Bipolar disorder (BD) is commonly comorbid with other psychiatric conditions, such as obsessive-compulsive disorder (OCD). Despite increasing interest in this comorbidity, quantitative data on its clinical characteristics remain limited. This systematic review and meta-analysis aimed to evaluate the clinical impact of OCD comorbidity in BD by comparing individuals with BD and OCD (BD-OCD) to those with BD without OCD.

We systematically searched the PubMed/MEDLINE, Scopus, PsycINFO, and Web of Science databases up to April 15, 2024. Meta-analyses were conducted to compare BD-OCD and BD without OCD groups across multiple clinical domains.

From 11,959 initial records screened, 26 studies were included in the qualitative synthesis, with 22 eligible for meta-analysis. Individuals with BD-OCD showed higher odds of experiencing chronic mood episodes (OR = 9.42; 95%CI = 2.23, 39.9), rapid cycling (OR = 1.92; 95%CI = 1.04, 3.53), comorbid eating disorders (OR = 3.37; 95%CI = 1.99, 5.7), panic disorder (OR = 3.3; 95%CI = 2.11, 5.2), substance use disorders (OR = 1.39; 95%CI = 1.02, 1.89), and lifetime suicide attempts (OR = 1.85; 95%CI = 1.21, 2.84). Additionally, they presented earlier onset of BD (SMD = -0.27; 95%CI = -0.52, −0.01) and reduced functioning (SMD = -0.42; 95%CI = -0.59, −0.24). Most data were derived from adult populations, limiting the evidence available for children and adolescents.

BD-OCD presents a more severe and complex clinical profile, requiring specialized assessment and integrated treatment approaches. Identifying these features may support earlier recognition and inform personalized interventions for this population.

Little is known about the diagnostic trajectories following a first psychiatric diagnosis in childhood or adolescence. Such knowledge could aid clinicians in treatment, risk prediction, and psychoeducation. This study presents a comprehensive nationwide overview of diagnostic trajectories in children and adolescents after their first diagnosis in child and adolescent psychiatric hospitals.

Patients aged 0 to 17 years who received their first psychiatric diagnosis between January 1996 and December 2011 were identified through the Danish National Patient Registries. Shifts at the International Classification of Diseases (ICD-10) two-cipher level (F00-F99), grouped into 19 categories, were identified. Subsequent diagnoses during 10 years of follow-up until December 2021 were identified and analyzed using state sequence analysis and Cox proportional hazard regression models.

A total of 77,464 children and adolescents (32,733 [42.26%] girls) were identified with a first-time psychiatric diagnosis. Among these, 46.7% of girls and 37.6% of boys had at least one diagnostic shift after 10 years of follow-up. High entropy and low diagnostic stability were found in first-time diagnoses often presenting in adolescence, such as affective disorders, psychotic illness, and personality disorders, while lower entropy and high diagnostic stability were found in neurodevelopmental disorders and eating disorders. For most categories, girls had higher mean entropy measures than boys (P < 0.05).

Diagnostic shifts are common in child and adolescent psychiatric services, particularly when the first contact occurs in adolescence. Adequate focus on psychoeducation about emerging diagnostic shifts, and on timely detection, particularly in girls, and particularly in adolescence, is warranted.

Esketamine has been shown to produce a major antidepressant response in patients with treatment-resistant depression (TRD). We evaluated the factors associated with achieving remission in these individuals.

The study was carried out across four psychiatry departments in Madrid, Spain. Patients aged over 18 years were included if they received esketamine as an augmentation treatment for TRD. Standard esketamine protocol included an induction phase (4 weeks) and a maintenance phase (5 to 8 weeks). Subsequent treatment continuation was proposed. Clinical data and scores at the Clinical Global Impression scales were measured following each esketamine administration.

