European Psychiatry

ObjectiveThe Concise Health Risk Tracking (CHRT) assessment has utility in suicide risk prediction in adults and adolescents. Because multi-informant assessment is the gold standard in pediatric populations, a parent report version of the CHRT may enhance evaluation of youth suicide risk. We adapted the self-report version of the 16-item CHRT as a parent report version (CHRT-PR16) and evaluated the psychometric properties and continuous age- and sex-specific norms in a nationally representative sample of parents. MethodParents of youth aged 6-18 years (N=2,236; 2,235 in sex-stratified analyses) completed the CHRT-PR16, enabling evaluation of both the 16- and 14-item (CHRT-PR14) version. Psychometric analyses included internal consistency, factor structure, Item Response Theory, measurement invariance, criterion validity, and continuous norming using Generalized Additive Models for Location, Scale and Shape (GAMLSS). ResultsInternal consistency was excellent for both CHRT-PR16 and CHRT-PR14 (both{omega} t =.98, =.96), although general factor variance was higher for CHRT-PR14 ({omega}H=.83) than CHRT-PR16 ({omega}H=.68). Mokken scale analysis confirmed zero monotonicity violations for CHRT-PR14. CHRT-PR16 showed a clinically trivial edge in criterion correlations with other measures of psychopathology. In GAMLSS modeling, a zero-inflated negative binomial distribution achieved optimal fit for both scales. Score trajectories diverged by age and sex around age 10, with males scoring slightly higher at upper percentiles. ConclusionsCHRT-PR16 and CHRT-PR14 demonstrate strong psychometric support, essential unidimensionality, measurement invariance, and optimal GAMLSS fit. Age- and sex-specific percentile lookup tables provide population-level benchmarks to guide measurement-based care, symptom tracking, and suicide risk stratification in pediatric settings.

Background: A comprehensive overview of how premature mortality in severe mental illness varies by socioeconomic position and healthcare utilization is lacking. Methods: We followed all Norwegian residents aged 30-79 years on January 1, 2008, through December 31, 2023. Nationwide registry linkage provided data on mental illness in primary and specialist care, educational attainment, and cause of death. We estimated the mortality gap as excess life-years lost from age 30 for depression, bipolar disorder, and schizophrenia compared with the general population, stratified by sex, healthcare utilization, and educational attainment. All-cause, external-cause, and natural cause mortality were assessed using competing risks. Results: The cohort comprised 2,486,836 individuals, including 483,933 with depression, 40,125 with bipolar disorder, and 21,963 with schizophrenia. Among men, the mortality gap ranged from 1.50 year (95% CI 0.36-3.34) among those with depression, non-inpatient care utilization, and university education to 19.86 years (18.34-21.36) among those with schizophrenia, inpatient care utilization, and less than high school education. Among women, the corresponding range was no gap to 18.16 years (17.03-19.53). Mortality gaps were generally larger with lower educational attainment and inpatient care utilization and increased from depression to bipolar disorder to schizophrenia. This pattern was consistent across sexes, diagnoses, healthcare utilization levels, and educational attainment levels and was most pronounced for natural-cause mortality. Conclusions: Premature mortality among people with severe mental illness forms a continuum across socioeconomic disadvantage, healthcare utilization, and diagnosis. Combining these measures can identify subgroups with the greatest mortality burden and may help target preventive interventions.

