Registry-based studies can inform suicide prevention by identifying mental disorders with the highest risk. Previous studies focused on severe disorders and suicide, with limited data on non-lethal self-harm or population impact. We quantified individual- and population-level associations of 32 mental disorders with non-lethal intentional self-harm (NLISH) and suicide.

Registry-based cohort study representative for all residents of Catalonia (Spain) aged ≥10 years (2014–2019; n = 645,571). Cause-specific Cox models estimated individual (hazard ratios [HRs]) and population-level (population attributable fractions [PAFs]) associations with NLISH and suicide, stratified by sex and adjusted for age, socioeconomic status, and nationality.

Individual-level associations with NLISH were strongest for borderline personality disorder (BPD; females HR = 26.9 [95%CI 24.9–29.0]; males HR = 18.9 [95%CI 16.7–21.4]). Associations with suicide were strongest for BPD in females (HR = 40.9 [95%CI 28.5–58.8]) and obsessive-compulsive disorder in males (HR = 17.4 [95%CI 5.3–56.5]). Associations with suicide were stronger among females, and those aged 10–44 across mood, substance use, dissociative, borderline personality, and psychotic disorders. Substantial proportions of outcomes were associated with common disorders: depressive episodes (PAFs 29.8–49.8%), substance use disorders (PAFs 25.1–48.7%), mixed anxiety-depressive disorders (PAFs 19.7–53.2%), and adjustment disorders (PAFs 10.6–44.6%).

Depressive, anxiety, adjustment, and substance use disorders are associated with large shares of self-harm and suicide, whereas BPD confers particularly high individual risk. Our findings support multilevel prevention strategies, especially among young people, including improved risk assessment, collaborative care, and timely access to specialized interventions.

Bipolar disorder is a recurrent and disabling condition, with a critical clinical need to prevent transitions from euthymia or depression (normal or low activation states) to mania (a high activation state). This study investigates how disruptions in sleep–wake and circadian rhythms may trigger these high activation states, to inform more effective relapse prevention strategies.

We developed a computational agent-based model integrating empirical evidence, clinical expertise, and lived experience to simulate how 24-hour sleep–wake behaviors (SWBs) influence manic episodes. Individual characteristics were drawn from the Brain and Mind Youth Cohort (N = 2,330), and multiple scenarios were simulated to assess how SWB dynamics affect the emergence and course of mania.

In the absence of all irregularities, no individuals experienced a manic episode. Removing behavioral feedback loops resulted in a substantial reduction in manic episodes and delayed onset. In contrast, eliminating light–dark entrainment slightly increased the frequency of manic episodes, suggesting that seasonal adaptation plays a stabilizing role. When examining components of SWB separately, removing sleep irregularities alone had only a modest effect on mania rates, whereas reducing activity irregularities led to the largest benefit: a significant drop in mean manic episodes, a delay in onset, and preventing mania in 65% of the simulated agent population.

Our findings highlight the value of computational modeling for uncovering causal dynamics in mental health. These specific findings demonstrate how daily irregularities in sleep–wake behavior may be a necessary condition for mania. Targeting behavioral regularity may offer a powerful pathway for prevention and early intervention.

Alexithymia is a multifaceted, transdiagnostic trait characterized by challenges in emotion processing. Affecting up to 10% in the general population, it represents a risk factor for various mental and physical health conditions. Recent neuroimaging studies have elucidated the neural substrates of alexithymia, providing initial insight into altered functional connectivity within key emotional, attentional, and interoceptive networks, potentially impairing emotion processing and everyday functioning. However, no large-scale study has yet confirmed these network alterations.

Resting-state functional magnetic resonance imaging from 575 individuals (ages 29–60, 334 women) in the population-based SHIP-TREND cohort, using regions of interest covering major functional networks across the whole brain, was paired with the 20-item Toronto Alexithymia Scale (TAS-20) to investigate the signature of alexithymia. The analysis accounted for technical variables, sociodemographic factors, lifestyle, and current depressive symptoms.

