Frontiers in Psychiatry最新文献

Background: There are currently no published studies evaluating antipsychotic prescribing patterns in state hospital settings in the United States. This data is important to review since state hospitals involuntarily commit patients with serious mental illness (SMI) to receive treatment with antipsychotic medications, which are associated with a multitude of dose-dependent adverse effects.

Methods: This cross-sectional study describes antipsychotic prescribing patterns at a single state psychiatric hospital with predominantly forensic admissions. Data was collected via chart review at a single point in time, including demographic data and clinical characteristics such as admission type, neuropsychiatric diagnoses, length of stay, antipsychotic selection and dosing, and total number of scheduled antipsychotics. If the total daily dose of the scheduled antipsychotic was greater than the recommended typical maximum dose, it was considered 'high-dose' antipsychotic use.

Results: Among 212 state hospital admissions, nearly two-thirds of patients were prescribed ≥ 1 antipsychotic at either the recommended typical maximum dose (N=76; 35.8%) or above the typical maximum dose (N=62; 29.2%). Several patients were prescribed antipsychotic polypharmacy (APP) (two scheduled antipsychotics [N = 76; 35.8%]; three scheduled antipsychotics [N = 13; 6.1%]). About one-third of patients were prescribed olanzapine (N = 76; 35.8%), and about a quarter of patients were prescribed clozapine (N = 51; 24.1%) and/or paliperidone (including Invega Sustenna) (N = 49; 23.1%). One-fifth of patients were prescribed a first-generation antipsychotic (N = 43; 20.3%). Nearly one-third of patients were prescribed a long-acting injectable antipsychotic (LAIA) (N = 69; 32.5%).

Conclusion: High-dose antipsychotic use and APP was common in this U.S. state psychiatric hospital. Larger, multicenter studies are needed to determine how antipsychotic prescribing patterns vary between U.S. state hospitals. Testing the development and implementation of antipsychotic stewardship programs in state hospital settings is recommended to establish best practices for monitoring antipsychotic use patterns and associated health outcomes.

[This corrects the article DOI: 10.3389/fpsyt.2025.1710696.].

Large language models (LLMs) have shown promise in generating personality-tailored persuasive messages, yet their effectiveness remains inconsistent across contexts. This research systematically investigated how the characteristics of recommended products or actions shapes the efficacy of LLM- generated personality-tailored persuasion through three experimental studies (N = 618). Study 1 revealed that personality-matching effects were limited and inconsistent when the core features of the recommended product or action were not controlled. Qualitative analysis suggested that uncontrolled semantic variation across personality framings obscured persuasive effects. Study 2 demonstrated that explicitly anchoring messages to core product or action features-while allowing stylistic variation-produced robust personality-matching effects across multiple traits and topics. Study 3 extended findings across diverse domains (health, consumer products, entertainment, prosocial behavior) and confirmed that topic-specific stereotypes systematically influence message effectiveness independent of recipient personality. Messages aligning with widely shared topic expectations (e.g., high-Extraversion framing for music festivals, high-Agreeableness framing for donations) were preferred across audiences regardless of individual traits. These findings reveal two critical boundary conditions for LLM-based personalized persuasion: stabilizing core content through semantic anchoring facilitates the emergence of personality-matching effects, and topic stereotypes create baseline preferences that may amplify or attenuate personalization benefits. Practically, effective implementation requires anchoring core content while modulating style, and evaluating topic stereotypes before applying trait customization. This work clarifies when and how generative AI can reliably enhance persuasive communication across mental health, public health, and consumer domains. Study 3 extended the findings across diverse domains (health, consumer products, entertainment, and prosocial behavior) and suggested a consistent role of topic-specific stereotypes in shaping message effectiveness, above and beyond recipient personality.

Background: Patients with polycystic ovary syndrome (PCOS) often experience anxiety, depression, and sleep problems in addition to endocrine and metabolic abnormalities, which may adversely affect their quality of life and disease progression. However, research on the co-occurrence patterns and interconnections among these psychological symptoms in PCOS remains limited. This study applied network analysis to explore the relationships among anxiety, depression, and sleep problems in women with PCOS, aiming to identify key symptom nodes and provide evidence for targeted psychological interventions.

Methods: This retrospective study included 1,068 patients with PCOS. Anxiety, depression, and sleep problems were assessed using the Generalized Anxiety Disorder Scale (GAD-7), Patient Health Questionnaire (PHQ-9), and Pittsburgh Sleep Quality Index (PSQI). Symptom networks were estimated using the Least Absolute Shrinkage and Selection Operator (LASSO) and Extended Bayesian Information Criterion (EBIC) in R software. Central and bridge symptoms were identified using expected influence (EI) and bridge expected influence (BEI). Network stability and accuracy were evaluated through bootstrap methods. The Network Comparison Test (NCT) was applied to analyze network differences across subgroups that vary by marital status and weight status.