Importance. Suicide is a leading cause of mortality, yet its prevention remains a challenge. Suicide attempters exhibit disrupted decision-making, but the specific cognitive processes driving this impairment and their utility for risk stratification are unclear. Objective. To determine which computational decision-making mechanisms are disrupted in high-risk suicide attempters, and whether they distinguish attempters from depressed and healthy controls. Design. This cross-sectional study fit reinforcement-learning models to Iowa Gambling Task performance across two independent studies: SPAD (August 2017 to May 2020); SUICIDE-DECIDE (March 2021 to September 2023). Data was analyzed between January 2025 and July 2026. Setting. SPAD was conducted in Nimes (France). SUICIDE-DECIDE was a muticenter study across Jena (Germany) and Nimes. Clinical groups were recruited from academic inpatient psychiatry units and outpatient clinics, and healthy controls through local advertisement. Participants. SPAD included adults aged 60 years or older; SUICIDE-DECIDE middle-aged adults stratified by attempt means (violent/nonviolent). Consecutive participants were recruited into three groups: suicide attempters, patient controls, healthy controls. Main outcomes and measures. The primary outcomes were group differences on parameters reflecting learning from rewards and losses, sensitivity to win frequency, choice perseverance, and forgetting of past choices. We trained a multinomial logistic regression model in the SUICIDE-DECIDE study using self-reported depression and parameters that differentiated attempters from controls across studies, and evaluated its performance in the SPAD sample. Results. SPAD included 57 participants (40 females [70.2%]; mean [SD] age, 70.1 [8.2]). SUICIDE-DECIDE included 124 participants (77 females [62.1%]; 32.1 [11.0]). Suicide attempters forgot past choices faster than controls (SPAD: F(2,36) = 13.5; P < .001; SUICIDE-DECIDE: F(3,57) = 46.6; P < .001). No other parameter specifically differed in attempters across studies. In SUICIDE-DECIDE, greater forgetting of past choices was associated with attempter status only (RRR = 4.2, 95% CI [1.5, 11.5]). This parameter paired with depression severity correctly classified 87.2% of participants in SPAD (95% CI [74.3%, 95.2%], 41/47). Conclusions and relevance. Short-sighted decision-making may represent a cognitive phenotype associated with suicide in high-risk populations and a potential target for prevention and treatment.

Individuals with autism spectrum disorder (ASD) and co-occurring mood or psychotic disorders face substantially elevated suicide-attempt risk, but prior research is largely limited to population-level incidence and cross-sectional risk-factor studies, leaving unclear whether individual-level, prospective prediction is possible in this population. We conducted a retrospective prediction model study using Epic Cosmos electronic health record (EHR) data from 322,879 individuals with ASD and co-occurring mood or psychotic disorders to predict suicide attempts at the next clinical encounter using only information available at or before the preceding encounter. Five machine-learning algorithms were compared, with performance evaluated across discrimination, calibration, and clinical utility. All algorithms achieved strong discrimination using the full predictor set (AUROC 0.87-0.91). A parsimonious feature set (22 predictors) matched or exceeded full-model performance, with extreme gradient boosting (XGBoost) achieving the highest discrimination and standardized net benefit post-ablation (AUROC = 0.90; AUPRC = 0.34), though net benefit was comparable for elastic net and logistic regression. A prior suicide attempt was the strongest individual predictor. Decision-curve analysis indicated that model-guided decisions provided greater net benefit than treating all or no individuals across a broad range of clinically plausible thresholds. These findings demonstrate that near-term suicide-attempt risk can be predicted with high decision utility in this high-risk population using data already captured in routine care, suggesting a feasible basis for future EHR-based clinical decision-support tools.

Early detection of individuals at clinical high risk for psychosis (CHR-P) improves access to preventive care. We developed and internally validated the E-DetectioN Tool for Emerging mental disoRders (ENTER), a multimodal digital screener designed to improve community identification of CHR-P compared with an established approach (PQ-16 cut-off). Participants aged 12-35 years from the UK and Italy completed the online ENTER screener, assessing attenuated psychotic symptoms, processing speed and environmental risk factors. Participants above the PQ-16 cut-off and a random subset below were assessed with the Comprehensive Assessment of At Risk Mental States (CAARMS). PQ-16 cut-off and ENTER models were developed using (penalised) logistic regression, random forest and extreme gradient boosting (XGBoost) within a repeated nested cross-validation framework with semi-supervised learning incorporating unlabelled data. Models were evaluated by discrimination, calibration and clinical utility. 2,522 participants completed the ENTER screener. 495 underwent CAARMS assessments. 124 (25.1%) met CHR-P criteria; 2,027 participants were not assessed with the CAARMS (unlabelled). ENTER showed improved discrimination (C=0.744, 95%CI: 0.697-0.790) compared to the PQ-16 cut-off (C=0.625, 95%CI: 0.570-0.682, p=0.003) and similar calibration (ENTER: slope=1.02, 95%CI: 0.78-1.32; PQ-16 cut-off: slope=0.39, 95%CI: 0.19-0.52, p=0.074). At a clinically relevant threshold, ENTER identified approximately 2 additional CHR-P individuals per 100 assessments compared with the PQ-16 cut-off. Compared with established PQ-16 cut-off pre-screening, ENTER showed higher performance for community identification of CHR-P individuals. Multimodal digital screening might support more informative community triage before specialist assessment. External validation and implementation studies are required to establish real-world clinical utility.