Higher TAS-20 scores were associated with altered functional connectivity within the frontoparietal network and between the dorsal attention and salience networks. Specifically, the subscale “difficulties identifying feelings” was associated with functional alterations between and within attentional, salience, and sensorimotor networks, indicating a divergent pattern within the salience network.

These findings underscore the widespread impact of alexithymia on brain networks involved in emotional attention, interoception, and somatosensory processing. Controlling for lifestyle factors, current depressive symptoms, and other health indicators supports the specificity of these patterns. This supports the view of alexithymia as a personality trait that affects large-scale network functioning, potentially hampering emotional regulation and self-awareness processes, contributing to mental and physical health risks.

This systematic review evaluates specialized psychosocial and complex interventions for early bipolar disorder (BD), early borderline personality disorder (BPD), early depression, early psychosis, and first-episode mental illness in general (FEMI).

We included systematic reviews and randomized controlled trials (RCTs) of interventions with psychosocial components, excluding trials that focused on pharmacological-only interventions and stand-alone psychotherapies. Searches were conducted in January 2023 across five databases. Review quality was assessed using AMSTAR-2 and risk of bias for RCTs using the Cochrane tool.

Ten studies met the inclusion criteria: seven reviews and three RCTs. High-to moderate-quality evidence supports complex psychosocial interventions combined with pharmacotherapy for early psychosis. The most robust effects were reductions in relapse and improvements in psychosocial functioning; additional benefits were observed for symptom burden, remission, treatment discontinuation, and hospital admissions. Benefits were most sustained in longer-duration, community-based programs. For early BD, limited evidence suggests that combining pharmacotherapy with family-focused therapy or structured psychoeducation may improve the course of illness and treatment satisfaction. One RCT in early BPD reported improved engagement with a developmentally tailored program. Two FEMI RCTs found that nurse-led psychoeducation and psychosocial programs improved in-patient duration, symptoms, insight, self-efficacy, quality of life, and engagement. No eligible studies addressed early-stage depression, indicating a notable evidence gap for multimodal psychosocial interventions.

Complex psychosocial interventions are strongly supported for early psychosis. Preliminary data in BD, BPD, and FEMI suggest consistent benefits for engagement, but further rigorous trials – especially in early depression – focusing on different outcomes – are required.

People with psychotic disorders have high cardiometabolic risk, yet prediction tools are rarely validated outside early-intervention settings. We externally validated and recalibrated the UK Psychosis Metabolic Risk Calculator (PsyMetRiC) in a Dutch cohort of young adults with psychotic disorders in long-term care.

We used data from the PHAMOUS registry. Individuals aged 16–35 years, without metabolic syndrome (MetS) at baseline (prevalence 21.2%), were included. MetS incidence over approximately 6 years (last assessment 1–6 years; cumulative incidence 29.1%) was defined using international criteria. Full (biochemical + clinical) and partial (clinical only) PsyMetRiC models were applied to 10 multiply imputed datasets. Discrimination, calibration, and decision-curve analysis (DCA) were assessed before and after logistic recalibration of intercept and slope.

In external validation, C-statistics were about 0.69 for the full and 0.67 for the partial model. Both systematically underpredicted MetS risk; recalibration yielded calibration intercepts near 0 and slopes near 1, while discrimination was unchanged. DCA suggested that, across risk thresholds of 0.10–0.35, using recalibrated PsyMetRiC could provide higher net benefit than “treat all” or “treat none.”

In this chronic-care cohort, PsyMetRiC showed moderate discrimination and improved calibration after logistic recalibration. The recalibrated models may support more targeted metabolic monitoring and prevention, but interpretation is limited by registry design, variable follow-up times, reliance on multiple imputation, and modest power for subgroup analyses.

Social cognitive impairments are a fundamental aspect of schizophrenia, exerting a substantial influence on patients’ functional outcomes. However, to date, there have been no meta-analyses of comprehensive pharmacological interventions covering all domains of social cognition. The aim of the present study was to address this knowledge gap by conducting a network meta-analysis, a comprehensive approach that systematically compares the efficacy of pharmacological interventions across all domains of social cognition.

