. SettingA population-based evaluation of comorbidity and polygenic scoring in two suicide death subgroups. ParticipantsA total of 8 738 Utah Suicide Mortality Research Study individuals (23.9% female, average age = 42.6 yo) who died from suicide were evaluated, divided into trauma (N = 1 091) and non-trauma exposed (N = 7 647) individuals. A subset of unrelated European genotyped individuals was also assessed in PGS analyses (Trauma N = 491; Non-trauma N = 3 233). Exposures"Trauma" is here defined as interpersonal trauma exposure, including abuse, assault, and neglect from International Classification of Disease coding. Main Outcomes and MeasuresPrevalence of comorbid clinical sub/categories and PGS enrichment in trauma versus non-trauma exposed suicide deaths. ResultsOverall, trauma-exposed individuals died from suicide earlier (mean age of 38.1 yo versus 43.3 yo; P <0.0001) and were disproportionately female (38% versus 21%, OR = 3.3, CI = 2.9-3.8). Prevalence of asphyxiation and overdose methods, prior suicidality, psychiatric diagnoses, and substance use (OR range = 1.3-3.7) were elevated in trauma exposed individuals who died from suicide. Genetic PGS were also elevated in trauma-exposed individuals who died from suicide for depression, bipolar disorder, cannabis use, PTSD, insomnia, and schizophrenia (OR range = 1.1-1.4) with ADHD and opioid use showing uniquely elevated PGS in trauma exposed males (OR range = 1.2-1.4). Conclusions and RelevanceResults demonstrated multiple convergent lines of age- and sex-specific evidence differentiating trauma-exposed from non-trauma exposed suicide death. Such findings suggest unique biological backgrounds and may refine identification and treatment of this high-risk group.