Sixty-five patients initiated the treatment, and 45 patients (69.2%) completed the standard protocol. The median number of esketamine administrations was 19. The mean age was 53.09 and 52.3% of the patients were females. Out of the whole sample, 36 (55%) of the patients achieved remission over the follow-up. Remission rates elevated to 67% in those who completed the standard protocol, and to 70% in those having received more than 19 esketamine administrations. Achieving remission over the follow-up was associated with the absence of dissociative symptoms, and with completing the standard esketamine protocol (OR = 0.229, p = 0.045; and OR = 4.538, p = 0.025, respectively). Receiving more than 19 esketamine administrations was associated with remission over the follow-up (OR = 6.513, p = 0.006).

Our results suggest that extending the numbers of esketamine administration may increase the chances to obtain remission. Adverse effects did not impact the treatment course.

Cannabis use is elevated in youth with depression and attention-deficit/hyperactivity disorder (ADHD), but drivers of this increase remain underexplored. The self-medication hypothesis suggests cannabis is used by patients for mood regulation, a common difficulty in ADHD and depression. This study aimed to examine associations between mood instability and cannabis use in a large, representative clinical cohort of adolescents diagnosed with ADHD and/or depression.

Natural language processing (NLP) approaches were utilised to identify references to mood instability and cannabis use in the electronic health records of adolescents (aged 11–18 years) with primary diagnoses of ADHD (n = 7,985) or depression (n = 5,738). Logistic regression was used to examine mood instability as the main exposure for cannabis use in models stratified by ADHD and depression.

Mood instability was associated with a 25% higher probability of cannabis use in adolescents with ADHD compared to those with depression. Following adjustment for available sociodemographic and clinical covariates, mood instability was associated with increased cannabis use in both ADHD (aOR: 1.61 [95% CI: 1.41–1.84]) and depression (aOR: 1.38 [95% CI: 1.21–1.57]) groups.

This was the first study to explore the differential impact of mood instability on adolescent cannabis use across distinct diagnostic profiles. NLP analysis proved an efficient tool for examining large populations of adolescents accessing psychiatric services and provided preliminary evidence of a link between mood instability and cannabis use in ADHD and depression. Longitudinal studies using direct measures or tailored NLP techniques can further establish the directionality of these associations.

There is an urgent need to improve early accessibility to psychoeducational interventions for informal caregivers of individuals with eating disorders (EDs). We adapted the BREF programme, a short, single-family, psycho-educational intervention originally developed for caregivers in severe mental disorders, to EDs (BREF-ED) and assessed at diagnosis announcement. We hypothesised that it has a good acceptability and effectiveness in reducing short-term caregivers’ self-reported levels of burden and depressive symptoms.

Data of caregivers who participated in the BREF-ED programme were analysed. Adherence, satisfaction, and perceived usefulness were evaluated. Changes in self-reported burden and depression symptoms were measured pre-, post-, and 3 months after the intervention using the Zarit Burden Interview (ZBI) and Center for Epidemiological Studies – Depression scale (CES-D).

Of the 53 caregivers included in the study, 52 participants completed the BREF-ED programme. As compared to baseline, ZBI scores showed a significant reduction after the intervention (Cohen’s d = 0.61, p < 0.001), and at the 3-month assessment (Cohen’s d = 0.62, p < 0.001). The CES-D scores also significantly decreased by the end of the third session (Cohen’s d = 0.83, p < 0.001) and at the 3-month follow-up (Cohen’s d = 0.77, p < 0.001). Satisfaction scores were high, with 90.1% of participants reporting being “very satisfied” and 9.9% “satisfied.”

Preliminary findings demonstrated high adherence rates, caregiver satisfaction, and a positive impact on burden and related depressive symptoms immediately after the programme and at short-term follow-up. This time- and resource-efficient programme has the potential for easy dissemination.

Certain prescription drugs used during pregnancy are associated with offspring autism spectrum disorder (ASD). Nonetheless, ASD risk following prenatal exposure to most drugs remains unknown. Furthermore, methodological challenges and ethical concerns hinder the scope for causal inference.

We used a case-cohort study design of a nationally representative sample from Israel to examine the associations between maternal prescription drug use during pregnancy and offspring ASD. To scrutinize these associations, the analyses were (a) adjusted for indication proxy (level 2 Anatomical Therapeutic Chemical (ATC) codes), (b) repeated using shared pharmacological targets as exposures, and (c) inspected further through target-enrichment analysis.