A literature search for randomized controlled trials (RCTs) was conducted using PubMed, Embase, the Cochrane Central Register of Controlled Trials, PsycINFO, ClinicalTrials.gov, and the International Clinical Trials Registry Platform. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines were followed.

A total of 8,752 records were screened, and 60 RCTs involving 4,270 subjects were included in the systematic review. Thirty-six pharmacological interventions were extracted, but no compounds had a significant ameliorative effect on social cognition in comparison with placebo. In each domain of social cognition, the following compounds were identified as the most probable candidates for treatment selection: selective glycine uptake inhibitor (standardized mean difference [SMD], 0.46; 95% credible interval [CI], −0.52 to 1.44) and stimulant (SMD, 0.44; 95% CI, −0.57 to 1.45) for emotion perception in comparison with placebo. In the context of emotion processing, γ-aminobutyric acid (A) α2/α3 partial agonist (SMD, 0.33; 95% CI, −0.53 to 1.19) emerged as the top compound.

To date, no pharmacological interventions have demonstrated efficacy for social cognitive impairments in schizophrenia.

The network theory of mental disorders posits that associations between symptoms activate other symptoms to maintain a disorder over time. Network analytic approaches therefore may inform treatment targets. In the present study, we compared baseline OCD symptom networks among treatment responders to non-responders and examined how network structure and connectivity changed from before to after exposure and response prevention (ERP) treatment.

Community adults with OCD (n = 712) who underwent intensive outpatient treatment were assessed using the Yale-Brown Obsessive Compulsive Scale (YBOCS) at admission and discharge. Network comparison tests were used to (a) examine differences in baseline symptom network structures between treatment responders versus non-responders and (b) examine changes in network structures from pre- to post-treatment.

Pre-treatment network structures and global connectivity did not differ significantly between treatment responders and non-responders. However, post-treatment networks exhibited greater global strength (i.e., stronger associations between OCD symptoms) and significantly different network structure (i.e., different patterns of associations between OCD symptoms) relative to the pre-treatment network.

Findings showed that network structure and connectivity in OCD may be more informative as a marker of therapeutic change than in discriminating treatment responders from nonresponders using baseline symptoms. After ERP treatment, associations between obsessions and compulsions demonstrated significantly greater global network strength and altered network structure, thus underscoring the potential for network approaches to identify mechanisms of change throughout OCD treatment. Future studies incorporating session-by-session data may clarify when and how these network shifts occur over the course of therapy to help identify treatment targets.

The vulnerability–stress framework guiding gene–environment interaction (GxE) research overlooks the role of positive experiences. The Differential Susceptibility (DS) model offers a broader perspective, suggesting that individuals vary in sensitivity to both negative and positive environments. This study aimed at replicating previous DS research by examining interactions between polygenic scores for environmental sensitivity (PGS-ES) and positive and negative early exposures on subclinical psychosis and internalizing psychopathology, functioning, and wellbeing.

The sample consisted of 638 twins from the first wave of the TwinssCan study, a general population twin cohort. PGS-ES and adversity, bullying and positive experiences in childhood were collected, along with assessments of psychotic, affective, functioning, and positive mental health. GxE interactions were tested under a competitive–confirmatory approach.

DS effects were found for the interactions between PGS-ES and all environmental exposures on schizotypic eccentricity and functioning. Adolescents with high genetic sensitivity were rated as more eccentric and less functional under childhood adversity but were rated as less eccentric and better adjusted under childhood favorable conditions. DS also resulted from the interaction between PGS-ES and positive childhood on social coping. No significant models emerged for internalizing or wellbeing.

Findings overall supported DS, indicating that genetic sensitivity to the environment operates in a “for better and for worse” manner depending on the quality of environmental exposures. It extends initial evidence that DS applies to nonclinical psychosis expression and highlights the importance of considering the full spectrum of environmental conditions to understand both risk and opportunity factors in GxE.

