Individual responses to stress are highly heterogeneous, resulting in diverse psychopathological outcomes. This variability poses challenges for traditional diagnostic frameworks and underscores the need for a transdiagnostic approach to guide interventions. This study aimed to identify distinct phenotypes within a stress-exposed population and to characterize their biological profiles using a multimodal machine learning framework.

A total of 809 stress-exposed adults (mean age 40.5 ± 8.74 years; 53.7% female) underwent clinical, laboratory, and structural MRI assessments. Data-driven clustering of clinical variables identified phenotypes, followed by machine learning classifiers trained on neuroimaging and laboratory data to predict phenotype membership. SHapley Additive exPlanations (SHAP) analysis was used to identify key biological features distinguishing each phenotype.

Three phenotypes were identified: a multi-risk group (n = 321) characterized by prominent depression, anxiety, and sleep disturbances; an alcohol-related risk group (n = 226) with high alcohol misuse and minimal comorbidity; and a resilient low-risk group (n = 262). Machine learning models accurately classified these phenotypes, indicating distinct biological profiles. SHAP analysis revealed phenotype-specific signatures: the multi-risk phenotype was associated with frontal-subcortical structural alterations and dysregulated cortisol, whereas the alcohol-related risk phenotype was characterized by frontal-insular structural alterations and metabolic abnormalities.

This study demonstrates the stratification of stress-exposed individuals into clinically and biologically distinct phenotypes. By integrating multimodal data with machine learning, we identified phenotype-specific neurobiological and metabolic profiles that extend beyond conventional diagnostic frameworks. These findings support a transdiagnostic, data-driven approach to improve risk stratification and inform personalized interventions in stress-exposed populations.

Mental disorders are intergenerationally associated, particularly affecting adolescent offspring. However, the extent of such intergenerational associations among adult women in China remains unclear. This study aimed to examine the intergenerational associations of depression and anxiety between two adult female generations.

This cross-sectional study included 2,130 grandmother-mother dyads from the Grandmothers, Mothers, and Their Children’s Health study. Depression and anxiety of the grandmaternal (G0) and maternal (G1) generations were assessed using the 10-item version of the Center for Epidemiologic Studies Depression Scale and the 7-item Generalized Anxiety Disorder Scale, respectively, with scores of 10 or higher defined as depression and anxiety. Statistical analyses included logistic regression, negative binomial regression, and restricted cubic spline analyses.

A total of 11.4% G0 and 11.5% G1 participants reported depression, and 4.1% G0 and 3.1% G1 participants reported anxiety. Depression in G0 was associated with 4.29-fold (95% CI: 3.09–5.94) and 3.50-fold (95% CI: 1.98–6.01) higher odds of depression and anxiety in G1, respectively, while anxiety in G0 was associated with 3.95-fold (95% CI: 2.41–6.35) and 5.47-fold (95% CI: 2.64–10.60) higher odds of depression and anxiety in G1, respectively; dose–response relationships were also observed. In addition, the intergenerational association of depression was stronger among G0 participants residing in rural areas, whereas G0 depression and anxiety were more strongly associated with anxiety in G1 among those with higher household income.

Mental disorders were intergenerationally associated between mothers and their adult daughters. These findings emphasize the importance of family-based interventions for mental health.

Narcissistic Personality Disorder (NPD) involves disturbances in self-regulation, interpersonal functioning, and personality organization. Although traditionally characterized by grandiosity, contemporary models suggest that grandiose self-states coexist with vulnerable features such as shame, emotional dysregulation, and hypersensitivity to rejection. Recent evidence indicates that metacognitive impairments may underlie both grandiose and vulnerable narcissistic presentations; however, no study has examined how metacognition interacts with personality traits and interpersonal difficulties within an integrated system.

A cross-sectional network analysis was conducted on 287 patients with NPD. Measures included the Metacognition Assessment Interview, the Pathological Narcissism Inventory, the Personality Inventory for DSM-5 (PID-5), the Inventory of Interpersonal Problems, and SCL-90-R Depression. A Gaussian graphical model with LASSO regularization was estimated, and expected influence was used as the primary index of node centrality. Network accuracy and stability were assessed through bootstrapping procedures.