The sample included 1,400 individuals with and 94,713 without an ASD diagnosis. Among all drugs prescribed during pregnancy, five were statistically significantly associated with increased offspring ASD risk after adjustment for indication proxy (e.g., hazard ratio [95% confidence interval] cyproterone = 2.71 [1.17–6.25] and prednisolone = 2.10 [1.27–3.49]), and two with decreased risk (ferrous sulfate = 0.82 [0.68, 0.99] and lynestrenol = 0.43 [0.2, 0.93]). Further analysis revealed four pharmacological targets shared by these drugs, which were themselves associated with ASD (e.g., neuronal acetylcholine receptor α4β4 = 1.45 [1.05–1.99] and serotonin 2b receptor = 1.31 [1.04–1.61]). Enrichment analysis suggested the association between ASD and medications affecting cholinergic and serotonergic signaling.

Increased ASD risk followed prenatal exposure to five prescription drugs, and decreased risk followed exposure to two. Subsequent analyses suggested no confounding by indication in these associations, but further studies are warranted.

This analysis evaluated potential differences in subjective well-being (SW) among patients with early-phase schizophrenia (SZ) randomized to treatment with either long-acting injectable (LAI) or oral aripiprazole or paliperidone within the “European Long-acting Antipsychotics in Schizophrenia Trial” (EULAST).

A total of 478 patients were followed for up to 19 months. SW was measured using the Subjective Well-being under Neuroleptic Treatment scale (SWN). Linear mixed-effects models assessed treatment differences. Comprehensive analyses included age, sex, symptomatology (Positive and Negative Syndrome Scale [PANSS]), and side effects (Systematic Monitoring of Adverse Events Related to Treatments [SMARTS] and St. Hans rating scale [SHRS] for extrapyramidal syndromes) on SWN changes.

Overall, SW improved over the course of the study. No significant differences emerged between LAI and oral administration (p = 0.1533) or between aripiprazole and paliperidone (p = 0.2008). Similarly, age and sex were not relevant in this regard. In contrast, negative, positive, and affective symptoms (all p < 0.0001) as well as the overall side effect burden (SMARTS sum-score, p < 0.0001) showed significant inverse associations with SW. Certain SHRS subscales correlated with SW in partial models, but associations disappeared in the fully adjusted model.

Patients with SZ initiating LAI or oral treatment with aripiprazole or paliperidone reported comparable SW improvements. Findings emphasize that treatment choice should be guided less by formulation or substance and more by individual patient needs, prioritizing symptom control while minimizing adverse effects. A patient-centered approach remains essential to optimize both clinical outcomes and subjective well-being in early-phase SZ.

Network analysis is a promising approach for elucidating the dynamics of the transition from psychopathology to well-being. Recently, symptom connectivity strength has been proposed as a measure of plasticity – the capacity to change disease severity. Yet, empirical findings remain inconsistent. We propose that this inconsistency can be resolved by recognizing that the interpretation of connectivity strength varies along the recovery process from depression, whether at baseline or during clinical change.

We analyzed 2,710 depressed patients from the STAR*D dataset, grouped by the magnitude of change in depressive score. Symptom network connectivity was estimated from QIDS-C items at three time points: (i) baseline, (ii) change – defined as when clinical change in depression score occurs, (iii) post-change - corresponding to when the maximum clinical change is achieved.

At baseline, connectivity strength predicts the maximum clinical change, inversely correlating with its magnitude (ρ = −0.95, p = 0.001). At the change time point, connectivity strength parallels clinical change (ρ = 0.92, p = 0.002). A direct and significant association between connectivity strength and depression severity emerges only at the change (ρ = 0.98, p = 0.0003) and post-change (ρ = 0.95, p = 0.001) time points.

The interpretation of connectivity strength for predicting depression trajectories varies by timepoint: at baseline, it measures plasticity -- the capacity for change -- whereas during clinical change, it indicates the magnitude of change in symptom severity. This framework supports the reliability of this prognostic marker for designing personalized therapeutic interventions in psychiatry.