Sex differences in psychosis pathoetiology are insufficiently understood. This study explores how childhood adversity (CA) and coping mechanisms relate to psychosis expression (PE) across males and females in the general population.

Data from the TwinssCan project (males: n = 312; females: n = 478) were used. The Childhood Trauma Questionnaire assessed CA domains. The Utrecht Coping List assessed coping strategies. Psychosis expression was assessed using the Community Assessment of Psychic Experiences (CAPE). Mixed linear regression analyses examined sex-stratified associations of CAPE scores with CA, coping strategies, and their interactions.

Emotional abuse (EA) was associated with increased total CAPE scores (T-CAPE), explaining the greatest variance among CA across sexes. Sex-specific effects showed that sexual abuse (SA) and physical abuse (PA) were linked to higher T-CAPE in females, whereas physical neglect (PN) was linked to higher T-CAPE in males. Passive-reacting was associated with increased T-CAPE, explaining the greatest variance among coping styles across both sexes. Sex-specific effects showed that, in females, seeking social support was linked to decreased T-CAPE, while emotional expression increased it. The only sex-shared interaction effect was between reassuring thoughts and emotional neglect (EN), associated with decreased T-CAPE. In females, social support (× PA/PN/EA), reassuring thoughts (× PA/PN), and palliative-reacting (× PN/PA) were associated with decreased T-CAPE, while passive-reacting (× EN) increased it. In males, avoidance (× SA/PA) and passive-reacting (× PN) were associated with increased T-CAPE.

Sex differences in the associations of PE with CA and coping underscore the necessity for sex-specific interventions that promote adaptive coping strategies.

Attention deficit hyperactivity disorder (ADHD) affects 5–7.2% of children and 2.5% of adults. Despite its prevalence, ADHD remains underdiagnosed and undertreated, leading to significant challenges for affected individuals. Early diagnosis and intervention can prevent adverse outcomes and improve quality of life.

We developed a predictive model to identify adults with ADHD using electronic health records. The dataset comprised 2,973 adult patients (aged 18 years and above) diagnosed with ADHD and a control group of 4,447 adults referred to psychologists with no ADHD diagnosis. A transformer-based architecture was implemented, utilizing only clinical codes and gender as input features. Fivefold cross-validation was adopted, and model performance was evaluated on held-out test data consisting of 800 patients, 400 of whom had an ADHD diagnosis.

Our study demonstrated the ability to predict adult ADHD using clinical data, with a 6-month model achieving an area under the receiver operating characteristic curve (AUC) of 0.79 (95% confidence interval: 0.76–0.81), F1-score of 0.79, sensitivity of 0.80, and specificity of 0.77. Shapley Additive Explanations identified key contributing codes, including F158 and Y903, consistent with known associations between ADHD and substance use.

Our findings show that machine learning can effectively use clinical codes and demographic data from routine EHRs to support early, cost-efficient diagnosis of adult ADHD, paving the way for earlier intervention and improved outcomes.

The early phases of severe mental disorders are often diagnostically challenging, with frequent diagnostic shifts over time. Few studies have combined detailed baseline diagnostic assessment with long-term follow-up to examine both diagnostic and social development.

We conducted a 20-year register-based follow-up of 150 patients with first-time psychiatric hospitalizations. At baseline, all participants underwent a comprehensive diagnostic assessment. Follow-up data were obtained through linkage to national registers, providing information on psychiatric diagnoses, education, family formation, crime, mortality, and suicide. Cumulative incidence functions accounting for competing risks were calculated stratified on baseline diagnoses.

Only seven participants (4.6%) had no further contact with hospital-based psychiatry during the 20-year follow-up. During the follow-up period, 37.9% received a diagnosis of schizophrenia, 35% schizotypy, 14.4% depression, 24.6% personality disorder, 11% bipolar disorder, and 6.1% substance use disorder. Participants with a baseline diagnosis of schizophrenia, schizotypy, or depression had a significantly higher probability of receiving the same diagnosis during follow-up (schizophrenia 81.6%, schizotypy 69.4%, and depression 53.3%), whereas this was not the case for participants with a baseline diagnosis of personality disorder. Mortality was elevated (5.9%), with suicide accounting for one-third of all deaths, ten times the national average.