Narcissistic vulnerability was the most central node, followed by interpersonal sensitivity and metacognitive integration. Narcissistic vulnerability showed strong associations with PID-5 Negative Affectivity and Detachment, whereas narcissistic grandiosity was related to PID-5 Antagonism. Metacognitive integration occupied a central position, linking maladaptive traits and interpersonal distress. Network stability indices indicated good reliability.

Findings suggest that narcissistic vulnerability and interpersonal hypersensitivity are central aspects of dysfunction in NPD, whereas metacognitive integration appears closely associated with the organization of psychological processes within the network. Although causal inferences cannot be drawn, the results are consistent with theoretical models underlying Metacognitive Interpersonal Therapy (MIT), supporting the potential relevance of targeting integrative metacognitive capacities in NPD treatment.

While both evidence-based medicine as well as personalized patient-centered medicine are glorified, clinical practice seems to be only partially influenced by guidelines or by patients’ views. Against this background, shared decision-making (SDM) became a hype but remains an ill-defined concept: it can be considered as an umbrella concept covering therapeutic alliance, physician and patient preferences, information giving, information retrieving, information receiving, patient involvement in goal setting, decision-making, and treatment choice.

A narrative review based on a literature search in PubMed and PsycINFO.

SDM in depression should move away from an ethical imperative where “one size fits all” toward a personalized approach, tailoring the medical encounter to the physician’s and patient’s expectations (knowledge, need for knowledge, and desire for degree of SDM) and to the patient’s clinical status. SDM cannot be conceived as a “snapshot” since it is a dynamic process where adjustments should be made depending on the growth of the doctor–patient alliance, the changes in expectations, and the changes in clinical status. The clinician should be more aware of barriers to effective implementation of SDM in him or herself, in the patient. The different definitions of SDM and the many reported SDM interventions (having different ingredients) hamper final conclusions on the effect of SDM on outcomes.

This narrative review aims to critically examine SDM in depression and proposes to conceptualize it as a dynamic, relational, and personalized process rather than a universal ethical standard.

Esketamine has demonstrated efficacy in treatment-resistant depression (TRD), but medium-term real-world functional outcomes remain understudied. This study described 6-month depressive symptoms and functional trajectories during routine esketamine treatment, focusing on functional outcomes and remission correlates.

In this prospective multicenter study, 60 patients with TRD initiating intranasal esketamine augmentation were assessed at baseline, Month 1, Month 3, and Month 6 using the Montgomery-Åsberg Depression Rating Scale (MADRS) and Sheehan Disability Scale (SDS). Mixed-effects models, Turnbull interval-censored time-to-remission analysis, logistic regression, and ROC analyses were performed.

MADRS and SDS improved significantly at all follow-up time points (p < 0.001). At Month 6, symptomatic response and remission rates were 78.3 and 46.7%, while functional response and remission rates were 78.3 and 33.3%, respectively. Turnbull estimates showed cumulative functional remission rates of 5.0, 15.0, and 33.3% at Months 1, 3, and 6, respectively. MADRS-SDS correlations decreased over time, supporting partial symptomatic-functional dissociation. Higher baseline SDS (OR = 0.73, 95% CI: 0.59–0.89) and more previous antidepressant trials (ADTs; OR = 0.53, 95% CI: 0.35–0.82) were associated with lower odds of Month 6 functional remission; bootstrap internal validation supported coefficient stability. ROC-derived thresholds were considered sample-dependent and not clinically validated. Cumulative esketamine dosage was associated with functional response but not remission.

Depressive symptoms and functioning improved progressively over 6 months during esketamine treatment in routine clinical care. Functional remission followed a slower trajectory than symptomatic remission and had partly distinct correlates, supporting functional monitoring as a distinct TRD outcome.

Treatment-Resistant Late-Life Depression (TRLLD) represents a significant clinical and research challenge. Studies on TRLLD use heterogeneous diagnostic criteria limiting the interpretation of results and the development of clinical guidelines.

This study aimed to establish expert consensus on the core components and definition of TRLLD through a Delphi process conducted by a European Task Force of clinicians and researchers with experience in late-life depression.

