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.

Partner resemblance influences and reflects the social, genetic and health structure of human populations. Using Danish registers on 787,658 couples, we quantified partner resemblance for ten psychiatric disorders and socioeconomic status (SES), measured up to a year before first childbirth and across the life course. Psychiatric partner correlations ranged from 0.08 for eating disorders to 0.36 for schizophrenia, below those for education (0.63) and income (0.57). Income resemblance fell substantially across the life course (to 0.38), whereas education resemblance was stable. Psychiatric resemblance changed little across windows. Adjusting psychiatric liability for own SES reduced psychiatric partner resemblance, whereas adjusting SES for own psychiatric status barely affected SES partner resemblance. The reduction in psychiatric partner resemblance had a median of ~7% before first childbirth but ~26% across the life course, as diagnosis and SES became increasingly coupled within individuals. What psychiatric partner resemblance represents therefore depends on when it was measured.

Background: The course of major depressive disorder is heterogeneous, with UK Biobank (UKB) participants reporting episode durations ranging from <1 month to >24 months. Here, we identify predictors of episode duration, characterise its genetic architecture, and examine links to treatment seeking and response. Methods: In UKB participants meeting criteria for major depressive disorder, we examined clinical, sociodemographic, and genetic predictors of short (0-3 months) and long (>24 months) episode duration, fitted in predictor-specific, domain-level, and combined models. We also conducted genome-wide association studies in European-ancestry participants (n = 40,858) and estimated common-variant heritability. Results: Clinical features were most informative: higher childhood trauma scores, a stressful trigger, and recurrence showed the most consistent associations with short and long durations across models (ORcombined: short = 0.75-0.95; long = 1.13-1.45; all p[&le;]0.02). Higher neuroticism scores were also associated with both durations (ORcombined: short = 0.977; long = 1.053; p<0.001). Polygenic risk for depression was associated with episode duration, though its independent contribution was modest. Long episodes were more predictable than short in validation analyses (AUC = 0.705 vs 0.601) and were associated with greater treatment engagement but lower perceived benefit; SNP-based heritability was nominally significant. Conclusions: Clinical features captured most of the predictable variance in episode duration, with the same predictors largely operating in opposite directions for short and long episodes, consistent with a continuum of chronicity. Those at risk for long episodes emerge as a priority for early identification and intervention.

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.

Background: Interview-based suicide assessments are insufficient for near-term risk detection, but there are no evidence-based, high-performing alternatives. The Death Implicit Association Test (DIAT) has been proposed as a suicide risk assessment tool. However, traditional DIAT scoring methods exhibit limited association with suicidality. Methods: We tested whether temporal structure in reaction times (RTs) from the Brief Death Implicit Association Test (BDIAT) tracks active suicidal ideation (SI), which was ascertained by ecological momentary assessment (EMA). Seventy-seven participants who either did or did not endorse active SI during EMA (SI+ n=22; SI- n=55) completed 18 alternating blocks of the BDIAT (9 Life + Me, 9 Death + Me). We computed the conventional D-score, an aggregate index of self-life versus self-death associations, and separately treated RTs as time-varying signals, examining entrainment to block alternation and habituation during conflict-related trials. We then developed a bilinear logistic regression classifier to extract these temporal RT features and trained it to predict SI status, with performance validated using leave-one-out cross-validation. Results: The conventional D-score did not reliably classify SI+/SI- individuals. In contrast, temporal RT dynamics reveal group differences in block-level entrainment and trial-level habituation. A bilinear logistic regression classifier leveraging these dynamics predicts SI status with 77% balanced accuracy and AUC 0.799. Conclusions: Results demonstrate that temporal dynamics of RT during the BDIAT track active ideation and can be used to distinguish SI status at the individual level, implicating RT temporal dynamics evoked during BDIAT as a candidate behavioral marker of near-term suicide risk.

The present study examined the relationship between the DSM-5 diagnostic criteria for gambling disorder (GD) and gambling severity via an item response theory (IRT) analysis in two large German population survey data sets (Buth et al. (2022, 2024)). IRT-based person fit analyses may reveal atypical response patterns (e.g. endorsing criteria linked to higher levels of disorder severity, but not criteria linked to lower levels). We examined the link of such atypical response patterns and mental health as measured by the MHI-5, employing a 2-parameter-logistic (2PL) IRT model and a linear mixed model with random intercepts. Results largely replicated previously reported item severity rankings across both samples: GD criteria such as loss chasing and a preoccupation with gambling were generally linked to lower severity levels, whereas criteria such as withdrawal symptoms or job/family problems where generally linked to higher severity levels. Modelling revealed a reduced assessment sensitivity in lower gambling severity ranges. Furthermore, person fit analyses suggest that atypical symptom patterns may be linked to poorer mental health (MHI-5). Implications for the interpretability of total scores of endorsed criteria and the validity of diagnostic practices determining eligibility for treatment and financial compensation are discussed.