Many patients with major depressive disorder (MDD) do not respond sufficiently to first-line treatments. Due to its biological and psychological mechanisms, exercise may enhance the effectiveness of other MDD treatments. In a pragmatic randomised superiority trial, we evaluated the clinical and cost-effectiveness of exercise therapy adjunct to guideline-concordant care as usual (CAU) for MDD in specialised mental health care.

MDD outpatients (N = 112; Mage = 37; 51% female) were randomized to CAU (96.9% psychotherapy, 59% pharmacotherapy) or CAU + EX (CAU plus 12 weeks of exercise therapy: one supervised and two home-based aerobic sessions/week). Depressive symptoms were assessed using the Inventory of Depressive Symptomatology-Self Report. Remission was evaluated during follow-up by blinded assessors using the Structured Clinical Interview for DSM-5. The economic evaluation followed a societal perspective.

Patients in the CAU + EX condition were significantly more likely than those in CAU to meet the exercise prescription; however, only 22% fully adhered to it. Depressive symptoms decreased from severe to moderate depression in both conditions, with no significant difference between the conditions on symptom reduction (b = −0.22, [−0.72, 0.29]) or remission rate (OR = 0.06, [−0.20, 0.32]). Evidence for cost-effectiveness was found in the per-protocol (≥ six supervised exercise sessions) but not in the intention-to-treat sample.

Adjunct exercise therapy does not provide additional clinical benefits or cost-effectiveness in specialized mental health care. Low adherence to the exercise prescription limits its potential. Cost-effectiveness may be achievable with higher adherence, warranting emphasis on strategies to improve adherence in this population.

Chronic pain (CP) and mental disorders often coexist, yet their relationship lacks comprehensive synthesis. This first hierarchical umbrella review examined systematic reviews and meta-analyses, also observational studies and randomized controlled trials (where reviews are currently lacking) to report CP prevalence, risk factors, and treatment across mental disorders.

We searched MEDLINE, PsycINFO, Embase, Web of Science, and CINAHL, identifying 20 studies on anxiety, depression, bipolar disorder, schizophrenia, ADHD, autism, or dementia, and CP. Quality was assessed using AMSTAR and Newcastle-Ottawa Scale.

Prevalence varied widely—23.7% (95% CI 13.1–36.3) in bipolar disorder to 96% in PTSD—consistently exceeding general population rates (20–25%). Risks were elevated, with bidirectional links in depression (OR = 1.26–1.88). Risk factors included female gender, symptom severity, and socioeconomic disadvantage, though data were limited beyond PTSD and depression. Treatment evidence was sparse: cognitive behavioral therapy showed small effects on pain (SMD = 0.27, 95% CI -0.08–0.61), acupuncture with medication improved pain (MD = -1.06, 95% CI -1.65–-0.47), and transcranial direct current stimulation reduced pain in dementia (d = 0.69–1.12). Methodological issues were evident, including heterogeneous designs and inconsistent pain definitions.

This review confirms CP as a significant comorbidity in mental disorders. Clinicians should prioritize routine pain screening and multimodal treatments. Researchers need longitudinal studies with standardized assessments to clarify causality and improve interventions. Taken together, this work highlights an urgent need for integrated psychiatric care approaches, emphasizing that addressing CP could enhance mental health outcomes and overall patient well-being.

Shared decision-making (SDM) is a collaborative process between clinicians and service users to select treatment, guided by evidence and service user preferences. SDM has clinical, economic, and ethical benefits compared to clinician-led decision-making; yet, implementation remains challenging. An important knowledge gap is the influence of culture on implementation. Cultural impacts on service user decision-making preferences have been documented, but little is known about how culture impacts clinician preferences. This study examined associations between country-level cultural characteristics and decision-making preferences of psychiatrists in routine care settings across Europe.

We analysed data from 751 psychiatrists and trainees in 38 European countries, who completed the Clinical Decision-Making Style–Staff (CDMS-S) scale. Country-level Hofstede cultural dimensions were linked to CDMS-S scores using univariate and multivariate regression models. Mixed-effects models were used to account for country-level clustering and controlling for professional and economic variables.