We conducted an electronic Delphi study with 30 European experts to identify key definitional elements of TRLLD. In the 1st survey round (SR), participants responded to open-ended questions on definitions of TRLLD. Responses informed the development of 70 structured items for 2nd SR, involving 58 closed (yes/no) items and 12 multiple-choice questions across six domains: symptom presentation, cognitive impairment, comorbidities, pharmacotherapy, treatment adherence, and psychosocial factors. Consensus was defined as ≥70% agreement. In 3rd SR, participants reviewed comments and validated the final categorical definition, the operational staging model, and the derived decision algorithm for TRLLD.

Consensus was reached for 72.4% of the 58 closed items. Experts agreed that the categorical definition of TRLLD should correspond to major depressive disorder in individuals aged ≥65 years who show insufficient response to two adequate antidepressant treatments, in the absence of dementia and medical conditions that could account for depressive symptoms. An operational staging model and decision-making algorithm were developed from consensus items.

This study provides the first European consensus definition of TRLLD and highlights the need for age-adapted diagnostic criteria that reflect the clinical complexity of depression in older adults.

The development of cognitive impairment (CI) is a frequent and debilitating consequence of COVID-19 and can persist for more than 1 year after the acute infection stage. Previous neuroimaging studies in COVID-19 survivors with CI have revealed widespread alterations in functional connectivity (FC), particularly within fronto-parietal circuits and subcortical nuclei such as the hippocampus, basal ganglia, and thalamus. This study focuses on neural correlates of CI in subjects who recovered from COVID-19 and the relationship between FC patterns and discrete cognitive domains.

Resting-state functional MRI data from 136 subjects were analyzed using a ROI-to-ROI approach across 246 brain regions derived from the Human Brainnetome Atlas. Group comparisons were performed based on the presence or absence of CI, and correlation analyses were conducted between FC and scores obtained from a comprehensive neuropsychological test battery.

Whole-brain FC showed no difference between patients with and without CI. In the whole study sample, hypoconnectivity between two basal ganglia regions and two frontal motor regions was associated with impaired performance in the cognitive domain “Reasoning and Problem-Solving,” while hyperconnectivity between the prefrontal thalamus and the postcentral gyrus was associated with impaired performance in the same cognitive domain.

Our findings indicate that FC alterations within the cortico-striatal and thalamo-cortical circuits may subtend deficits in higher-order executive functions in post-COVID-19 patients and highlight the importance of examining discrete cognitive domains in relation to brain connectivity.

Gaming disorder (GD), i.e., persistent problematic gaming with clinically significant impairment, is a growing concern; however, estimates of GD in representative adolescent samples are limited. This study aimed to examine GD prevalence, incidence, persistence, and risk factors for different epidemiological parameters across 6 years, covering pre- to post-COVID-19 pandemic.

Population-based longitudinal data, including 3358 German adolescents, were collected annually from 2019 to 2024 using online surveys. GD prevalence estimates were assessed by standardized International Classification of Diseases (ICD-11)-based self-report questionnaires. Between-wave persistence and incidence of GD, sociodemographic data, gaming time, and stress perception were measured. Risk factors for incidence and persistence of GD were examined using generalized-estimating equation (GEE) models.

GD prevalence doubled from 2.9% in 2019 to 6.5% in 2023 and remained above prepandemic levels in 2024 (3.9%). Males showed higher prevalence estimates compared to females across most waves, and prevalence peaked in 2023 (8%). For females, GD prevalence doubled between 2019 (1.7%) and 2020 (3.4%), peaked in 2022 (6.1%), and declined thereafter. The incidence of GD increased during the pandemic. According to GEE models, male sex, higher perceived stress, and longer gaming times were risk factors for GD incidence; older age and higher education were protective factors. The persistence of GD reached its peak in 2020 (36.2%). Significant risk factors for GD persistence were higher stress perception and longer gaming time.

Prevalence and incidence rates indicate that GD continues to be a significant concern, and pandemic-related increases affected both males and females. Prevention and intervention programs should target identified risk groups.

Cultural competence training has become increasingly common in psychiatric practice across Europe and worldwide, supported by evidence demonstrating improvements in quality of care, clinical effectiveness, and patient satisfaction. Since the publication of the original EPA guideline in 2015, the field has advanced considerably in its theoretical foundations, evidence base, and institutional support. This updated guideline addresses recent developments and challenges in research, policy, and clinical practice.