Background: Substance use during pregnancy can substantially increase risk for postpartum depression and anxiety symptoms, which can have lasting effects on family functioning and child development. However, substance use is often conceptualized as a binary exposure, limiting our understanding of whether specific patterns of use are associated with maternal mental health in the perinatal period. Here, we examined longitudinal patterns of prenatal alcohol use and smoking in relation to maternal depressive and anxiety symptoms across pregnancy and the first two years postpartum. Methods: We analyzed prospective data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a population-based cohort from the UK. Alcohol and cigarette use were assessed across all three trimesters and modeled as longitudinal patterns (abstained, persistent, intermittent, discontinued). Maternal depressive and anxiety symptoms were measured from the second trimester through 21 months postpartum using the Crown-Crisp Experiential Index. Results: Persistent alcohol use was associated with higher depressive and anxiety symptoms and slower symptom declines over time, while women with intermittent or discontinued use had symptom profiles similar to abstainers. By contrast, persistent, intermittent, and quitting smoking patterns were associated with higher symptom levels overall, with persistent smoking additionally associated with steeper declines in symptoms over time. Conclusion: Our findings highlight the importance of considering the persistence and cessation of substance use during pregnancy in the context of maternal mental health, pointing to patterns of persistent substance use as a potential target to inform screening and early intervention for women at higher risk for perinatal psychological distress.

Background: Major depressive disorder (MDD) is associated with brain dysfunction and age-related diseases. Epigenetic clocks based on DNA methylation patterns estimate biological aging and aim to predict morbidity and mortality. Although MDD has been linked to epigenetic age acceleration (EAA) cross-sectionally, it is unknown whether EAA is associated with MDD after trauma. Methods: We included 706 participants (66% non-white, 64% female) from the multi-ancestry AURORA study, enrolled at emergency departments (ED) within 72 hours after trauma, from whom three age-adjusted epigenetic clocks were measured at enrollment: PhenoAge, GrimAge, and DunedinPACE. Functional MRI and assessment for probable MDD were conducted two weeks and six months later, respectively. Logistic and linear regression models tested the association of EAA with MDD and functional neuroimaging endpoints. Results: A total of 660 participants had available assessments of probable MDD six months after trauma, and from those 160 screened positively (24.2%) after trauma. EAA calculated by GrimAge (OR = 1.44, 95% CI = 1.12 - 1.85, p-adj= 0.012) and DunedinPACE (OR = 1.46, 95% CI = 1.15 - 1.85, p-adj = 0.005), but not PhenoAge (p-adj= 0.239), was significantly associated with MDD 6-months after trauma. Associations remained significant after adjusting for additional confounders, including prior trauma and disability (p= 0.008 for GrimAge, p= 0.010 for DunedinPACE). Subgroup analysis based on a median age split revealed these effects were only observed in participants 35 years of age or older. DunedinPACE was significantly associated with altered connectivity of fourteen brain network pairs after FDR correction (n = 217). Conclusions: EAA is associated with a higher risk of MDD after trauma and with concomitant brain connectivity changes. Calculation of GrimAge and DunedinPACE at the time of ED presentation may help recognize patients at risk for MDD, potentially improving personalized care after trauma.