In univariate analyses, all six dimensions were associated with SDM preferences. However, only three remained significant in mixed-effects models. Higher levels of Indulgence and Individualism were associated with stronger preferences for SDM, while higher Power Distance was associated with more clinician-led decision-making. These associations did not remain significant in fully adjusted multivariate models, suggesting professional and systematic factors mediate cultural influences.

Indulgence, Individualism, and Power Distance are associated with psychiatrists’ decision-making preferences across Europe. Culturally sensitive SDM interventions should address not only clinician attitudes but also healthcare structures and patient expectations. Findings offer an empirical foundation for tailoring SDM training and policy to diverse cultural contexts within European psychiatry.

The significant heterogeneity among individuals who die by suicide complicates prevention, suggesting that a “one-size-fits-all” approach is insufficient. It is crucial to identify distinct subgroups for targeted strategies. This study aims to characterize suicide profiles based on trait impulsivity and related factors.

Data from the FRieNDS project (Factores de Riesgo en Defunciones por Suicidio – Risk Factors in Suicide Deaths), a psychological autopsy study of 408 suicide deaths, were used. After determining the optimal number of clusters via stability analysis through agglomerative nesting, a final cluster analysis was performed on 391 valid suicide deaths (defined as cases with no missing data on the variables used for clustering) using k-means on a lower-dimensional representation of the data encoded by an autoencoder. Key clustering variables included sex, impulsivity (Barratt Impulsivity Scale-11), aggression, intent to die, previous history of suicide attempts, history of substance abuse, psychotic and affective disorders, and the presence of a depressive episode at the time of death.

We identified three clusters: (1) Impulsive-aggressive (29.8%), characterized by high rates of Cluster B disorders, substance abuse, more stressful events, and low lethal intent; (2) depressive prior attempters (24.5%), which comprised mostly women and showed greater behavioural changes before death; and (3) non-impulsive/aggressive (45.7%), a group with no clear psychopathological profile, less healthcare contact, and minimal communicated intent to die, despite having few prior attempts.

Our study identified three suicide clusters with varying impulsivity levels, highlighting the need for tailored interventions and community-level research for better suicide prevention strategies.

Cognitive impairment is central to psychosis and strongly linked to functional outcomes. The Brief Assessment of Cognition (BAC) app is a tablet-based, automated tool for assessing key cognitive domains but has not been validated in Spanish-speaking populations or across illness stages.

A total of 402 participants (117 with first-episode psychosis [FEP], 125 with schizophrenia, and 160 controls) completed the BAC app along with clinical and functional assessments. We evaluated internal consistency, group differences, convergent and discriminant validity, and the effects of sex, age, and education. Normative percentiles were derived from controls.

The BAC app showed good internal consistency across groups (α = 0.76–0.87) and effectively differentiated individuals with psychosis from controls (area under the curve [AUC] = 0.862), with performance declining from controls to FEP to schizophrenia. Discrimination between FEP and schizophrenia was limited (AUC = 0.649). BAC App correlated positively with estimated intelligence quotient and functional capacity, and negatively with symptom severity, particularly in FEP. Performance varied by age, sex, and education, supporting the need for stratified normative data.

The BAC app showed strong reliability and validity for cognitive assessment in Spanish-speaking individuals with psychosis. Its brevity, automated scoring, and normative data support its clinical and research applications for cognitive screening, monitoring, and treatment evaluation.

Measurement-based care (MBC) is widely recommended in psychiatry but remains underutilized in routine clinical settings. The Transdiagnostic Global Impression – Psychopathology (TGI-P) scale was developed to provide a brief yet comprehensive assessment of 10 core transdiagnostic symptom domains. To support more inclusive care and promote patient and caregiver engagement in treatment planning, two new versions of the TGI-P, that is, a patient-rated and a separate informant-rated, were developed, complementing the previously published clinician-rated version.

The patient and informant versions mirror the original clinician-rated TGI-P, assessing the identical 10 domains using a seven-point Likert severity scale, with results displayed via a personalized symptom map. A user satisfaction/feasibility study was conducted with 50 participants (25 patients and 25 caregivers) from the UK and US. After completing the scale, participants provided feedback on its clarity, usability, emotional impact, and comparative utility.