The guideline is based on a systematic meta-review of 15 systematic reviews and evidence-based guidelines on cultural competence training in psychiatric care and mental health. The evidence was synthesized to identify key concepts, educational components, implementation strategies, and current debates.

The review comprises four sections. First, it examines core elements of cultural competence training, emphasizing cultural humility, structural competence, and perspectives from the social and cultural sciences. Second, it provides practical recommendations for curriculum design, including the potential role of digital learning tools. Third, it addresses critiques of cultural competence, particularly concerns regarding essentializing and potentially racist interpretations. Finally, it explores strategies for integrating cultural competence training into existing psychiatric services, highlighting both individual and organizational factors that support implementation.

Cultural competence benefits not only migrant and ethnically diverse populations but all patients and healthcare professionals, including members of majority cultures. Successful implementation requires cultural sensitivity, critical self-reflection, and sustained commitment at individual, organizational, and system levels to achieve meaningful and lasting improvements in psychiatric care.

Late-life depression refers to a depression occurring in older adults, defined as individuals aged 65 years and older. It is common and often mismanaged due to complex clinical profiles, polypharmacy, and limited evidence-based guidance. Existing tools poorly address psychiatric nuances in older adults. This work aims to develop French recommendations based on experts’ consensus on the use of antidepressants in unipolar late-life depression, to guide safer prescribing practices.

This tool was developed using a Delphi survey, based on a review of literature published between 2014 and 2024 and focused on “antidepressants” and “late-life depression” Experts from various fields: geriatric psychiatry, clinical pharmacy and general practice, rated items using a 9-point Likert scale. Items with a median score ≥ 7 and at least 80% agreement were validated and included in the final version of the tool.

Twenty to 23 experts per round, different from the authors of the proposed items, participated in a four-round Delphi process. The resulting tool includes 57 validated items across 10 sections and a stepped-care algorithm for treating major depression in older adults. It addresses drug choice, dosing, monitoring, comorbidities, and treatment resistance, prioritizing safe first-line options like sertraline, citalopram, and escitalopram.

A Delphi survey involving multidisciplinary experts led to a French consensus tool for prescribing antidepressants in unipolar late-life depression. It integrates clinical evidence and expert judgment to address treatment complexity, drug safety, and resistance. The tool offers practical, stepwise recommendations tailored to primary care, aiming to optimize antidepressant use, reduce iatrogenesis, and improve patient outcomes.

Cannabinoids are increasingly discussed as adjuncts in addiction treatment, yet whether they improve clinically meaningful substance use disorder (SUD) outcomes beyond short-term symptom relief is unresolved. We determined whether cannabinoid exposure confers directional efficacy across opioid, alcohol, cocaine, tobacco, and methamphetamine use disorders, distinguishing symptomatic targets from sustained therapeutic outcomes.

PubMed and Embase (1975–2025) were searched for human studies evaluating cannabinoid exposure in relation to SUD outcomes. Two reviewers independently screened and extracted data. Risk of bias was assessed using RoB 2 for randomized controlled trials (RCTs), ROBINS-I for cohort studies, and JBI checklists for cross-sectional, case, and qualitative designs. Six prespecified endpoints (treatment retention, relapse, abstinence, craving, withdrawal severity, consumption) were mapped to each target SUD. Following Synthesis Without Meta-analysis (SWiM) guidance, structured narrative synthesis used a design-based weighting scheme (RCT 1.00 to qualitative 0.25). PROSPERO: CRD420251151193.

Ninety-seven studies (41,954 participants) contributed 195 endpoint instances: 89 Beneficial (45.6%), 80 No Significant Effect (41.0%), 12 Mixed/Partial (6.2%), and 14 Harmful/Inferior (7.2%). Short-term symptom targets accounted for most Beneficial findings (76.4%). Sustained outcomes were predominantly No Significant Effect, most pronounced in opioid use disorder. Beneficial symptom findings derived overwhelmingly from weaker study designs (craving 81.5%; withdrawal severity 85.7%; consumption 80.0%).

Cannabinoids confer short-horizon symptomatic benefits but do not demonstrate efficacy for sustained abstinence, relapse prevention, or retention, most clearly in opioid use disorder, where evidence is strongest. Findings for other disorders remain preliminary. Adequately powered adjunctive randomized trials with biochemically verified endpoints are needed.