Importance. Anorexia nervosa (AN) is a severe metabo-psychiatric disorder with heterogeneous outcomes and elevated mortality. Characterizing severity trajectories may improve early risk stratification and targeted intervention. Objective. To identify AN severity trajectories using a register-based severity index (AN-RSI) and examine their associations with polygenic scores (PGS), preceding (prior to AN diagnosis) as well as subsequent (5 years post AN diagnosis) psychiatric and somatic disorders. Design. Population-based cohort study. Setting. Nationwide study in Denmark. Participants. Individuals born between 1969 and 2013 with diagnosed AN (N = 9,534 individuals). Genetic data were available in a subsample comprising 5,126 individuals. Exposures. Forty-one PGS indexing traits relevant to AN, and psychiatric and somatic disorders prior to AN diagnosis. Main Outcomes and Measures. The main outcomes of interest were the AN-RSI trajectories and psychiatric and somatic disorders 5 years post AN diagnosis. Results. Three trajectories were identified: "low and stable" (32.6%), "medium and stable" (53.5%), and "high increasing" (14.0%). The "low and stable" group was used as the comparison group for all analyses. Each 1 standard deviation (SD) increase in AN PGS corresponded with 13% greater odds of following the "high increasing" trajectory. Increases in BMI and attention-deficit/hyperactivity disorder PGS corresponded with 15% and 14% lower odds of following the "high increasing" trajectory, respectively. No preceding psychiatric or somatic disorders were significantly associated with trajectory assignment. In contrast, psychiatric and somatic disorders were more likely to occur subsequent to an AN diagnosis in those in the "high increasing" trajectory with odds ratios (OR) ranging between 1.73 and 3.81 for psychiatric disorders and between 1.61 and 5.38 for somatic disorders with a notable exception of obesity which showed a lower OR of 0.27. Conclusions and Relevance. Our findings hold significant clinical relevance by demonstrating that individuals with AN follow distinct severity trajectories that have different genetic risk as measured by PGS and clear differences in post-diagnosis morbidity patterns but no discernable differences in pre-diagnosis psychiatric or somatic morbidity. As the eating disorders genetics field progresses, incorporating PGS into comprehensive assessments at first presentation may aid in early identification, personalized intervention, and resource allocation for individuals at higher risk of developing a severe illness trajectory.

BackgroundPsychotic-like experiences (PLEs) have been shown to increase the risk for mental health problems in later life, especially psychosis. Following previously raised methodological concerns about the assessment of PLEs in adolescents, this study sought to differentiate subtypes of PLEs and to explore their trajectories. MethodsLongitudinally matched data of 671 German adolescents from three surveys over the time span of one year were analysed. Four trajectories were identified, including persisting, subsiding, and emerging highly indicative PLEs (HIPs), and non-highly indicative PLEs (non-HIPs), and longitudinally compared in terms of associated distress, psychopathology, and substance use. A differentiated never PLEs group was considered as a control. ResultsThe persisting HIPs group reported greater distress than the non-HIP group over time and was consistently associated with higher rates of internalising symptoms. The subsiding HIP group showed significant reductions in distress and internalising symptoms over time, but no significant changes regarding externalising symptoms and substance use. There was no difference in the extent of substance use between the groups. ConclusionsScreenings of PLEs should be mindful of different subtypes of PLEs that indicate a greater associated risk of poor mental health. PLE screening should not stop at whether PLEs are present but ask which ones.

Suicide risk assessment in clinical conversations relies on the sequential structure of therapist-patient dialogue, yet formal models of how suicide-related content emerges, transitions, and re-ciprocates across conversational turns are lacking. We applied network analysis to C-SSRS-coded utterances from psychotherapy sessions to characterize the topology and dynamics of suicide-related clinical communication. Transcripts of 110 psychotherapy sessions from the SPEAK-SAFE study were classified for suicidality relevance using the Qwen3-32B large language model with an adapted Columbia-Suicide Severity Rating Scale (C-SSRS) schema. From the suicidali-ty-relevant utterances, we constructed a weighted directed category transition network. Centrali-ty, reciprocity, clustering, assortativity, and path length metrics were computed. Independent human expert ratings for a session-level subsample of 30 sessions from this cohort showed sub-stantial agreement with the LLM classifications (Spearman {rho} = 0.885, ICC[2,1] = 0.708). The network was dominated by therapist inquiry. Reciprocity was high, and closeness centrality de-creased monotonically with C-SSRS severity. Active suicidal ideation functioned as a bridge node from which escalation pathways to method, plan, and attempt categories originated. The network exhibited a hub-and-spoke topology with small-world characteristics. Suicide-related clinical dialogue is structured as a therapist-centered hub-and-spoke network with high reciproci-ty and a consistent severity-peripherality gradient. The extension of network theory from intra-individual symptom structures to inter-individual communication dynamics represents a method-ological innovation demonstrated here as a proof of concept, with potential applications to clini-cal training, automated decision support, and multimodal risk assessment. clinical interviews clin-ical interviews

