Journal of Psychopharmacology

Psilocybin shows therapeutic promise for several psychiatric disorders, but the acute perceptual and cognitive alterations produced by conventional doses (10-25 mg) require in-clinic supervision, which limits scalability. Whether the therapeutically relevant pharmacology of psilocybin can be separated from its hallucinogenic activity remains unresolved. To address this gap, we conducted a Phase 1, randomized, double-blind, placebo-controlled, single ascending dose study to characterize the safety, pharmacokinetics and pharmacodynamics of low doses of psilocybin. Fifty-six healthy adults received a single oral dose of psilocybin (0.5, 1.0, 1.5, 2.5, 3.5 or 4.0 mg) or matching placebo across seven sequential cohorts, with each dose escalation reviewed by a Drug Safety Review Committee. All participants completed the study with no serious adverse events or discontinuations. Treatment-emergent adverse events were comparable to placebo and most prominently arose as somnolence. Plasma psilocin appeared rapidly with a median time to maximum concentration < 1 h with dose-proportional exposure and a short terminal half-life. Subjective drug effects were dose-related and became distinguishable from placebo at doses at or below 2.5 mg. Peak subjective ratings increased with dose, while any signs of hallucinations or altered-states scores remained low and not different than placebo. Psychophysiological engagement was confirmed by a clear dose-dependent pupillary dilation while cognitive performance (attention, vigilance, working memory, impulse control) showed no dose-dependent decrement and state anxiety did not increase at any dose. These findings indicate that the perceptible pharmacology of psilocybin can be dissociated from significant perceptual alterations and cognitive impairment at low doses. They further support controlled investigations in outpatient Phase 2 studies evaluating the safety and feasibility of repeated, self-administered low-dose psilocybin. ClinicalTrials.gov #NCT07710027

Background. UK clinical guidance recommends that structured risk prediction tools and risk stratification should not be used in self-harm, to predict suicide or determine who is offered treatment. Underpinning this position is the premise that routinely collected health data contain no useful predictive signal, which has received little direct scrutiny. Objective. To test whether routinely collected electronic health record data can distinguish groups at higher and lower risk of severe outcomes following paracetamol overdose. Methods. We analysed 4,095 adults presenting to NHS Lothian emergency departments with paracetamol overdose (2017-2023). Elastic-net logistic regression was fitted to 37 routinely collected electronic health record features to predict a composite of death or mental health inpatient admission at 0-7, 8-30 and 31-365 days following attendance, evaluated on a held-out 20% test set with bootstrapping. Findings. Events occurred in 5.5% of patients at 0-7 days, 2.0% at 8-30 days and 7.9% at 31-365 days, dominated by mental health admission. Bootstrap AUROC 95% confidence intervals lay above 0.5 in every window (0.65-0.82, 0.63-0.90, 0.71-0.85): models ranked patients better than chance. Calibration slopes (1.04, 1.14, 1.07) were close to one. Ranking drew primarily on mental health-related features. Conclusions. Routinely collected health data carried predictive signal for severe outcomes after paracetamol overdose, although discrimination fell short of what is needed for individual-level clinical use. Clinical implications. These models are not proposed for clinical deployment; however, treating risk prediction as a settled question will redirect research efforts, potentially excluding this patient population from machine learning advances driving improvements in care in other medical specialties.

Background: Bidirectional next-day associations between sleep disturbances and affective symptoms have been shown in previous research, yet the consecutive day effects between these factors remains poorly understood. Methods: We analysed longitudinal ecological momentary assessment (EMA) data obtained from a subsample of young persons in the Brazilian High-Risk Cohort (BHRC) study collected in 2020-2021. Participants reported sleep quality each morning and rated affective symptoms relating to mood, anxiety, and energy four times daily for 28 days. We selected 88 individuals (17.83{+/-}1.74 years, 56 [63.6%] female gender) with at least one instance where individuals were observed three-days in a row. Within-person bidirectional next-day effects between sleep quality and affective symptoms were estimated using mixed-effects regression analysis adjusting. We then applied g-estimation approaches to estimate the effect that lagged sleep quality and consecutive improvements in sleep quality had on affective symptoms. Results: Sleep quality and affective symptoms had bidirectional next-day effects, with sleep quality tending to have greater influence on affective symptoms than the reverse. Improved lagged sleep quality had positive effects on affective symptoms incrementally above the prior night's sleep quality. Also, improvement of sleep quality across consecutive days had incremental and approximately equal effects on affective symptoms. Conclusions: Sleep quality and affective symptoms exhibit a feedback loop, whereby poor sleep quality influences affective symptoms over consecutive days. Breaking these feedback loops, by improving sleep quality across several consecutive nights should improve affective symptoms. This supports interventions that target sustained improvement in sleep and possibly circadian regulation to improve affective symptoms.