Previous research has demonstrated the positive impact of early remission on disease trajectory for patients with major depressive disorder. However, there is a paucity of literature assessing the response trajectory for patients with treatment resistant depression (TRD). These analyses investigated patient outcome trajectories to Week 32, including the relationship between short- and long-term outcomes with esketamine nasal spray (ESK-NS) treatment and symptom resolution.

ESCAPE-TRD (NCT04338321), a randomized, open-label, phase IIIb study, evaluated the efficacy and safety of ESK-NS versus quetiapine extended release (QTP-XR) in patients with TRD. Rater-blinded Montgomery-Åsberg Depression Rating Scale (MADRS) total score was used to assess depressive symptoms and the trajectory of patient responses to Week 32. For ESK-NS versus QTP-XR, time to symptom resolution across MADRS items was evaluated using Kaplan–Meier analyses.

Of 676 patients, 336 and 340 were randomized to ESK-NS and QTP-XR, respectively. Most ESK-NS-treated patients achieved continuously improved outcomes to Week 32; early response was associated with better long-term outcomes. Among patients who achieved Week 4 response, 89.6% achieved remission at any point from Week 4 to 32; 78.3% of Week 8 responders achieved remission at any point from Week 8 to 32. Greater and earlier symptom resolution was observed with ESK-NS versus QTP-XR across most MADRS items.

Most ESK-NS-treated patients with TRD showed continuous improvements over time, with short-term response associated with better long-term outcomes. Long-term improvements were observed even among partial/minimal early responders, reinforcing the value of longer treatment. ESK-NS had a positive impact across the full spectrum of MADRS-assessed symptoms.

Bipolar disorder (BD) is frequently misdiagnosed as major depressive disorder (MDD), with diagnostic delays averaging 6–10 years leading to suboptimal treatment and poorer outcomes. Early identification of patients at risk for diagnostic conversion remains a critical clinical priority. We aimed to identify clinical predictors of BD conversion in a large population-based cohort and develop a clinically applicable prediction model.

We conducted a retrospective cohort study using electronic health records from the Catalan PADRIS-PRESTO database (2010–2019). Patients aged ≥18 years with incident MDD diagnosed in specialized mental health services (2015–2019) were followed until BD diagnosis, death, or study end. Time-varying Cox regression addressed proportional hazards violations, with competing risks analysis accounting for mortality.

Among 52,001 patients (median follow-up 4.0 years), 3,958 (7.61%) converted to BD. Psychotic features emerged as the strongest predictor (HR = 3.18, 95% CI: 2.92–3.45, E-value = 5.82), with consistent effects across follow-up. Anxiety disorders showed time-varying protection (baseline HR = 0.41, 95% CI: 0.35–0.48) that attenuated over time (interaction HR = 1.30 per period). The time-varying model achieved good discrimination (C-index = 0.745). Machine learning validation confirmed predictor importance rankings (Spearman r = 0.87).

Psychotic features during depressive episodes robustly predict BD conversion, warranting enhanced clinical monitoring. Our time-varying prediction model using routinely collected clinical data enables early risk stratification to guide diagnostic vigilance and treatment decisions.

Gaming disorder (GD) is recognized by the WHO as a behavioral addiction, yet research remains predominantly men-centric. This study explores the experiences of women gamers, their perceptions of GD, and the barriers women face in accessing care.

Semi-structured interviews were conducted with seven participants identifying as women (six cisgender women and one transgender woman) aged 21–26 years old, in France and Switzerland. Inductive reflexive thematic analysis was used to identify women’s experiences of gaming behavior, stigma, and help-seeking.

Participants reported diverse gaming behaviors, with preferences for narrative-driven games (e.g., RPG and simulations). Stigma, lack of self-awareness, limited self-recognition of problematic gaming, and broader societal misconceptions emerged as significant barriers to recognizing GD as a potential clinical issue warranting help-seeking. None had sought professional care for GD, citing gendered stereotypes and diagnostic biases as key deterrents.

The study highlights the need for women-centered diagnostic tools, clinical approaches, targeted awareness campaigns, and flexible support systems for women with GD. Future research should prioritize larger, diverse samples and intersectional approaches.

There has been growing interest in developing a clinical staging model for eating disorders (EDs). The aim of this scoping review is to investigate the extent, range, and nature of research that can inform clinical staging approaches for EDs.