Background: Autistic people experience substantially higher rates of mental health conditions and are overrepresented in mental health services. However, most interventions and service models have been developed for non-autistic people, and evidence is needed as to whether there are disparities in outcomes. This systematic review aimed to compare outcomes between autistic and non-autistic people receiving the same mental health interventions or services. Methods: We conducted a systematic review following PRISMA guidelines (PROSPERO: CRD420251021068). We searched academic databases (MEDLINE, Embase, PsycINFO, PubMed, CINAHL), a grey literature database (HMIC), a trial registry (ISRCTN), preprint servers (medRxiv and PsyArXiv), Google, and Google Scholar, to identify relevant papers published 01/01/1992-30/04/2026. We conducted backwards and forwards citation searching and contacted experts. Study quality was assessed using a modified Critical Appraisal Skills Programme Cohort Study Checklist and the Autism-Inclusive Research Assessment (AIRA). Data were synthesised narratively, with random effects meta-analyses where appropriate. Results: Thirty-nine studies were included, comprising 4787730 participants, assessing outcomes of psychological therapies (n = 17) and multi-component or service-level approaches (n = 22). Nearly half (46.2%) were UK-based, and under a quarter (23.1%) included people with intellectual disabilities. Ten studies (25.6%) were rated low quality, twenty-two (56.4%) medium quality, and seven (17.9%) high quality. AIRA ratings highlighted concerns about research inclusiveness for autistic people, including limited involvement of autistic people and lack of validated or adapted outcome measures. Findings varied by intervention: for some, multiple large, higher-quality studies showed less favourable outcomes for autistic people (e.g., less improvement in symptoms or functioning, or higher rates of restrictive practices or acute service use). For other interventions, comparable or mixed outcomes were found across studies, with interpretation often limited by small samples. Conclusions: Mental health treatment outcomes for autistic versus non-autistic people varied across interventions and outcome types. Where significant differences were observed, these usually showed poorer outcomes for autistic people, although they generally reflected smaller improvements rather than a lack of benefit. Action is needed to improve the accessibility and appropriateness of mental health care for autistic people, supported by more high-quality, co-produced research across a broader range of countries and service contexts.

Objective: To evaluate the psychometric properties, factor structure, validity, and age- and sex-specific norms of the 21- and 10-item parent-report Child Mania Rating Scale (CMRS-P) in a nationally representative U.S. sample of youth aged 6-18 years. Method: Parents of 2,229 youth aged 6-18 years [weighted M(SD)=12.0(3.3) years; 45.9% female] completed the CMRS-P and related measures between July 2025 and March 2026. Data were weighted to represent U.S. demographics. A clinical comparison sample included parents of 522 youth seeking outpatient mental health services. Complete-case analyses evaluated reliability, factor structure, item response theory, measurement equivalence, retest stability, and convergent and discriminant validity. GAMLSS estimated age- and sex-specific norms. Results: Weighted mean scores were 8.5(SD=9.0) for CMRS-P-21 and 4.0(4.3) for CMRS-P-10. Internal consistency was high ({omega}=.97/.93), and forms correlated .95. A general severity factor explained most reliable variance ({omega}H=.94). Three items differed in response thresholds across samples, with an average impact below one point on expected total scores. Both forms correlated strongly with attention problems, suicidality, depression, externalizing symptoms, and emotion dysregulation (r=.51-.63 for CMRS-P-21) and negligibly with pubertal status. Reliable-change thresholds were 14.5 (CMRS-P-21) and 6.8 (CMRS-P-10) points. Weighted GAMLSS CMRS-P-21 95th percentiles declined with age in males (30-23) and increased in females (22-30), with wide bootstrap intervals at age extremes; the female trend was not replicated without weights. Conclusions: Findings support both CMRS-P forms for assessing youth manic symptoms. The first nationally representative U.S. norms provide age- and sex-adjusted benchmarks for interpreting scores and informing further clinical assessment.