Most participants completed the scale in less than 5 min. Instructions were considered clear, and the format was rated easy to follow. Response options were deemed appropriate by 86% of participants, and the visual output was widely appreciated. While one-third reported mild emotional triggering, overall burden was described as manageable. Approximately, three-quarters of participants rated the TGI-P as equal to or better than other tools they had used.

TGI-P patient and informant versions were developed and, informed by the feasibility study, refined to offer brief, user-friendly tools that support multi-informant assessment as input to MBC. Both versions of the TGI-P, with their graphical output, may support shared understanding and collaborative decision making among clinicians, patients, and caregivers. A validation study of the TGI-P is underway.

Cognitive impairment represents a central component of major depressive disorder (MDD), affecting a large proportion of people living with MDD and showing a consistent negative impact on social, interpersonal, and occupational functioning and subjective quality of life. Cognitive remediation (CR) is a training-based psychosocial intervention targeting cognitive performance and psychosocial functioning that has shown consistent evidence of effectiveness in individuals with schizophrenia and that could provide significant benefits also in people with MDD: this study aimed to assess the effects of a computerized CR intervention in adults living with MDD.

Participants recruited in this single blind multicentric randomized controlled trial were allocated to receive a computerized CR intervention delivered by an active and trained therapist or to an active control condition (computer games – CG). Outcomes were measured with validated instruments by blind assessors and included cognitive performance, depressive symptoms, and psychosocial functioning. Outcomes were assessed using mixed models for repeated measures, considering baseline and end-of-treatment scores.

Hundred and one participants (CR=52 and CG=49) were included and 81 (CR=45 and CG=36) completed the study. CR produced superior results in clinician-rated depressive symptoms (p=0.023, d=042), global clinical severity (p=0.025, d=0.39), subjective depressive symptoms (p=0.005, d=0.45), working memory performance (p=0.004, d=0.34), executive functions/cognitive flexibility (p=0.020, d=0.43), and subjective cognitive impairment (p=0.006, d=0.48).

CR represents an effective intervention in MDD, improving clinical outcomes and cognitive performance in a clinician-rated and in a subjective manner, which should be more consistently implemented in clinical practice and included in MDD treatment recommendations.

The use of artificial intelligence (AI) in psychiatry holds promise for diagnosis, therapy, and the categorization of mental disorders. At the same time, it raises significant theoretical and ethical concerns. The debate appears polarized, with proponents and critics seemingly irreconcilably opposed. On the one hand, AI is heralded as a transformative force poised to revolutionize psychiatric research and practice. On the other hand, it is depicted as a harbinger of dehumanization. To better understand this dichotomy, it is essential to identify and critically examine the underlying arguments. To what extent does the use of AI challenge the theoretical assumptions of psychiatric diagnostics? What implications does it have for patient care, and how does it influence the professional self-concept of psychiatrists?

To explore these questions, we conducted 15 semi-structured interviews with experts from psychiatry, computer science, and philosophy. The findings were analyzed using a structuring qualitative content analysis.

The analysis focuses on the significance of AI for psychiatric diagnosis and care, as well as on its implications for the identity of psychiatry. We identified different lines of argument suggesting that expert views on AI in psychiatry hinge on the types of data considered relevant and on whether core human capacities in diagnosis and treatment are viewed as replicable by AI.

The results provide a mapping of diverse perspectives, offering a basis for more detailed analysis of theoretical and ethical issues of AI in psychiatry, as well as for the adaptation of psychiatric education.

We aimed to identify therapeutic approaches for managing schizophrenia in different phases and clinical situations – the prodromal phase, first-episode psychosis, cognitive and negative symptoms, pregnancy, treatment resistance, and antipsychotic-induced metabolic side effects – while assessing clinicians’ adherence to guidelines.

A cross-sectional online survey was conducted in 2023 as part of the Ambassador project among psychiatrists and trainees from 35 European countries, based on a questionnaire that included six clinical vignettes (cases A–F). Additionally, a review of multiple guidelines/guidance papers was performed.