Lithium has been the gold standard for the treatment and prevention of relapse in bipolar disorder for over 60 years. Guidance from the National Institute for Health and Clinical Excellence states explicitly to 'offer lithium as a first-line, long-term pharmacological treatment for bipolar disorder'. Yet, in the last two decades its use has been in decline with clinicians favouring anticonvulsants or antipsychotics when treating this condition. In this study, we have used three openly available datasets containing prescribing data from primary and secondary care to explore trends in the use of lithium in England, showing both regional and temporal variance between 2015-2024. We have shown that lithium use declined in primary care by 20.9% in the last ten years (2015-2024) and 10.9% overall in the last five years (2019 to 2025). We have also shown how there is some regional variation in the source of lithium for patients, although the vast majority is prescribed in primary care. Further research into clinical behaviour is needed to understand what is driving the decrease in lithium usage, and what barriers and enablers may influence its use across the country.

Purpose This study aimed to examine the association between screen time and depressive symptoms among Chinese college students, and to investigate the mediating roles of sleep quality and emotion regulation in this relationship. Furthermore, a serial mediation model was constructed to elucidate the underlying psychological mechanisms linking screen exposure to depression. Methods A stratified cluster sampling method was employed to recruit 10,999 college students for a cross-sectional questionnaire survey. Data were collected on screen time, sleep quality, emotion regulation ability, and depressive symptoms. Descriptive statistics, correlation analyses, and regression analyses were conducted using SPSS 26.0 A serial mediation model was tested using the PROCESS macro (Model 6), and bootstrapping procedures were applied to estimate the significance of indirect effects. Results Correlation analyses indicated that screen time was significantly positively associated with depressive symptoms (r = 0.16, p < 0.01) and sleep quality (r = 0.15, p < 0.01), and significantly negatively associated with emotion regulation (r = -0.13, p < 0.01). Sleep quality was positively correlated with depressive symptoms (r = 0.31, p < 0.01), whereas emotion regulation was negatively correlated with depressive symptoms (r = -0.42, p < 0.01). Regression analyses further showed that screen time significantly positively predicted depressive symptoms ({beta} = 0.712, p < 0.001), positively predicted sleep quality ({beta} = 0.217, p < 0.001), and negatively predicted emotion regulation ({beta} = -0.085, p < 0.001). In addition, both sleep quality ({beta} = 1.318, p < 0.001) and emotion regulation ({beta} = -0.424, p < 0.001) were significant predictors of depressive symptoms. Mediation analyses demonstrated that sleep quality significantly mediated the association between screen time and depressive symptoms (95% CI [0.239, 0.332]), as did emotion regulation (95% CI [0.269, 0.416]). Moreover, a significant serial mediation effect of sleep quality and emotion regulation was observed in the relationship between screen time and depressive symptoms (95% CI [0.082, 0.117]). Conclusion Screen time is significantly associated with depressive symptoms among college students, with sleep quality and emotion regulation serving as important mediating mechanisms. Extended screen exposure may be linked to higher levels of depressive symptoms by impairing sleep quality and weakening emotion regulation capacity.