Background Youth involved in child protection systems are at increased risk of psychiatric disorders and are overrepresented in inpatient mental health services. However, few studies have directly compared the clinical characteristics and mental health service use of youth across different child protection pathways. Objective To compare clinical characteristics, psychosocial risk factors, clinical complexity, and mental health service use among psychiatrically hospitalised youth in foster care, adoption, and child welfare supervision. Participants and Setting This retrospective observational study included 236 children and adolescents across three child protection pathways admitted to a Child and Adolescent Inpatient Psychiatry Unit between 2018 and 2024. Methods Clinical, psychosocial, and service-use data were extracted from medical records and compared using univariate analyses, multilevel mixed-effects models, logistic regression, and time-to-event analyses. Results All groups showed high comorbidity and clinical severity, but distinct clinical profiles emerged. Youth in foster care more frequently presented with externalising disorders, trauma exposure, and substance use; adopted youth showed higher rates of neurodevelopmental and prenatal adversity-related conditions; and youth under child welfare supervision more often presented with affective symptoms and suicidal ideation. Post-discharge emergency department re-consultation differed significantly between groups (p = 0.007) and was most frequent among adopted youth, who also had higher odds of psychiatric readmission. Youth in foster care had the shortest median time to emergency re-consultation, although time-to-event differences were not significant (p = 0.476). Conclusions Distinct clinical and service-use profiles across child protection pathways support trauma-informed, placement-sensitive mental health care and stronger coordination between child protection and mental health services.

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.

Importance: Excess mortality associated with mental disorders is well established, but estimates are largely based on specialist psychiatric populations. Whether they characterize mortality in the broader diagnosed population is uncertain. Objective: To characterize heterogeneity in excess mortality by diagnosis, psychiatric care setting, substance use disorder (SUD), and time since diagnosis. Design: Nationwide population-based cohort study with follow-up from January 1, 2011, through December 31, 2023. Setting: Primary and specialist health care and population registers in Finland. Participants: Residents aged 5 to 95 years without a recorded prevalent mental disorder at cohort entry. Exposures: Mental, behavioural, and neurodevelopmental disorders classified using ICD-11, with time-varying psychiatric care setting and SUD status. Main Outcomes and Measures: All-cause mortality, mortality rate ratios (MRRs), and 10-year differences in restricted mean survival time (RMST). Results: Among 5,526,599 individuals (2,784,897 [50.4%] women), 1,463,064 (26.5%) received a mental disorder diagnosis. Excess mortality varied substantially by diagnosis, clinical subgroup, and time since diagnosis. Among those aged 5 to 64 years with any mental disorder, adjusted MRRs across care setting and SUD strata ranged from 1.54 (95% CI, 1.39-1.71) to 8.97 (7.86-10.24). MRRs were highest immediately after first diagnosis and declined during the first 2 to 3 years. At 3 years, MRRs for depressive, anxiety or fear-related, and stress-related disorders among individuals without SUD treated outside specialist psychiatric care ranged from 0.88 (0.79-0.98) to 1.20 (1.12-1.29) in men and from 0.81 (0.73-0.89) to 1.13 (1.04-1.22) in women, whereas MRRs for schizophrenia and other primary psychotic disorders remained 1.84 (1.60-2.12) in men and 1.55 (1.37-1.75) in women. Ten-year survival loss across all mental disorders was 0.53 years (95% CI, 0.53-0.54) in men and 0.34 years (0.33-0.34) in women and was greater for natural than external causes. Conclusions and Relevance: Excess mortality varied markedly by diagnosis, clinical context, and time since diagnosis and was small in some common disorders outside specialist psychiatric care without SUD. Estimates derived from specialist psychiatric populations or averaged across follow-up may therefore provide an incomplete picture of mortality in the broader diagnosed population.