This review was conducted following the Joanna Briggs Institute methodology for scoping reviews and the PRISMA extension for Scoping Reviews. A search of PubMed, PsycINFO, MEDLINE and Web of Science databases was conducted. Sixty studies were included for review, and data were extracted according to revised pre-published criteria. Studies were summarized using narrative synthesis.

Thirty-six of the included manuscripts were quantitative, 18 were qualitative, and six were conceptual/review papers. The included studies primarily focused on anorexia nervosa in white, female samples and compared only two stages of illness, equating to “early” and “longstanding” or “severe and enduring” EDs. “Middle” stages or transitions between stages were not well-defined. Stages have mostly been conceptualized using duration of illness or other behavioral or clinical parameters, with few (neuro) biological studies identified. Factors that may modify illness stage have not yet been integrated into ED staging literature.

There is growing consensus that early- and later-stage EDs have distinct characteristics and treatment requirements; however, these distinctions require clearer definition. Recommendations for future research are outlined, emphasizing integration of psychosocial and biological research, focused investigation of illness phases outside of early and longstanding phases, and evaluation of personalized, stage-based treatments. A tentative staging model for EDs is proposed.

Early adolescence marks a critical period for the onset of psychiatric symptoms, with 50% of mental disorders emerging before age 18. Recent evidence points to individuals being born preterm and/or with low birth weight (henceforth, PTB) having an increased risk of developing mental disorders in adolescence. Surprisingly, existing early detection and intervention strategies in adolescence are not tailored to PTB needs and profiles. The previous use of several disorder-specific instruments complicates unified, efficient screening.

We analyzed data on the frequency of experiencing mental health challenges from 225 adolescents aged 10-14 years (M = 12.03 years) who were born very PTB (M = 28.03 weeks, M = 999.62 g) to test the applicability of the diagnostic system for mental disorders for children and adolescents – III (DISYPS-III) to PTB adolescents.

A confirmatory factor analysis replicated the DISYPS-III’s factorial structure and internal consistency for 10- to 14-year-old PTB adolescents. Overall, PTB adolescents reported significantly more mental health challenges than the DISYPS-III community norm sample. The instrument’s transdiagnostic scales provided a better relative fit to these challenges compared to the disorder-specific scales. Results also replicated specific findings of mental health challenges from other PTB cohorts and countries, such as a higher number of comorbidities in adolescents officially diagnosed with the inattentive presentation (ADD) of ADHD.

These findings of an elevated psychological burden suggest a need for structured PTB screening of long-term mental health outcomes in adolescence that also includes 10-year-old PTB individuals, with the DISYPS-III being a suitable screening instrument.

Schizophrenia is often a persistent mental illness characterized by cognitive deficits and altered brain network dynamics especially affecting the cortico-subcortical salience processing system. Childhood trauma has been implicated in mechanisms contributing to schizophrenia, but the role of genetic vulnerability remains unclear.

A total of 164 schizophrenia patients and 114 healthy controls were included. First, a matched subsample of 117 patients (76 with and 41 without childhood trauma), and 59 healthy controls were compared on polygenic risk scores for schizophrenia (SczPRS). SczPRS was then correlated with neurocognitive performance using a comprehensive cognitive battery (n = 147 patients) and brain-wide static and dynamic functional connectivity (sFC and dFC) using resting-state fMRI (n = 117 patients). Patients were also stratified into high-SczPRS and low-SczPRS (n = 25 each) subgroups.

Patients with childhood trauma had significantly lower SczPRS than those without. Higher Childhood Trauma Questionnaire (CTQ) scores related to lower cognitive PC score (r = −0.282, p < 0.001), but CTQ did not affect brain-wide dysconnectivity or subcortical/salience system among patients. Patients with the highest SczPRS showed lower dFC between the cingulo-opercular network and subcortical networks (F = 7.949, p = 0.007), but SczPRS did not affect cognitive performance.

Our findings reveal distinct effects of childhood trauma and polygenic risk in the neural and cognitive substrates of schizophrenia. Childhood trauma relates to poor cognitive function, while polygenic risk primarily affects salience/subcortical network dynamics. These patterns indicate that in genetically predisposed individuals who experience childhood trauma, a “double mechanistic hit” may influence the schizophrenia phenotype.