The application of artificial intelligence (AI) to resting-state electroencephalography (EEG) data represents a burgeoning frontier in schizophrenia diagnostics. However, the inferential validity of findings is frequently compromised by methodological heterogeneity. This systematic review rigorously evaluates the diagnostic efficacy and methodological robustness of AI-generated EEG biomarkers by implementing the Prediction model Risk Of Bias Assessment Tool for Artificial Intelligence (PROBAST+AI).

Following PRISMA guidelines, a systematic search of PubMed, Scopus, and Web of Science identified 43 primary studies encompassing 3,420 patients with schizophrenia or first-episode psychosis and 3,164 healthy controls (total N = 6,584). Methodological quality and validation strategies were assessed using the 34 signaling questions of the PROBAST+AI framework.

The aggregate mean diagnostic accuracy across the literature was 93.38%, with deep learning architectures demonstrating superior metrics relative to classical machine learning (96.83% vs. 87.68%). Critically, external validation was restricted to 4.7% of the included studies. A pronounced performance discrepancy was observed between subject-wise (88.22%) and segment-wise (98.14%) validation protocols, indicating pervasive data leakage. Overall, 76.7% of the analyzed studies were characterized by a high risk of bias, predominantly stemming from suboptimal data partitioning and inadequate independent verification.

Contemporary diagnostic accuracies appear to be artifactually elevated due to structural methodological deficiencies and data leakage. Consequently, current evidence does not support the immediate clinical implementation of AI-EEG biomarkers in schizophrenia. To facilitate translational progress, we propose a standardized methodological framework optimizing validation strategies.

Obsessional jealousy is described in DSM-5 under Other Specified Obsessive-Compulsive and Related Disorders, yet operationalized criteria and clinical characterization are lacking. This study aimed to develop and field-test provisional research criteria for obsessional jealousy and describe the clinical features of individuals meeting these criteria.

Provisional research criteria were developed based on DSM-5 descriptions and applied in a self-referred sample of individuals reporting problematic jealousy (n = 58). Participants underwent structured clinical assessment, including best-estimate diagnostic procedures, evaluation of differential diagnoses, and measures of functional impairment. Participants’ views on introducing a formal jealousy diagnosis were explored.

Among the participants, 34 (59%) met the provisional research criteria. The criteria showed strong sensitivity but modest specificity, reflecting a deliberately conservative threshold to avoid over-pathologization. All individuals meeting criteria were judged to meet DSM-5 and ICD-11 definitions of mental disorder. Obsessional jealousy was typically recurrent across relationships, with onset in mid-adolescence and clinical significance emerging in early adulthood. Participants showed generally good insight; comorbidity was common with mood and anxiety disorders. Many reported prior help-seeking and ongoing need for treatment. Participants expressed balanced views regarding formal diagnosis, citing both potential benefits and risks.

These findings identify a group of individuals with pervasive, recurrent obsessional jealousy that is distressing, impairing, and not readily explained by existing diagnostic categories. The proposed criteria provide an initial framework for research and clinical development but require further refinement and validation in more representative community and clinical samples, with careful attention to diagnostic boundaries, transcultural aspects, and stakeholder perspectives.

The European Psychiatric Association (EPA) undertook a study to investigate treatment preferences of European psychiatrists towards Bipolar Disorder (BD), as part of the Ambassador programme series of surveys.

We conducted a cross-sectional online survey among psychiatrists and psychiatry trainees from 40 European countries. The questionnaire contained clinical vignettes of different phases of BD including manic, rapid cycling, mixed, hypomanic, and depressive episodes, for both initial and subsequent treatment strategies.

The final sample consisted of 654 participants, from Central and Eastern Europe (CEE), Southern Europe (SE), Northern Europe (NE), and Western Europe (WE). The majority preferred pharmacotherapy, most commonly as a combination of two or three drugs to treat all phases of the BD, with lithium being the most preferred option in all phases.

Among antipsychotics, olanzapine and quetiapine were the most commonly chosen. Antidepressants were applied in almost 20% of responses for the depressive phase. Psychosocial interventions were not systematically implemented, particularly during manic and mixed episodes, but when recommended, the most common approaches included psychoeducation, cognitive behavioural therapy (CBT) in up to 40% in depressive phase, and lifestyle recommendations. However, latent class analysis identified four different classes of prescribers.

Psychiatrists showed broadly similar pharmacological treatment preferences for BD, with frequent use of lithium-based combination therapies and limited implementation of psychosocial interventions, although latent class analysis revealed distinct prescribing profiles. These findings support the need for enhanced dissemination of evidence-based guidelines and greater integration of psychosocial approaches in BD care.

Childhood maltreatment (CM) has been linked to poor emotional intelligence (EI) and psychosocial functioning (PSF) in patients with bipolar disorder (BD). However, no study has investigated whether EI mediates the relationship between CM and PSF in patients with BD. Here, we aimed to assess the association of CM with EI and PSF in euthymic patients with BD compared with healthy controls (HCs).

We assessed 124 euthymic participants with a BD diagnosis and 124 HCs by means of the Mayer–Salovey–Caruso Emotional Intelligence Test, the Functioning Assessment Short Test and the Childhood Trauma Questionnaire. Linear regression models were constructed using CM categorized as no-CM, low/moderate-CM and high-CM. We subsequently assessed whether EI mediates the relationship between CM and PSF.

Compared with HCs, patients with BD reported higher rates of CM and lower rates of PSF and EI. In the BD group, subjects who exhibited low/moderate CM obtained lower levels of PSF and EI than those with no-CM and high-CM levels. The regression models demonstrated that, compared with the no-CM category, the low/moderate CM category was inversely associated with EI strategic area scores in patients with BD. However, EI did not mediate the relationship between CM and PSF.

Low/moderate-CM was associated with the worst EI scores in BD. However, we did not observe any mediating effect of EI on the relationship between CM and PSF. Our results emphasize the importance of assessing CM in mental health and suggest that targeted therapies should be administered to affected patients.

Prolonged war-related adversity places Ukrainian university students at heightened risk of psychological distress. Scalable, low-intensity interventions such as WHO Self-Help Plus (SH+) show promise, yet evidence of their implementation and short-term effectiveness during active conflict is limited.

A multicenter longitudinal study was conducted across five universities. Students with mild-to-moderate distress (PSS-10) joined a 5-week offline Acceptance and Commitment Therapy-based SH+ course led by trained non-specialist facilitators. Outcomes included psychological distress (PHQ-9, GAD-7, PCL-5), well-being (WHO-5), daily functioning (WHODAS 2.0), and resilience (CD-RISC-10), assessed at baseline (T1), post-intervention (T2), and 3-month follow-up (T3). Analyses used non-parametric longitudinal tests on 297 completers.

SH+ participation significantly reduced perceived stress, depression, anxiety, and post-traumatic stress from T1 to T2. Well-being and daily functioning improved, with all gains sustained at T3. Resilience remained stable. Implementation barriers included security threats, power outages, and exam overlaps, contributing to attrition.

WHO SH+ is an effective, scalable first-line psychosocial intervention for university students in wartime. It alleviates distress, enhances functioning, and maintains benefits over 3 months. SH+ can be rapidly deployed by non-specialists within stepped-care university frameworks during humanitarian crises. Flexible delivery and alignment with academic schedules are essential to overcome conflict-driven barriers.