Background: Actigraphy-derived rest-activity rhythm (RAR) features are widely used to characterize clinical states in bipolar disorder (BD). Both mean levels and temporal variability of these features have been associated with mood episodes; however, variability measures are often statistically coupled with the mean, particularly in skewed distributions. This raises a question as to whether variability reflects a separate characteristic of the data or whether the observed association arises from statistical properties of the data. Objective: In this study, we aim to determine whether temporal variability of actigraphy-derived RAR features provides standalone information on mood episodes in BD beyond mean activity levels after accounting for mean-variance dependence. Methods: We analyzed actigraphy data from a subset of 72 participants with BD drawn from a larger longitudinal study, extracting 22 daily RAR features aggregated weekly as sample mean (MEAN) and within-week temporal variability computed as sample standard deviation (VAR). Variance-stabilizing transformations (Box-Cox or Yeo-Johnson) were applied to the entire study cohort to reduce mean-variance dependence. Associations with mood episodes and remission (mania: n=34; depression: n=58 annotated participants) were evaluated using generalized linear mixed-effects models with a logistic link function, including univariate (MEAN or VAR) and multivariate (MEAN+VAR) specifications, assessed by likelihood-based metrics and the area under the receiver operating characteristic curve (AUC). Results: Transformations reduced mean-absolute correlations from 0.43 to below 0.06. Temporal variability remained significantly associated with clinical state for 11/22 RAR features in mania and 16/22 features in depression, with all significant associations remaining after false discovery rate correction (p<0.05). Joint models showed modest incremental gains (AUC 3%-4% overall; up to 12% in mania, 7% in depression), with absolute performance remaining limited (AUC 0.50-0.66). In both mania and depression, nearly all significant variability-based regressors contributed incremental information beyond mean-based models. Only sleep duration and activity changes around wake time (+-1 hour), did not improve discrimination between mania and remission. Conclusions: Temporal variability in RAR features can be considered a standalone state marker of mood episodes not captured by mean activity. We found it to be more consistently associated with depression than mania. Its incremental discriminative contribution is modest, suggesting greater utility within multivariate or multimodal frameworks.

Air pollution exposure has been associated with increased risk of developing mental health problems. It is possible that individuals at high genetic risk for psychopathology may be more vulnerable to these effects; however, this question remains to be investigated. We leveraged longitudinal data from n=10,620 participants from the Adolescent Brain Cognitive Development Study to first investigate sex-stratified associations of particulate matter (PM2.) exposure and genetic risk with mental health trajectories across 9-16 years including internalizing symptoms and psychotic like experiences (PLEs). Additionally, we tested whether genetic risk for schizophrenia (PRS-SCZ) and major depressive disorder (PRS-MDD) exacerbate the association with PM2. exposure and change in symptoms over time. PM2. exposure was associated with lower decreases in PLEs over time in females (p-FDR=0.005), with no effects on internalising symptom trajectories in either sex. Genetic influences were sex-specific, with higher PRS-SCZ and PRS-MDD linked to greater increases in internalising symptoms in females (p-FDR=0.009; p-FDR=0.022) and higher PRS-MDD associated with greater decreases in PLEs in males (p-FDR=0.001). In females we also observed an interaction between PM2. and PRS-MDD on PLEs trajectories (p-FDR=0.048) such that those with high genetic risk and high PM2.5 exposure demonstrated increases in PLEs over time. Our results suggest that PM2. exposure and polygenic risk for depression jointly shape mental health during adolescence. This underscores the potential of interventions aimed at lowering air pollution during sensitive periods of neurodevelopment in improving adolescent mental health.

Study Objectives Co morbid insomnia and sleep apnea (COMISA) is challenging clinically and difficult to treat. Our goal was to assess how much COMISA is the mere addition of two phenotypes or display features indicative of genuine statistical interactions. Methods A total of 152,487 patients from 240 sleep centers across 30 US states were included. Insomnia was defined as difficulty initiating/maintaining sleep with daytime fatigue/sleepiness occurring "often"/"always". OSA was defined as having an Apnea Hypopnea Index (AHI) more than 15 events/h. Modified Poisson regression was conducted to evaluate multiplicative interactions between insomnia and OSA on common comorbidities and sleep symptoms. Additive interactions were also examined. Linear regression models were used to evaluate additive interactions for PSG parameters. The false discovery rate was controlled using the Benjamini Hochberg procedure. Results After adjustment for confounders, insomnia and OSA demonstrated positive interactions for depression, chronic muscular pain, headache, subjective excessive daytime sleepiness (EDS), naps, and pre-sleep anxious and muscular tension (adjusted p < 0.05). Furthermore, insomnia and OSA demonstrated positive interactions for parameters related to respiratory disturbance, including AHI, oxygen desaturation index (ODI), respiratory disturbance index (RDI), total arousal index (AI) and respiratory AI, and negative interactions for minimum oxygen saturation and percentage of rapid eye movement stage (REM%) (adjusted p < 0.05). Furthermore, the adverse effects of insomnia and OSA on AHI, ODI, RDI and REM% were substantially amplified in males. Conclusions Our findings demonstrate that insomnia and OSA do not merely coexist but genuinely interact synergistically to amplify selected adverse clinical outcomes.