Background: Dissociative identity disorder (DID) is associated with frequent psychiatric comorbidity. Its complex and overlapping symptom profile can complicate recognition of both DID and co-occurring psychiatric conditions, contributing to diagnostic uncertainty. Evidence regarding psychiatric comorbidity is limited and prevalence estimates vary across studies. Aims: This meta-analysis aimed to examine the prevalence of psychiatric comorbidities in DID and factors associated with variation in prevalence estimates. Methods: Eligible studies were identified through PubMed, Scopus, Embase, PsycINFO, and MEDLINE from 1980 to 25 April 2026 (PROSPERO, no. CRD420261335819). Studies reporting psychiatric comorbidity in adults with DID were independently screened by two reviewers. Risk of bias was assessed. Random-effects meta-analyses using logit-transformed prevalence estimates were conducted. Meta-regressions examined moderators, whilst influence and sensitivity analyses assessed robustness. Certainty was evaluated using the GRADE approach. Results: Twenty-four studies (N = 858) contributed to the meta-analysis across 23 psychiatric comorbidities. Among individuals with DID, posttraumatic stress disorder had the highest pooled prevalence (87.44%, 95% CI 71.79-94.96), followed by major depressive disorder (62.64%, 95% CI 33.45-84.84), and borderline personality disorder (47.05%, 95% CI 34.21-60.32). Substantial heterogeneity was noted across most estimates. Meta-regressions identified significant associations with participant characteristics, recruitment, study quality, and diagnostic method. Risk of bias and certainty of evidence were heterogenous. Conclusions: Psychiatric comorbidity in DID is substantial and spans multiple diagnostic categories, although considerable heterogeneity and methodological variation limit confidence in prevalence estimates. Standardised diagnostic assessment, more representative sampling, and longitudinal research are needed to clarify the extent and clinical significance of comorbidity in DID.

Objective: The Genetic Risk for Serious Mental Illness and Development ("Paisa Kids") Study is establishing a longitudinal cohort of 3,000 youth enriched transdiagnostically for risk for serious mental illnesses (SMI; i.e., schizophrenia, bipolar disorder, and severe depression) from the Paisa region of Colombia. Its objective is to clarify the early clinical, neurobehavioral, genetic, and environmental profiles associated with later SMI and distinguish transdiagnostic from disorder-specific pathways. This paper describes the study infrastructure, recruitment streams, and baseline assessment battery, and characterizes the first two-thirds of the cohort. Method: Youth aged 6-15 years are being recruited. Youth recruited for high SMI risk either have a first or second degree adult relative with a SMI diagnosis or a psychiatric diagnosis themselves identified through electronic medical records (EMRs) associated with later SMI. Lower-risk youth have a relative without a SMI diagnosis. Baseline measures include psychiatric and developmental history, neurobehavioral functioning, environmental exposures, and genome-wide genotyping. Psychiatric EMRs provide longitudinal follow-up. Results: Among 2,384 participants enrolled thus far (mean age=11.2 years, 45.0% female), 2,211 were recruited for high SMI-risk and 173 for lower SMI-risk. Overall, 73.2% met criteria for a history of one or more psychiatric disorders. Logistic regression comparing rates of diagnoses and ACEs between recruitment streams showed elevated rates of depressive and anxiety disorders, attention-deficit/hyperactivity disorder, oppositional defiant disorder, and several ACEs among high versus lower SMI-risk youth. Conclusion: Integrating multidomain phenotyping, genomic data, and longitudinal EMR follow-up, the Paisa Kids cohort provides a unique resource for investigating pathways of risk and resilience to SMI.

Background. Population-representative evidence on social inequalities in youth mental health from an intersectional perspective is limited. We investigated inequalities across multiple mental health outcomes among young adults and examined whether measures operated equivalently across social and intersectional groups. Methods. Cross-sectional analyses were conducted with 9,675 participants aged 23 years from the nationally representative UK Millennium Cohort Study (born 2000-2002). Self-reported outcomes included psychological distress (Kessler-6), probable serious psychological distress/'caseness' (Kessler-6 score [&ge;]13), psychological wellbeing (Short Warwick-Edinburgh Mental Well-Being Scale; SWEMWBS), past-year self-harm, and lifetime suicide attempts. Measurement invariance analyses assessed comparability of the Kessler-6 and SWEMWBS across groups. Intersectional MAIHDA examined inequalities by sex assigned at birth, ethnic identity/background, sexual identity, and childhood poverty. Young people with lived experience of mental ill-health and/or social discrimination contributed to study design, interpretation, and reporting. Findings. Large inequalities were observed across all outcomes, with the largest disparities by sexual identity, followed by sex assigned at birth, childhood poverty history, and ethnic identity/background. Across intersectional strata, predicted psychological distress ranged from -0.27 to 1.32 SDs, and psychological wellbeing from -0.54 to 0.11 SDs. Predicted prevalence varied 6.99-fold (9.81% to 68.55%) for psychological distress 'caseness', 6.84-fold (8.60% to 58.79%) for self-harm, and 22.10-fold (1.96% to 43.32%) for suicide attempts. Young people at the intersection of sexual minority status, female birth sex, childhood poverty, and some ethnic minority identities/backgrounds experienced particularly poor outcomes. Most inequalities showed cumulative patterns consistent with additive expectations, although some intersectional groups experienced better or worse outcomes than expected. Accounting for measurement differences revealed inequalities that were otherwise undetected. Interpretation. Findings highlight the large extent of mental health inequalities when multiple dimensions of social (dis)advantage are considered, and the need to address both the social conditions generating these inequalities and the methodological assumptions shaping how they are measured and understood.