Background: Various explanations have been proposed for increasing trends in diagnosed depression in the UK, including increases in the proportion of the population that experience symptoms, changes in the threshold for seeking treatment and changes in clinical recognition or coding practices. Identifying trends over time for the relationship between the experiences of psychological distress and receiving a diagnosis can help explain wider trends in the incidence of clinical depression, such as whether the threshold for seeking treatment and receiving a diagnosis of depression has changed. Aims: This study aims to examine trends in the incidence of diagnosed depression, and relationships between psychological distress and recent depression diagnosis among UK adults between 2011 and 2022. We also assess whether the difference in psychological distress between adults with and without a recent depression diagnosis has changed over time and examine these relationships across subgroups (sex, ethnicity, age, cohort, education and financial stress). Methods: Data were from 66,360 adults (341,764 observations) aged 16 or older from the UK Household Longitudinal Study (UKHLS) across nine fieldwork periods spanning 2011-2022. Psychological distress was reported with the GHQ-12 used as a continuous variable and as a binary variable indicating caseness. Recent depression diagnoses were self-reported. Analyses we run for the overall population and stratified by different sociodemographic characteristics. Results: Incidence of diagnosed depression has not increased over time in the overall sample, but there was a notable increase in some sub-groups, most clearly seen for women aged 16 to 24. There has been a clear increase in the number of cases of psychological distress, but who have not received a recent diagnosis of depression. The level of psychological distress experienced by adults recently diagnosed with depression has slightly increased over time, whilst the difference in psychological distress experienced by adults with and without a recent depression diagnosis remained stable. Subgroup analyses show differences in the distress experienced by those with and without a recent diagnosis based on sex, age, cohort, ethnicity, education and financial situation: temporal trends were mostly similar across groups. Conclusions: Stable trends in (a) the distress experienced by adults recently diagnosed with depression, and (b) the difference in psychological distress experienced by adults with a recent depression diagnosis compared to adults without suggests little support for the hypothesis that depression is being diagnosed at lower levels of psychological distress. Instead, our findings suggest there may be a growing population who are not receiving clinical support for high levels of distress.

Background: Previous trauma research includes many limitations, such as the scarcity of pretraumatic health measurements and assessment of traumatic experiences with a broad scope across the lifespan. To respond to these gaps, we aimed to develop a new, prospective, population-based trauma dataset from childhood to middle age. Methods: We used the Young Finns Study that is a population-based, multi-generational, prospective study (n = 3596 for the main generation). It has started in 1980 (baseline assessment) and includes follow-ups in 1983, 1986, 1989, 1992, 1997, 2001, 2007, 2011/2012, and 2018-2020. From the 38-year follow-up and ten measurement points of the YFS, we collected all relevant trauma variables, including both free-format and structured questions that both the participants and their parents responded to. By a data-driven case-to-case analysis, we developed a scale to numerically capture variation in the quality of the experiences. Results: Our final dataset captured a total of 7769 traumatic experiences. We also developed the Traumatic Experience Severity Scale (TESS), including six subscales such as shamefulness, rarity, danger to life or health, effects on everyday life, human-made physical threat, and whether the target person was within or outside one's household. We also preprocessed the dataset to be later easily interleaved with other psychological, cardiovascular, and epigenetic variables of the YFS. Conclusions: We believe this new trauma dataset with thousands of experiences across the lifespan provides new opportunities to multidisciplinary, lifelong trauma research.

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.

Stress-related disorders are among the most common and burdensome mental health conditions worldwide, yet the mechanisms that allow most trauma-exposed individuals to maintain or regain mental health remain poorly understood. Decades of research have focused on identifying risk factors for psychopathology rather than the active processes that promote resilience and recovery. Here, we present the study protocol for Stress and Trauma Resilience: Opportunities for National Growth (STRONG), a multi-tiered, multi-domain, multi-level investigation of resilience conducted in Israel in the aftermath of the October 7, 2023 attack and the prolonged national adversity that followed. STRONG uses a nested design that integrates nationally representative longitudinal data with in-depth neurobehavioral assessment. STRONG-1 is a longitudinal, population-based study of approximately 4,600 Israeli adults assessed across five waves over three years, characterizing individual, social, and societal predictors of resilience trajectories. STRONG-2 is a controlled laboratory study of highly resilient and highly vulnerable individuals selected from STRONG-1, assessing behavioral and physiological mechanisms alongside cognitive tests and ecological momentary assessment. STRONG- 3 examines a subset of these individuals in the MRI scanner, capturing structural and functional neural markers with synchronized physiological and eye-tracking data. Advanced computational approaches will integrate data across tiers, levels, and domains into predictive models of resilience. STRONG will establish Israel's first nationally representative dataset on stress resilience and provide a rare opportunity to study human adaptation at scale and in a real-world context. These findings will inform early detection strategies and the development of empirically grounded, modifiable targets for intervention.