Background Brain abnormalities related to childhood adversity (CA) have been reported across clinical presentations in psychotic disorder (PD) and bipolar disorder (BD). This systematic review and meta-analysis examined gray matter volume (GMV) alterations linked to CA in PD and BD. Methods A PRISMA-compliant systematic review was conducted (PROSPERO ID: CRD42022351133). The EMBASE, MEDLINE, and PsycINFO databases were searched from inception to June 2024 for studies investigating CA and structural brain imaging in PD and BD. Study quality was assessed with the Newcastle Ottawa Scale (NOS). Data were extracted and synthesized accounting for sex differences and CA subtypes with brain findings categorized by the presence and direction of associations. Meta-analyses were performed for hippocampal and amygdala volumes. Results In the systematic review (k = 29), 3,056 participants with PD and BD (mean age = 36.6; SD =16.1; 47% female), published between 2011 and 2023, were included. Study quality was fair, with high heterogeneity. Most studies reported significant negative associations between CA and GMV, especially in prefrontal regions, while findings for the hippocampus and amygdala were largely null or inconsistent. Meta-analyses of a study subset identified no significant association between CA and hemisphere-specific and combined volumes of the hippocampus (k = 5; p [&ge;] 8805; 0.66) or amygdala (k = 4; p [&ge;] 8805; 0.87). Conclusion CA was not consistently associated with hippocampal or amygdala volume alterations in PD and BD. More consistent evidence emerged for reduced GMV in prefrontal regions, suggesting that neurobiological impact of CA may be more robustly captured at the cortical level.

Objective Psychosis spectrum symptoms (PSS) are common among children and youth. These symptoms may be clinically significant as studies indicate a heightened risk of mental health disorders, in general, as well as psychotic disorders, specifically, in youth that endorse PSS. This systematic review and meta-analysis investigates the longitudinal association between PSS in children and youth and subsequent mental health diagnosis. Methods A comprehensive search of Ovid Medline, PsycINFO, and EMBASE databases was conducted to identify longitudinal studies that: (i) assess PSS at a baseline timepoint, (ii) in individuals under 25 years, and (iii) assess mental health disorder diagnosis using a structured assessment at a later time point in the same sample. We conducted a meta-analysis and calculated pooled odds ratios (ORs) for mental health and psychotic disorders using random-effects models. Post-hoc meta-regressions were performed to examine the influence of a number of moderators on the relationship between earlier recorded PSS and subsequent mental health disorders or psychotic disorders. Results The search yielded 41 eligible studies of which 25 were included in the meta-analysis. Most included studies assessed PSS using brief self-report measures and recruited their samples from clinical or community settings. Among children and youth without an identified mental health diagnosis at baseline assessment, baseline PSS were associated with a 2-fold (OR = 2.07, CI = 1.61 - 2.66, I2 = 86.92%, p < 0.0001) increased risk of meeting diagnostic criteria for subsequent mental health disorder diagnosis and a 3-fold increased risk (OR = 3.11, CI = 2.11 - 4.58, (I2 = 60.93%, p < 0.0090) of meeting diagnostic criteria for a subsequent psychotic disorder diagnosis with a minimum 1 year follow-up time from baseline assessment. Meta-regression analysis indicated that study quality and sample size explained a substantial proportion of between-study heterogeneity for psychotic disorder outcomes. Conclusions Our results suggest that administration of simple self-report measures of PSS in both clinical and community settings may be helpful to identify children and youth at higher risk of subsequently meeting criteria for a mental disorder generally, and for a severe mental illness (i.e., psychotic disorder), specifically. Future longitudinal studies should focus on improving study design characteristics to increase confidence in identified longitudinal associations. The results of our work suggests that integration of self-report measures of PSS may be useful in a variety of settings to identify youth at increased risk of subsequent mental illness.