The final analysis included 454 participants. Our findings revealed a moderate to high level of agreement among European psychiatrists regarding pharmacological treatment preferences for first-episode psychosis and cognitive and negative symptoms, prodromal symptoms and pregnancy, with moderate adherence to clinical guidelines. There was substantial similarity in treatment preferences for antipsychotic-induced metabolic side effects and treatment resistance; however, adherence to guidelines in these areas was only partial. Despite guideline recommendations, non-pharmacological treatments, including psychotherapy and recovery-oriented care, were generally underutilized, except for psychoeducation and lifestyle recommendations, and cognitive behavioural therapy for treatment of the prodromal phase. Contrary to guidelines, cognitive remediation and physical exercise for cognitive symptoms were significantly neglected.

These discrepancies highlight the need for effective implementation strategies to bridge the gap between research evidence, clinical guidelines/guidance papers, and real-world clinical practice. Clinicians’ unique combination of knowledge and experience positions them to shape future guidelines, especially where real-world practice diverges from recommendations, reinforcing the need to integrate both research evidence and clinical consensus.

Suicidal behaviors (SB) in bipolar disorder (BD) are major adverse outcomes that may influence disease progression. While staging models exist for psychiatric disorders, none include suicide. This study aims to stratify suicidal risk in BD, propose a staging model for SB, and assess its clinical utility.

Participants from the FondaMental Advanced Centers of Expertise for Bipolar Disorder (FACE-BD) cohort were categorized into five stages (St) based on SB: St0 (no suicidal ideation [SI]), St1 (SI but no suicide attempt [SA]), St2a (non-severe/violent SA), St2b (severe /violent SA), and St3 (multiple SAs). Stages were analyzed based on demographic, clinical, cognitive, and biological characteristics using logistic regression.

Key differences emerged between stages. St1 showed longer untreated illness and higher lability and lower functioning than St0. St2a was linked to anxiety, substance use disorders, and longer disorder duration, while male gender and lithium bitherapy were protective. St2b exhibited shorter untreated illness and higher childhood trauma (CTQ) scores, with male gender and alcohol use as risk factors. St3 was associated with BD-II, alcohol use, longer disorder duration, and more depressive episodes, but less anxiety. No biochemical or cognitive differences were found across stages. The model was significantly associated with SA occurrence (LRT = 28.74, p < 0.0001).

This staging model for suicidality in BD provides a multifaceted approach to risk stratification and predictive insights, although further refinement is needed.

Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.

T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).

PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).

PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.

Antenatal depression symptom is a global health concern, but the trajectories of antenatal depression symptom vary across different studies. Additionally, the influencing factors and adverse pregnancy outcomes of antenatal depression symptom may differ across heterogeneous subtypes, which requires further exploration.

A prospective cohort study was conducted in Hubei province, China, from July 2022 to September 2023. Pregnant women (<14 weeks) were enrolled and followed up at 16, 21, 28, and 37 gestational weeks, with depressive symptom measured using the Edinburgh Postnatal Depression Scale (EPDS). Latent class growth modeling and logistic regression were used for data analysis.

Of 1034 women enrolled, 725 completed all follow-ups. Four depressive symptom trajectories were identified: no depression group (32.13%), persistent subclinical depression group (42.48%), persistent moderate depression group (19.17%), and persistent high depression group (6.21%). Risk factors of depressive symptom trajectories included low social capital, unplanned pregnancy, primiparity, mental illness history, high perceived stress, and low resilience (p < 0.05). Compared to the no depression group, gestational diabetes mellitus (GDM) risk was 1.90 times higher in the persistent moderate group and 2.59 times higher in the persistent high group; small for gestational age (SGA) risk was 2.42 times higher in the persistent moderate group and 3.98 times higher in the persistent high group.

This study identified four antenatal depressive symptom trajectories. Persistent moderate and high depression groups were linked to GDM and SGA, highlighting the importance of mental health assessments and intervention for pregnant women, especially those with higher depression severity, to prevent adverse outcomes.