Results: Network analysis revealed that the strongest edge was the connection between "Daytime dysfunction" and "Low energy" (PSQI7-PHQ4), spanning different symptom communities. Another edge of high intensity was observed between "Worthlessness" and "Suicidal ideation" (PHQ6-PHQ9). "Trouble relaxing" (GAD4) and "Sad mood" (PHQ2) exhibited the highest EI values within the network. Meanwhile, "Daytime dysfunction" (PSQI7) and "Low energy" (PHQ4) showed the highest BEI values. Network comparison analysis revealed no significant differences across marital and weight status subgroups.

Conclusion: This study is the first to explore the symptom interrelationships among anxiety, depression, and sleep problems in PCOS patients. Targeting these central symptoms (e.g., trouble relaxing, sad mood) and bridging symptoms (e.g., daytime dysfunction, low energy) may more effectively alleviate patients' overall psychological issues and potentially interrupt the spread of comorbid psychiatric conditions. The findings of this study can inform the development of personalized mental health management strategies for patients with PCOS.

Cannabis is commonly used among reproductive-aged individuals, and prenatal cannabis use (PCU) has increased dramatically in recent years, despite guidance warning of possible adverse outcomes. Physical activity interventions have been shown to reduce substance use in other populations. Building on this, we examined the feasibility and acceptability of a 10-week prenatal walking intervention in a small trial with 16 pregnant individuals who were seeking to reduce PCU. Participants wore a Fitbit to track activity and attended 6 sessions designed to promote gradual increases in daily step count. Indicators of feasibility, acceptability and safety were assessed, as were changes in cannabis use, physical activity, depression and anxiety. Results suggest the intervention was feasible and acceptable; most women (88%) completed the intervention, attending on average 5.8 of 6 sessions, with strong compliance to Fitbit wear. No adverse events were reported. Findings provide preliminary evidence for intervention efficacy: 62.5 percent of participants endorsed PCU at baseline vs. 16.6% by the 36 week assessment; in addition, by endpoint, physical activity increased from an average daily stepcount of 5738 at baseline to 6562, and anxiety and depression were significantly lower. Participants reported high satisfaction with the intervention on a satisfaction survey and in an interview. Participants voiced appreciation for the accountability provided by the intervention, and support for making gradual, achievable changes in behavior. Though preliminary, findings suggest a physical activity intervention could be a valuable strategy to help reduce PCU. Further research is needed to evaluate the intervention in a more rigorous controlled trial.

Children entering foster care (FC), adoption, or child welfare services (CWS) frequently experience early adversity, placing them at increased risk across multiple developmental domains. A structured narrative search (2020-October 2025) identified 61 eligible studies, including 22 high-quality longitudinal, administrative, and review-based 'core' studies. Findings were synthesised across five predefined domains to provide comparative evidence on placement stability, psychological and behavioural health, educational attainment, physical and developmental health, and social relationships. Findings indicate that FC is most consistently associated with instability and cumulative disadvantage, including high rates of mental health problems, disrupted education, unmet health needs, and relational difficulties. Adoption generally provides greater permanence and more favourable outcomes, particularly when it occurs early, though adoption at later ages or following institutional care is often linked to enduring emotional, behavioural, and neurodevelopmental difficulties. Children who remain with their families under CWS support show highly variable trajectories, with positive outcomes when interventions are timely and sustained, but persistent difficulties when family adversity continues and systemic support is lacking. Across pathways, placement stability-conceptualised as both an outcome domain and a protective process-consistently emerges, alongside secure relationships, trauma-informed approaches, and coordinated support, as a critical factor safeguarding children's developmental outcomes. However, the evidence base remains limited, with few longitudinal, intervention-driven, and culturally inclusive studies. Addressing these gaps is essential to advance policy and practice reforms that promote more responsive and coordinated systems of care, enabling children to build resilience and achieve long-term wellbeing.

This article discusses the important issue of the need for a stable definition of intellectual disability in order to allow comparisons by place and over time such as in the monitoring of this population's health needs and utilization. The aim of the new Australian National Centre for Intellectual Disability Health, established in 2023, is to ensure that all Australian children and adults with intellectual disability receive high-quality healthcare that meets their needs. Monitoring changes in this regard requires accurate identification of the number of people with intellectual disability within a population which itself is inherently dependent on how intellectual disability is defined. We have used a definition which is relatively easy to operationalize through different sources i.e. a full-scale IQ of less than 70, a condition known to be consistent with intellectual disability or documentation of intellectual disability in medical records; through education a level of intellectual disability defined as either mild/moderate or greater, and through the National Disability Insurance Scheme an International Classification of Diseases (ICD-10-CM) diagnostic code associated with intellectual disability. In contrast the definition required by Inclusion Australia "a lifelong condition that affects a person's intellectual skills and their behavior in different situations" is much more difficult to operationalize. We discuss this challenge within the context of historical changes and the range of sources possibly able to provide this information today. We present two case studies from different Australian states and conclude with some suggestions for a multi-source approach using data linkage.