Purpose: Suicide mortality is underestimated due to misclassification under undetermined and accidental deaths. This study examined national trends in suicide and related external causes of death in Portugal from 2002 to 2023, by sex and age group, assessing potential shifts suggesting masked suicide and quantifying the relationship between undetermined, suicide, and accident death rates through ratio indices. Methods: Using official mortality data from Portugal's Statistics Institute (INE) for 2002-2023, we calculated age-standardised (SDR) and age-specific death rates (ASDR) for suicide (X60-X84), undetermined intent deaths (Y10-Y34), and unintentional deaths (V01-X59), disaggregated by sex and four age groups (15-24, 25-44, 45-64, 65+). We estimated undetermined-to-suicide (UnD:Suic) and undetermined-to-accidents (UnD:Accs) rate ratios for SDRs and ASDRs. Trends were analysed using joinpoint regression (APC/AAPC) and structural breakpoint analysis (Chow test, BIC). Results: Suicide SDRs declined across the period for males (AAPC: -2.25%) and females (AAPC: -1.32%), with the sharpest reductions among males aged 25-44 (AAPC: -2.56%) and females aged 65+ (AAPC: -2.44%). Deaths of undetermined intent rose steeply from 2002 to 2005-2006 and declined thereafter. Unintentional deaths declined in most age groups, except females aged 65+ (AAPC: +1.41%). Both ratio series peaked around 2005-2009, declined progressively through the 2010s, and reached their lowest values in 2021-2022. Age-specific analyses revealed a significant and sustained increase in both ratios among females aged 45-64. Structural breakpoints clustered around 2004, 2013-2015, and 2019-2020. Conclusion: Suicide mortality declined in Portugal from 2002 to 2023, but divergent trends in undetermined and accidental deaths across sex and age subgroups highlight ongoing misclassification. Age- and sex-specific ratio analyses identify the population subgroups where misclassification is most concentrated, providing a foundation for future imputation-based estimates of probable suicide burden.

Importance: Patients who achieve remission from major depressive disorder (MDD) often face a preference-sensitive decision between continued antidepressant maintenance and discontinuation with active monitoring. Quantifying the tradeoff between depression burden and long-term medication exposure may support more individualized shared decision-making. Objective: To quantify tradeoffs between continuous antidepressant maintenance and active monitoring after MDD remission, and to identify preference thresholds favoring each strategy across relapse-risk strata. Design: Individual-level decision-analytic health-state transition model calibrated to randomized maintenance-discontinuation trials and a longitudinal first depressive episode cohort, with a 5-year time horizon. Setting: Outpatient clinical decision after completion of an 8-month continuation phase following remission from MDD. Participants: Adults in remission from MDD, represented across 4 clinically anchored relapse-risk strata ranging from very low risk after a first mild episode to high risk after highly recurrent depression. Exposures: Continuous antidepressant maintenance vs discontinuation with active monitoring and antidepressant restart after detected relapse. Main Outcomes and Measures: Severity-weighted depression-months, antidepressant medication-years, medication-years per depression-month averted, and net benefit across preference thresholds defined as the maximum additional medication-years a patient would be willing to accept to avert 1 depression-month. Results: Continuous maintenance reduced depression burden but required substantially more medication exposure, with efficiency strongly dependent on relapse risk. Medication-years per depression-month averted ranged from 11.8 (95% uncertainty interval [UI], 7.8-19.6) in the very low-risk group to 1.5 (95% UI, 0.8-3.0) in the high-risk group. At a preference threshold of 3 medication-years per depression-month averted, maintenance was preferred for moderate- and high-risk patients; at a threshold of 2, only for high-risk patients; and at a threshold of 1, for no risk group. Conclusions and Relevance: In this decision-analytic model, the value of continuous antidepressant maintenance depended strongly on baseline relapse risk and patient preferences regarding long-term medication exposure. These findings provide a quantitative framework for shared decision-making about antidepressant maintenance after remission from MDD.