A first psychiatric hospitalization in early adulthood marked the beginning of a longer clinical trajectory: 95% of participants re-entered hospital-based care or had prolonged initial hospitalization. The findings emphasize the importance of diagnostic assessment and sustained care to improve prognosis and reduce social impairment and premature death.

Network analysis was employed to test whether the overall pattern of depressive–anxious symptom connections remains stable or whether specific symptom-to-symptom links shift from pregnancy to postpartum.

In a perinatal sample (n = 4,461 pregnant women, n = 5,711 postpartum women), depressive and anxiety symptoms were assessed with the Edinburgh Postnatal Depression Scale (EPDS) and Generalized Anxiety Disorder-7 (GAD-7). Phase-specific polychoric Gaussian graphical models were estimated with EBICglass. We examined strength and bridge centrality, community structure, and nodewise predictability, and compared networks using the network comparison test.

Depression and anxiety formed four reproducible communities (one GAD-7 worry/arousal and three EPDS affective/anhedonic, anxious–cognitive distress, and depressed affect/sleep–suicidality modules) with identical partitions across phases. Global strength was similar, but postpartum networks showed higher edge density and more negative partial correlations, suggesting localized changes in which symptom pairs were directly linked—and how strongly—across phases. Across phases, Sadness, Crying, Uncontrollable worrying, and Trouble relaxing were most central and predictable. Worry-, arousal-, and sleep-related symptoms (e.g., hard to sleep) showed the strongest bridge centrality postpartum, and Self-harm was a prominent bridge during pregnancy; several edges shifted between phases, including stronger Enjoyment–Self-harm and weaker Hard to sleep–Self-harm postpartum.

Perinatal depression and anxiety organize into cohesive yet partially distinct symptom networks that remain globally stable but show localized shifts in direct symptom-to-symptom connections from pregnancy to postpartum. Central affective and arousal nodes, particularly sadness, pathological worry, and sleep disturbance, may be high-yield targets for phase-tailored screening and intervention.

The awareness of climate change as a global environmental threat through media consumption and/or social interaction can have a psychological impact on people’s mental health. However, little is known about the association between climate change awareness-related psychological distress (CCARPD) and mental health in people with psychiatric diagnoses or subclinical symptoms.

A comprehensive and systematic literature search of the PubMed, Embase, Web of Science Core Collection, Scopus, and CENTRAL electronic databases (from inception to February 2025) was conducted, without language restriction, for articles assessing the association between CCARPD and the mental well-being of people in the general and psychiatric populations.

Twenty-eight thousand forty-seven reports were retrieved. Of these, 67 met the inclusion criteria (64 general and 3 psychiatric population studies). The overall correlation between CCARPD and mental health measurements (ranging from subclinical symptoms to clinical diagnoses of depression, anxiety, or stress) was positive and of weak-to-moderate strength. Nevertheless, higher psychological distress due to the awareness of climate change was found in those having more severe mental health problems.

Although most studies have found small-to-moderate correlations between CCARPD and mental health measurements, it can be distressing and damaging for those with more severe mental health problems. As CCARPD will increase globally as the climate crisis unfolds in the coming decades while the understanding of the connections between CCARPD and mental well-being is still at an early stage of development, more research will be of utmost relevance, particularly in psychiatric populations.

Trazodone is commonly used in the treatment of major depressive disorder (MDD) in adults. This study aimed to establish consensus on the clinical scenarios and patient profiles for which trazodone treatment is considered suitable.

A two-round Delphi process was conducted across eight European countries. Statements regarding trazodone were rated by a panel of 32 experts for agreement or disagreement using a 9-point Likert scale; those with <70% agreement among panelists were revised and reassessed by the panel.