Introduction: There are currently limited autopsy-based studies on sudden unexplained death in patients with schizophrenia (SDU-SCZ).

Methods: We summarized the demographic data, autopsy characteristics, and postmortem antipsychotics result for a total of 152 SUD-SCZ decedents, encompassing three cases from our forensic center and 149 literature-reported autopsy cases.

Results: The SUD individuals were found in adults at all ages, ranging from 19-86 years old, with a male-to-female ratio being 94: 58. A total of 106 patients (69.7%, 106/152) were documented to be overweight or obese. Autopsy findings were available in 77 of the 152 cases. The most frequent postmortem pathology was cardiac (46.8%, 36/77), of which unclassified cardiomegaly, focal myocardial fibrosis, and mild coronary atherosclerosis were the most common manifestations, documented in 11 (14.3%), 8 (10.4%), and 5 cases (6.5%), respectively. Data on postmortem antipsychotics were available in 74 of the 152 cases, of which 65 (87.8%, 65/74) were tested positive of any antipsychotic drug, all at therapeutic levels. Olanzapine and clozapine were the most commonly prescribed antipsychotic drugs, documented in 18 cases (24.3%, 18/74) and 16 cases (21.6%, 16/74), respectively. In these SUD-SCZ individuals, the exact cause of death remained unexplained after comprehensive autopsy examination and postmortem antipsychotics analysis.

Discussion: Linking premorbid conditions (e.g. overweight or obese) to antipsychotics medication histories and postmortem myocardial pathologies would facilitate a more accurate determination and interpretation of the cause of death. Forensic investigation is useful for developing preventive strategies for this vulnerable population.

Background: Emerging evidence supports the role of immune-mediated neuroinflammatory processes and disrupted sleep patterns in elevating susceptibility to major depressive disorder (MDD). Sleep disturbances, a hallmark clinical feature of MDD, have further been linked to changes in lymphocyte profiles. Nevertheless, the potential relationship between sleep disturbance and lymphocyte subpopulations characteristic in patients with MDD remains underexplored.

Methods: In this study, flow cytometry was used to measure the proportion of peripheral blood CD4⁺ T-helper cells in 63 patients with MDD and 60 age- and sex-matched healthy controls (HCs). The relationship between self-reported sleep disturbances and the proportion of these cells was evaluated using Pearson's correlation coefficient.

Results: Baseline scores on the Hamilton Depression Rating Scale (HAMD) and Self-Rating Depression Scale (SDS) in patients with MDD were significantly higher than those in HCs. Regardless of antidepressant medication use, patients with MDD exhibited elevated proportions of CD4⁺ regulatory T cells (Tregs), IFN-γ⁺-Tregs, IL-4⁺-Tregs and Th1 (IFN-γ⁺-CD4⁺ T) cells compared to HCs. Furthermore, the Pittsburgh Sleep Quality Index (PSQI) scores in patients with MDD showed a positive correlation with CD4⁺ T cell frequency. Notably, MDD patients with self-reported sleep disturbance had a higher CD4⁺ T cell percentage than those without such disturbance.

Conclusions: Our findings demonstrate that patients with MDD comorbid with sleep disturbances exhibit elevated proportions of CD4⁺ T cells compared to those without such disturbance. These results suggest that targeted interventions addressing sleep disruption may contribute to restoring CD4⁺ T cell homeostasis, potentially offering a novel therapeutic strategy for MDD management.

Background: Emergency rooms in general hospitals receive patients experiencing acute crises, exacerbations of chronic mental disorders, and psychiatric emergencies. This study aims to describe the main characteristics and clinical symptoms of the sample of mental health patients across main diagnoses, and to identify the risk factors of suicide, as well as of hetero-aggression. This study aims to investigate the associations between clinical symptoms, risk factors for suicide attempts and hetero aggression, and psychiatric diagnoses in patients with mental disorders and addictions.

Method: This is a quantitative, cross-sectional, and analytical study. The Emergency Screener for Psychiatry instrument was applied to screen patients in an Emergency Care Unit in Primary Health Care and a Mental Health Unit of a University Hospital in Brazil. A comparative analysis of the main characteristics of patients between the sites was conducted. Logistic models were used to identify risk factors of suicide attempts and hetero aggression.

Results: The scales of depression severity (OR:2.69), risk of harm to others (OR:3.31), and social withdrawal (OR:4.27) were identified as risk factors for suicide attempts. A protective factor was the item reporting if family/friends or professionals are concerned about the patient's self-harm (OR:0.34). For hetero-aggression risk, using the harm to others scale, only the mania scale (OR:4.31) and history of four or more previous hospitalizations (OR:2.80) were significant. In both models, no significant associations were found for the type of diagnosis or the patient's admission site.

Conclusion: The Emergency Screener for Psychiatry proved to be a useful screening instrument to identify risk factors of suicide attempts and hetero aggression of patients in emergencies settings and general hospitals.