Objective: Working memory (WM) deficits are a co-occurring feature to numerous neuropsychiatric disorders, particularly attention-deficit/hyperactivity disorder (ADHD), and there remain no treatments that directly target WM. The coupling between the phase of theta band activity and amplitude of gamma band activity (i.e., TGC) is an established neural correlate of WM. However, no studies have examined WM-related TGC in ADHD or whether neuromodulation can modulate these oscillatory dynamics in youth. This set of studies examined the effects of intermittent theta burst stimulation (iTBS) to the left dorsolateral prefrontal cortex (DLPFC) and left posterior parietal cortex (PPC) on TGC in youth with ADHD. Methods: In two randomized, double-blind, sham-controlled crossover trials, adolescents with ADHD and clinically significant parent-reported WM symptoms first completed a single-session study comparing DLPFC versus PPC iTBS targeting (n = 47) and then a multi-session clinical trial comparing 10 sessions of active versus sham left DLPFC iTBS (n = 29). Participants completed a computerized visuospatial Sternberg WM task with concurrent electroencephalography (EEG) before and after the single sessions, as well as at baseline, midway through treatment, and approximately 24 hours after the final session within the multi-session trial. Phase-amplitude coupling between theta phase and gamma amplitude was quantified using the Kullback Leibler modulation index at frontoparietal electrodes. Linear mixed-effects models examined treatment effects and associations between change in TGC and WM status (including accuracy, reaction time, and clinical symptoms). Results: Across participants, lower TGC was associated with lower symptoms and better WM performance, including higher accuracy, faster and more consistent RT. Active iTBS increased frontoparietal TGC relative to sham stimulation, with effects observed both acutely after a single session and ~24 hours after multiple sessions. DLPFC-targeted iTBS increased TGC, whereas PPC-iTBS had no measurable effect. Change in TGC was associated with change in WM, such that a decrease in TGC was associated with faster RT and decreased RT variability. Higher baseline TGC was associated with greater improvement in WM. Active iTBS decoupled the TGC-WM association observed during sham iTBS, and greater electric field intensity of iTBS was associated with greater improvement in WM accuracy and greater decrease in TGC. Conclusions: Active iTBS to the left DLPFC modulated WM-related TGC in youth with ADHD. These findings provide preliminary evidence that neuromodulation may improve WW by modifying oscillatory dynamics within frontoparietal networks. Larger clinical trials with higher stimulation doses are needed to determine whether targeting oscillatory coupling represents a potential therapeutic strategy for WM deficits.

Executive function (EF) deficits are central features of schizophrenia and strongly influence long-term functional outcomes. Conventional cognitive assessments often lack ecological validity and cultural relevance. This study introduces the Luk Chup Augmented Reality (LCAR) tool a video guided, clay modeling task delivered through wearable AR that integrates culturally familiar activity with realtime neurophysiological monitoring. Thirty individuals diagnosed with schizophrenia (mean age = 38.9, SD. = 7.15 years) completed a series of modeling and memory tasks using LCAR while undergoing quantitative EEG (QEEG). Task duration and theta/beta power were analyzed across procedural and color shape memory phases. Memory phases took significantly longer to complete and were associated with decreased lateral prefrontal theta and increased frontal midline theta activity (Fz, Cz), indicating higher EF demand. A repeated-measures ANOVA revealed significant condition, site, and interaction effects on theta power. The LCAR tool shows promise as a culturally grounded, dual-mode assessment of EF in schizophrenia. It offers a novel integration of performance-based and neurophysiological metrics that may inform future interventions in psychiatric rehabilitation.

Background: Childhood adversity (CA) has been identified as one of the most robust risk factors for psychotic disorders; several treatable mediating mechanisms have been proposed. Aims: To conduct a systematic review and meta-analysis examining mediating pathways linking CA and psychosis. Method: This PRISMA-compliant systematic review (PROSPERO: CRD42024542972). consisted of a search conducted in January 2026 on Ovid (PsycINFO, Medline, and Embase) using search terms related to psychosis, CA, and mediation analyses. Evidence was appraised by calculating the percentage of the total effect mediated in each study, grouping mediators into meaningful groups. When possible, meta-analyses using two-stage meta-analytic structural equation modelling (METASEM) were conducted. Results: 117 studies were included (54 in clinical samples, 59 in non-clinical samples, and four studies in both clinical and non-clinical samples). 107 studies examined psychological mediators and 12 examined biological. The median percentages of total effect mediated across all analyses per mediator family were: 49% for dissociation (k = 24), 45% for psychosocial stressors (k = 6), 37.9% for negative schemas (k = 23), 35.2% for post-traumatic symptoms (k = 10), 31.5% for depressive symptoms (k = 14), 27.8% for anxiety (k = 11), 27.1% for attachment styles (k = 12), and 8.7% for mentalization domains (k = 5). Meta-analyses confirmed a robust mediating effect of dissociation (k = 7; N = 2143; indirect effect (I.E) =0.42 [0.17, 0.66] on psychosis; 50.49%), on delusions (k =7; N = 1053; I.E = 0.36, [0.27, 0.46]; 46.44%]) and on hallucinations (k =10; N = 5705; I.E = 0.28 [0.20, 0.36]; 57.59%). Robust mediation via depression (k =5; N= 5028; indirect effect= 0.33 [0.31, 0.35]; 31.05%) and negative schemas of the association between trauma and psychosis broadly defined (k = 7; N=10791; I.E= 0.26 [0.17, 0.35]; 26.36%) was also observed. High heterogeneity was observed across all meta-analyses. Fewer studies examined biological mediators, preventing quantitative synthesis. Conclusions: Childhood adversity impacts psychosis through psychosocial mediators, particularly dissociation. Further work is required to on the potential role of biological mechanisms and its interplay with psychological mechanisms.