Importance: Not in Education Employment or Training (NEET) in youth is associated with poorer mental health and is increasing. Prior work has treated NEET as a single status, obscuring whether repeated disengagement carries cumulative later mental health risk. Objective: Estimate associations between the number of NEET occasions between ages 16 and 33 years and depression, anxiety, wellbeing and a recent suicide attempt at age 33. Secondary analysis explored associations between age of first NEET and type of NEET with outcomes. Design, Setting and Participants: 3,792 individuals from a longitudinal population-based birth cohort (Avon Longitudinal Study of Parents and Children), followed from birth to age 33. Exposure: Number of NEET occasions, modelled as a count and as categories (0, 1, 2, 3+), the age of first NEET occasion and the type of NEET (single, sustained or recurrent occasions). Main Outcomes and Measures: Depression (SMFQ), anxiety (GAD-7), lower life satisfaction (SWLS), recent suicide attempt. Results: Each additional NEET occasion was associated with higher odds of depression (OR: 1.29 [95%CI: 1.18, 1.40], PFDR=3.04x10-08), anxiety (1.21 [1.11, 1.32], PFDR=7.54x10-05), lower life satisfaction (1.53 [1.40, 1.68], PFDR=2.26x10-19) and a recent suicide attempt (1.51 [1.28, 1.77], PFDR=1.17x10-06). Relative to never being NEET, odds of depression were higher at three or more NEET occasions (2.68 [1.74, 4.11], PFDR=1.76x10-05), while lower life satisfaction (5.97 [3.93, 9.05], PFDR=4.94x10-16) and a recent suicide attempt (7.40 [3.08, 17.80], PFDR=1.18x10-05) increased stepwise from one to three or more occasions. Associations were strongest for first NEET at ages 25 to 33, though first NEET between ages 16 to 20 was also associated with a recent suicide attempt (4.49 [2.20, 9.17], PFDR=6.51x10-05). Among those ever NEET, sustained and recurrent NEET showed little association beyond a single occasion, except for lower life satisfaction (2.60 [1.68, 4.02], PFDR=0.0001) and a recent suicide attempt (3.16 [1.23, 8.08], PFDR=0.042). Conclusions and Relevance: Repeated NEET status across adolescence and early adulthood was associated with poorer mental health at age 33, with dose-dependent associations for depression, life satisfaction and a recent suicide attempt. Our findings suggest that preventing repeated NEET and identifying mental health need at the point of first NEET entry, may be important targets for intervention and/or prevention of later poorer mental health.

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.

Background: Adolescent suicide is a leading cause of death in Australia, arising from multiple determinants. Psychological distress, lifestyle behaviours and socioeconomic factors are associated with adolescent suicidality. Existing research has predominantly employed cross-sectional designs, limiting our understanding of how these factors interact over time. Longitudinal and data-driven approaches are needed to help identify the factors associated with the emergence of suicidality throughout adolescence. Method: Participants aged 12-17 years completed longitudinal measures of suicidal ideation, psychological distress, sleep quality, mindfulness, physical activity, eating habits, and social connectedness. Subgroups were determined via hierarchical cluster analysis, based on average scores across later timepoints (9-15). ANOVA and pairwise effect size calculations were used to compare clusters across variables, and their preceding developmental trajectories were examined using generalised additive mixed models (across earlier timepoints; 1-8). Clusters were also compared on self-reported wellbeing, long-term suicidality, and socioeconomic status. Result: Three clusters characterised by low-, moderate-, and high-severity of suicidal ideation and psychological distress, and poorer sleep, social connectedness, physical activity, mindfulness, and eating habits were identified. Across earlier timepoints, the high-severity group showed consistently elevated suicidality and deteriorating wellbeing and lifestyle scores. Conclusion: Youth with high levels of suicidality had greater psychological distress, lower wellbeing, lower socioeconomic status, and poorer lifestyle behaviours. This subgroup was also found to have poorer scores on wellbeing and lifestyle factors in their early adolescence. Findings highlight the importance of early, preventative interventions targeting both mental health and lifestyle factors to reduce suicidality in adolescents.

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.