There was strong consensus agreement on 68 out of 91 statements (75%) related to trazodone. According to the panel, trazodone is well tolerated, with low anticholinergic activity, minimal impact on sexual function, weight neutrality, and low potential for clinically relevant drug–drug interactions. Consensus agreement supported trazodone use across a broad spectrum of patients with MDD, including those with insomnia, anxiety, psychomotor agitation, substance use, physical comorbidities, neurological conditions, and treatment-resistant depression; consensus agreement was also achieved for trazodone use in elderly patients, and those experiencing adverse effects with other antidepressants.

This study suggests that trazodone is useful in the treatment of MDD across multiple patient profiles. These findings offer practical guidance to support individualized and evidence-based decision-making in clinical practice.

The prevalence of mood, anxiety, and substance use disorders has risen in the last decade. It is unclear to what extent this rise is also seen in the first-incidence of these disorders, even though this is relevant for prevention. We provide up-to-date information on the first-incidence of common mental disorders (mood, anxiety, and substance use disorders) and compare this with the first-incidence 12 years ago.

First-incidence of DSM-5 common mental disorders was examined with a slightly modified version of the Composite International Diagnostic Interview (CIDI) 3.0 in 4,688 respondents (18–75 years; interviewed in 2019–2022 and 2023–2024) from the third Netherlands Mental Health Survey and Incidence Study (NEMESIS-3). The CIDI also assessed DSM-IV diagnoses and, therefore, 12-year changes could be examined by comparing first-incidence rates of DSM-IV mental disorders between NEMESIS-3 (3,687 respondents aged 18–64 years) and NEMESIS-2 (5,303 respondents aged 18–64 years; interviewed in 2007–2009 and 2010–2012).

In NEMESIS-3, 11.1% of adults without prior psychopathology experienced a DSM-5 common mental disorder over 3 years. First incidence was similar for any mood disorder (7.1%) and any anxiety disorder (6.9%), but lower for any substance use disorder (3.2%). From 2010-2012 to 2023-2024, the 3-year incidence of any DSM-IV disorder significantly increased from 8.5 to 14.0%. This change remained significant after controlling for differences in sociodemographic characteristics.

The substantial rise in first incidence of mental disorders likely contributes to the previously observed rise in their prevalence. This implicates a need for enhanced preventive measures and early intervention initiatives.

Parental alcohol supply in early childhood may increase the risk of alcohol use in late adolescence. This study examined its longitudinal impact and the distinct roles of mothers’ and fathers’ drinking.

We studied 1,891 mother–child pairs from the Czech European Longitudinal Study of Pregnancy and Childhood. Mothers reported parental alcohol supply at ages 3, 5, 7, and 11 years, while adolescent alcohol use was reported by mothers, pediatricians, and youth at ages 18 and 19 years. Structural equation modeling assessed the longitudinal link between early alcohol supply (three classes: none, occasional, and frequent) and adolescent alcohol use, accounting for parental drinking and covariates, including the child’s sex, mother’s education, and family structure.

Alcohol supply began in early childhood, with 14% of children exposed by age 3 and around 20% by age 11. By age 19, one-third of individuals reported frequent alcohol use. Adolescents’ alcohol use was associated with concurrent mothers’, but not fathers’ alcohol use (β = .24, p < .001). Early alcohol supply predicted higher adolescent use for both occasional (β = .14, p = .041) and frequent (β = .22, p = .005) classes. Mothers’ and fathers’ alcohol use at 6 months was associated with frequent alcohol supply, and fathers’ alcohol use was also associated with occasional alcohol supply. Significant indirect effects were found from early parental drinking to adolescent use via these classes.

Public health messaging should emphasize the risks of early alcohol consumption, including its potential harm to the developing brain.

As in other European countries, mental healthcare in Belgium has to deal with the increasing cultural diversity that exists within society. However, commitment of the Belgian healthcare system toward cultural diversity remains weak, and clear guidelines on culturally competent psychiatric practice are still lacking.