Background: Depression is clinically heterogeneous, and immune-metabolic disturbances may not map uniformly onto categorical diagnosis or symptom severity. In populations exposed to substantial structural adversity, it remains unclear whether inflammatory and metabolic biomarker differences reflect adversity exposure itself or cluster around specific depressive phenotypes. Methods: Data were drawn from the Sao Paulo Megacity Mental Health Survey, a population-based study in which 5,037 household residents underwent structured psychiatric interviews. Among 770 participants assessed as having clinically significant symptoms (SCID-I), individuals with chronic physical illnesses, hs-CRP >20 mg/L, or missing data were excluded, yielding an analytic sample of 653. Latent class analysis of 16 DSM-IV depressive symptoms was used to identify symptom-derived phenotypes. Multinomial logistic regression tested associations between latent classes and immune-metabolic biomarkers, including hs-CRP, lipid fractions, fasting glucose, and triglycerides, adjusting for age, sex, education, smoking, and BMI. Results: A four-class solution identified asymptomatic (44.56%), mild-moderate (19.14%), atypical-like (16.69%), and melancholic-like (19.60%) classes. The two highseverity classes diverged by neurovegetative features: atypical-like depression was characterised by weight gain, hypersomnia, and psychomotor retardation, whereas melancholic-like depression was characterised by weight loss, insomnia, and psychomotor agitation. hs-CRP was highest in the atypical-like class and lowest in the melancholic-like class despite similar symptom severity. After BMI adjustment, elevated hs-CRP in the atypical-like class attenuated, whereas lower hs-CRP in the melancholic-like class persisted. Other metabolic markers did not robustly differentiate classes after adjustment. Conclusions: Immune-metabolic differences in depression do not simply follow symptom severity. In this Sao Paulo cohort, higher and lower hs-CRP profiles clustered around distinct latent depressive phenotypes, supporting biologically heterogeneous depressive presentations within a socially exposed urban population.

Background: Emotion dysregulation is a core feature of bipolar disorder (BD), yet its behavioral expression during depressive episodes, and potential differences between its types, BD-I and BD-II, remain unclear. This study used automated facial-expression analysis during naturalistic affective film viewing to examine subtype-specific and context-dependent emotional responding in bipolar depression. Methods: The sample included 135 participants: 69 healthy controls and 66 patients with BD (BD-I, 23; BD-II, 43). Participants viewed nine emotionally evocative film clips spanning negative, positive, neutral, and socially threatening contexts, while their facial expressions were continuously recorded and quantified using computer vision-based facial-expression analysis. Results: Patients with BD-I showed a distinct, context-dependent facial-expression profile, characterized by greater negative responses across multiple contexts than other groups. Specifically, they showed increased sadness during sad, reward, and amusing clips, and elevated anger during sad and neutral clips. In socially threatening contexts, BD-I participants showed a multivalent pattern of elevated anger, fear, and joy, suggesting poorly coordinated or context-incongruent affective expression. In contrast, BD-II participants did not differ significantly from healthy controls on any emotion, despite depressive symptom severity comparable to BD-I participants. Conclusions: These findings suggest that facial-expression patterns in bipolar depression differ across subtypes. BD-I may be characterized by heightened negative reactivity and altered context-appropriate modulation of emotional expression, whereas BD-II may not show comparable alterations in overt facial output. Automated facial-expression analysis during naturalistic stimulation may provide a useful behavioral marker for characterizing subtype-specific affective disturbance in bipolar depression and related psychopathology.