Brief assessments reduce clinician and patient burden and increase utilization. Recently, five core depression symptoms (low mood, poor concentration, low self-worth, loss of interest, low energy) have been shown to be particularly sensitive to treatment effects in adults. How these core depressive symptom domains perform for screening or diagnostic purposes in youth is unknown. To address this question, we extracted five analogous symptom items from four widely used symptom assessment tools for children and adolescents (Child Behavior Checklist [CBCL], Youth Self Report [YSR], Parent General Behavior Inventory [P-GBI], and Adolescent General Behavior Inventory [A-GBI]) to create 5-item short forms. We evaluated their psychometric properties and diagnostic utility in a large (N=1185), racially diverse sample (48% Black youth) across community and academic outpatient mental health settings, with diagnoses established through LEAD consensus. All short forms correlated highly with full-length measures (r=.74-.92) and demonstrated comparable inter-item correlations (r =.19-.46). The short forms did not differ meaningfully from the full measures in correlations with psychiatric diagnoses, demographics, or diagnostic interviews. Area under the curve (AUC) values for identifying depression and any mood disorder diagnosis (determined by semi-structured diagnostic interviews) were fair to good (AUC=0.60-0.79), which were not worse than full measures, except for the P-GBI. The CBCL-5, YSR-5, P-GBI-5, and A-GBI-5 may be useful brief depression assessments in youth. How these five symptom domains perform as outcome measures in treatment deserves study.

Background: Major depressive disorder (MDD) is a heterogeneous condition characterized by neuro-immune-metabolic-oxidative stress (NIMETOX) pathways. A systems-biology approach may help elucidate how these interconnected NIMETOX disturbances relate to early-life adversity and multidimensional clinical phenomes in adolescent MDD. Objectives: This study aimed to define the peripheral metabolic, vascular, and acute-phase, oxidative, and lipid biomarker profiles of adolescent MDD and to investigate associations with ACEs and clinical phenotypes. Methods: This cross-sectional study recruited 80 adolescents with MDD and 53 matched healthy controls and assessed C-peptide and insulin, vascular tone markers, the acute-phase inflammatory axis, oxidative stress, and lipid profiles. Results: MDD adolescents exhibited significant reductions in C-peptide, NO, ApoE, ApoA1, HDL-C, albumin, and transferrin, together with increased ApoB/ApoA1 ratio. These biomarkers correlated significantly with family dysfunction, childhood trauma, bullying exposure, and maladaptive parenting. These biomarkers and stressors accounted for 46.2% to 61.2% of the variance in psychological resilience, and major affective, physiosomatic, self-injurious, suicidal, and self-regulation phenomes. ACEs and bullying exposure, together with relevant socio-demographic data, explained 10.5% to 28.4% of the variance in selected metabolic, vascular, and acute-phase biomarkers. Multivariable classification models showed adequate discrimination between MDD and healthy controls, achieving up to 88.5% classification accuracy and an AUC of 0.948. Conclusion: Adolescent MDD is characterized by coordinated reductions in negative acute-phase proteins, metabolic and lipoprotein protective factors, and endothelial NO, without overt CRP-defined inflammation or conventional dyslipidemia. These findings support a systems-biology model of impaired peripheral homeostatic protection associated with developmental adversity and multidimensional depressive phenomes.