Three focus groups with professional caregivers, three with adult patients, and one with young adults in the transition age were organized. The seven focus groups each consisted of 5–10 participants. Two brainstorming sessions with a total of 15 experts were organized a priori to delineate focus group topics. Data analysis software MAXQDA 24 was used for thematic analysis.

The thematic tree consists of the central theme “culturally sensitive mental healthcare” with five main themes (i.e., vulnerable population, language barrier, mental healthcare stigma, spirituality/religion, Western vs non-Western frame of reference). These themes are further stratified into a number of subthemes and one overarching theme (i.e., diversity policy). The themes have resulted in six recommendations to improve cultural psychiatric care. These recommendations underscore the vulnerability of the target patient population, specific training needs, the need for professional interpreters and intercultural mediators, the place of religion and spirituality in therapy, reflexivity as core competence, and the need to establish reference centers.

The six recommendations provide a scientifically sound base to develop focused and effective mental health policies at the governmental, organizational, and patient level. Continued attention to the importance of cultural sensitivity in mental healthcare provision remains important, particularly in countries that are lagging behind.

Psychedelic-assisted psychotherapy has shown potential for psychiatric disorders. However, the magnitude of symptom change in control groups remains poorly understood. We aim to evaluate within-group effects in control groups and compare them to treatment groups in psychedelic trials.

A systematic search was conducted up to 1 July 2025. The study protocol was preregistered in PROSPERO (CRD420251111853).

Fourteen randomized controlled trials (n = 643) were included. Direct between-arm meta-analyses showed greater symptom reductions in treatment compared with control across outcomes, including depressive symptoms (number of study arms [k] = 13; SMD = −0.82; 95% CI = −1.17, −0.47; I2 = 60.1%), posttraumatic stress disorder (PTSD) symptoms (k = 10; SMD = −0.89; 95% CI = −1.14, −0.65; I2 = 0%), and anxiety symptoms (k = 5; SMD = −0.66; 95% CI = −0.94, −0.38; I2 = 0%). Subgroup analyses showed limited evidence that effects differed by placebo type for depressive or PTSD symptoms. Descriptive within-group analyses indicated symptom reductions from baseline in both control and treatment groups, with larger within-group improvements observed in treatment groups across outcomes; notably, larger within-group reductions in PTSD symptoms were observed in inactive placebo groups. Sensitivity analyses showed consistent results.

Control groups in psychedelic trials demonstrated substantial symptom improvement, which may reflect non-specific trial factors (including expectancy and concurrent psychotherapy). These findings emphasize the importance of robust control conditions in psychedelic research and the need for nuanced interpretation of treatment effects.

Suicide is a major public health challenge requiring early detection of suicidal ideation (SI). Traditional direct questioning methods suffer from stigma and disclosure bias, failing to identify many at-risk individuals. While machine learning (ML) models show promise, most lack external validation. Indirect screening, using psychosocial data rather than direct SI questions, offers a scalable alternative. This study aimed to externally validate an indirect, ML-based SI screening tool. We tested if a model trained on a Slovenian general population sample retained predictive accuracy when applied to an independent Croatian sample during a period of societal stress (pandemic and earthquakes), assessing performance across age and gender subgroups.

A logistic regression model was trained on a Slovenian sample (N = 2,989) and validated on a Croatian sample (N = 2,364). The model used only indirect predictors, including sociodemographics, life satisfaction, behavioral changes, and Brief COPE subscales. The target outcome was the presence of SI (SIDAS score > 0). Performance was measured by the area under the receiver operating characteristic curve (AUROC).

The model demonstrated strong external validity on the entire Croatian sample, achieving an AUROC of 0.80. Performance remained robust across subgroups: males (AUROC = 0.83), females (AUROC = 0.79), younger adults (AUROC = 0.77), and older adults (AUROC = 0.81). Self-blame, behavioral disengagement, and relationship dissatisfaction were key predictors.

An indirect, ML-based screening tool can reliably identify SI risk in the general population. The model demonstrated strong cross-national transferability and resilience during a societal crisis, proving it is a feasible and valid strategy for population-level prevention.