Cognitive flexibility is an executive function that allows individuals to adjust behaviour in response to changing environmental demands. We assessed volitional switching under uncertainty, without rule-based learning, in the Change Your Mind task. Nineteen patients with obsessive-compulsive disorder (OCD), 19 patients with attention-deficit hyperactivity disorder (ADHD) and matched control participants (20 per group) completed the task whilst undergoing a functional MRI scan. The task was a two-alternative forced choice paradigm where each stimulus was presented twice successively, with spurious feedback following the first presentation. This allowed participants the opportunity to repeat or change their response. Participants with ADHD changed their response more frequently than controls following a previously correct response, associated with reduced accuracy on the second trial. This was accompanied with smaller differences between change and repeat trials in the superior frontal gyrus, paracingulate gyrus and frontal pole compared to controls. Participants with OCD did not differ from healthy controls in their performance but exhibited greater activity on both change and repeat trials in the pre- and postcentral gyri than controls. These results point to distinct neurobehavioural differences in patients with ADHD and OCD underlying what is often termed more broadly inflexible behaviour.

Cortisol, our stress hormone, exerts widespread influence on neural activity. However, its influence on the aperiodic component of the electroencephalography power spectrum remains to be investigated. Given individual differences in the capacity to cope with stress and adversity, it also remains unclear whether trait resilience moderates this relationship. Hence, the present study examined whether individual differences in trait resilience moderates the association between resting cortisol and aperiodic activity. Participants (N=145) completed various self-report questionnaires (e.g., trait resilience). Electroencephalography was recorded over a 20-minute baseline period, followed by salivary cortisol collection. The results revealed a significant moderating effect of trait resilience in the occipital scalp region. Specifically, higher cortisol concentration was associated with flatter 1/f slopes amongst individuals with low trait resilience, whereas this association was reversed amongst those with high trait resilience. Overall, our findings highlight the role of individual differences in trait resilience in shaping hypothalamic-pituitary-adrenal axis-related neural dynamics.

Abstract Background: Medical students carry a disproportionate burden of mental health problems, but large multicentre studies from low- and middle-income countries remain scarce, and most evidence relies on single-institution samples and odds-ratio-based analyses that overstate associations for common outcomes. We provide a comprehensive epidemiological overview of mental health among medical students across an entire Brazilian state, quantifying the burden, its co-occurrence, and its socioeconomic and academic determinants. Methods: Cross-sectional online survey of 1,560 medical students covering all 20 medical schools in operation in Rio Grande do Sul, Brazil (August-December 2023). Validated instruments assessed depressive and anxiety symptoms (PHQ-4), suicidal ideation (PHQ-9 item 9), non-suicidal self-injury, burnout (ESB-eu), quality of life (EUROHIS-QOL-8), spirituality (SSRS), substance use (ASSIST), prescription stimulant misuse, and mistreatment during training. Associations were estimated as adjusted prevalence ratios (aPR) using modified Poisson regression with robust variance, with linear trend tests, prespecified interactions, sensitivity analyses and E-values. Results: Anxiety symptoms affected 64.5% (95% CI 62.1-66.9), depressive symptoms 45.5% (43.1-48.0), burnout 49.1% (46.7-51.6), recent suicidal ideation 20.6% (18.7-22.7), lifetime self-injury 13.1% (11.6- -4.9) and stimulant misuse 7.9%; 57.4% screened positive for >=2 outcomes. Quality of life declined monotonically with cumulative burden. Low family income showed inverse gradients across five outcomes (e.g., depression: PR 0.93 per income level, p = 0.002). Four factors were independently associated with nearly all outcomes: short sleep (<6 h; aPR up to 2.73), minority sexual orientation (aPR up to 2.02), family psychiatric history, and mistreatment during training (reported by 55.6%; aPR up to 1.49). Stimulant misuse tripled from the basic cycle to clerkship (aPR 2.30, 95% CI 1.36-3.88). There was no evidence of multiplicative interaction, indicating that the risk factors acted independently on the outcomes. Estimates were robust across sensitivity analyses. Conclusions: One in two medical students in this state-wide sample screened positive for at least two mental health problems. Socioeconomic vulnerability, sleep deprivation, mistreatment and minority status operate as independent and largely modifiable determinants - actionable targets for medical schools and policymakers.