Background: Antidepressant selection in major depressive disorder remains trial-and-error, and no biomarker identifies which drug will work for an individual patient. Because neuroplasticity is a convergent mechanism of antidepressant response, we tested whether it could serve as a drug-specific biomarker in patient-derived neurons. Methods: We developed the Neuroplasticity Score (NPS), integrating structural and synaptic features from high-content imaging of patient-derived cortical neurons, and validated it against graded brain-derived neurotrophic factor (BDNF) exposure in neurons from 16 healthy donors. NPS was then applied unmodified to 75 antidepressant treatment episodes from 44 patients across two independent retrospective cohorts: 40 episodes from 20 STAR*D participants (Cohort 1; USA multi-site) and 35 episodes from 24 participants at Sheba Medical Center and Geha Mental Health Center (Cohort 2; Israel). Results: NPS increased with escalating BDNF dose (Spearman rho=0.83; P<.001). Response rate rose monotonically across NPS tertiles in both cohorts (trend P=.001 and P<.001). Across all 75 episodes, 84.6% of episodes in the highest NPS tertile responded, compared to 48.0% overall. NPS discriminated responding from non-responding episodes with an area under the receiver operating characteristic curve of 0.81 in both cohorts. The pooled odds ratio per 1-SD increase was 6.05 (95% CI, 2.80-13.05; I-squared=26%). Within patients contributing both a responding and a non-responding episode, the highest-scoring drug was the one that worked in 86% of patients (P<.001). Conclusions: Higher antidepressant-induced neuroplasticity in a patient's own neurons corresponded to a higher likelihood of response to that specific drug across two independent cohorts.

Objective A diversity of approaches and cohorts have been published in research literature for suicide risk estimation, leading to some uncertainty around which factors and conditions are most strongly contributing to risk. Methods exist for weighting estimates by propensity score, removing simplifying the interpretation of model effects. Few studies have explored the use of these tools to assess when the effect of certain factors is uncertain or inconsistent. Method A mix of 1,001,737 suicide decedents and living patients were evaluated for suicide risk, relying on a subset of commonly identified factors: demographics, psychiatric conditions, substance use disorders, and social needs. Care utilization patterns were then assessed controlling for these factors in a hospital care setting. Four methods were considered for controlling multivariate confounding of odds predicting death by suicide: multivariate logistic regression, 1-to-1 sample matching, inverse propensity weighting (IPTW), and entropy balancing (EBAL). Results Test statistics showed suicide decedents were much more likely to have various psychiatric and substance use diagnoses, social needs and more likely to heightened care utilization across sampling intervals. Greater utilization was found close to date of death. Effect sizes after IPTW and EBAL weighting were also generally greater than would have been documented by regression alone. Conclusions Propensity weighting is a useful alternative to exploring nuanced effects, especially when the direction and strength of an association differ from traditional statistics. By weighting, the overall imbalance of cases remains consistent and effect terms might reflect more nuanced associations than regression or sample matching alone.

Background: Alcohol use disorder (AUD) is associated with increased dementia risk, but its long-term relationship with dementia, variation by age and subtype, and how this risk compares with that associated with alcohol consumption remain poorly characterised. We investigated these questions in a large prospective cohort of UK women. Methods: We analysed Million Women Study participants recruited aged 50-64 years and followed for more than 20 years through linked health records. Women with hospital-recorded AUD were matched to up to five controls. Cox models estimated associations between time-varying AUD and incident dementia overall, by subtype and attained age, with exposure lags of up to 15 years and competing-risk analyses. Self-reported alcohol consumption was analysed separately. Findings: Among 1,288,359 women, 20,070 with AUD were matched to 100,339 controls. Dementia occurred in 3,774 women with AUD and 8,239 matched controls. AUD was associated with all-cause dementia (HR=3.73 [95% CI 3.52-3.95]), with strongest associations for mixed (5.03 [3.88-6.51]), unspecified (4.29 [3.92-4.70]), and vascular dementia (3.96 [3.44-4.56]). Associations were substantially stronger before age 70 years (10.68 [9.02-12.63]) than at ages 70-79 years (3.75 [3.47-4.04]) or 80 years or older (2.34 [2.11-2.60]). Risk remained elevated with a 15-year lag (2.16 [1.81-2.58]) and after accounting for competing mortality. Associations with self-reported alcohol consumption were substantially weaker. Interpretation: Clinically recognised AUD identifies women at markedly increased and prolonged dementia risk, particularly at younger ages and for vascular and mixed dementia, not captured by drinking quantity alone. People with AUD should be considered a priority population for earlier dementia prevention and risk reduction. Funding: Wellcome Trust Career Development Award to AT (306069/Z/23/Z); NIH grants P50AA012870 and R01DA054869 (JG). The Million Women Study is supported by the UK Medical Research Council (grant number UKRI1464).