Current Psychiatry Reports最新文献

Purpose of review: A number of sex differences have been reported in people with schizophrenia in terms of epidemiological data and clinical and social needs.

Recent findings: This review examines recent evidence on sex differences in clinical outcomes, medical comorbidities and social risk factors in schizophrenia. Sex-specific personality traits and the effects of childhood maltreatment are relevant in schizophrenia. Insomnia is more common in women and is associated with depressive symptoms and cognitive impairment. Differences in antipsychotic dose requirements, risk of hospitalization and adverse events between men and women with schizophrenia have been reported and vary with age. The association between negative symptoms and 10-year cardiovascular risk are more common in men. Hyperglycaemia and dyslipidaemia are potential targets for sex stratification in the treatment of schizophrenia. Living without a spouse is associated with an increased risk of schizophrenia, which is higher in men than in women. Loneliness and social isolation are positively associated with clinical symptoms in men. The mental, physical and social needs of men and women with schizophrenia differ. This should be recognised when planning sex-specific programmes for psychosis.

Purpose: Eating disorders and subthreshold symptoms during pregnancy and postpartum pose significant risks for maternal and child health. This review synthesizes recent findings (2020-2025) on epidemiology, assessment, and intervention to inform clinical care and research.

Recent findings: Eating disorders affect approximately 4% of pregnant individuals and over 9% of postpartum individuals. Subthreshold symptoms, particularly loss of control eating, are highly prevalent across both periods. Risk factors include maladaptive attitudes and worries related to pregnancy and motherhood and body comparison. Assessment tools adapted for pregnancy show promise, but no validated postpartum measures exist. Intervention research is sparse; two ongoing trials-an acceptance-based food craving intervention to reduce loss of control eating and an adapted Body Project to improve body image and prevent disordered eating-illustrate efforts to tailor evidence-based approaches for pregnancy. Pregnancy and postpartum present opportunities for prevention and treatment of eating disorders, but additional research is needed.

Purpose of review: This review examines the role of artificial intelligence (AI) in psychiatry in the past 5 years across four domains: screening; outcome prediction; risk and relapse prediction; and psychotherapy.

Recent findings: Machine learning models applied to questionnaires, electronic health records, neuroimaging, and digital phenotyping data demonstrate promising results for predicting symptom trajectories, relapse risk and treatment response, but external and clinical validation is rare. Randomized controlled trials provide some evidence for AI-enabled clinical decision support, but only preliminary evidence for chatbot-delivered psychotherapy. Some preliminary evidence for chatbots in screening exists. Ethical risks, including automation bias, model opacity and socioemotional harms, complicate integration into practice. Current evidence only supports AI's role as a complement to clinical expertise. To realize safe integration of AI into clinical practice, future work should focus on prospective, multi-site trials with active comparators, external validation across diverse populations, transparent reporting, and governance frameworks that prioritize explainability, oversight, and equity.

Purpose of review: This review examines recent evidence for the effectiveness of telehealth in treating Post-Traumatic Stress Disorder (PTSD), Major Depressive Disorder (MDD), alcohol use disorder, and insomnia in military veterans and active-duty service members (ADSMs).

Recent findings: Recent randomized controlled trials and prospective cohort studies provide strong evidence that synchronous video-teleconference based therapy is effective for PTSD, MDD, and insomnia in this population. There is growing evidence for the effectiveness of internet-based self-guided therapy, particularly when combined with coaching support provided by telemedicine, for symptoms of PTSD, MDD, and insomnia. The effectiveness of telehealth in the treatment of alcohol use disorders is less well-supported, as is the effectiveness of mobile applications. These findings are supported by the team's analysis of the literature as well as an analysis provided by an Artificial Intelligence (AI) platform. The current evidence supports the use of synchronous video-teleconference and internet-based self-guided therapy with coaching support in the treatment of several common diagnoses in the military veteran and ADSM populations. Other modalities of telehealth require further research.

Human and animal rights: This article does not contain any studies with human or animal subjects performed by any of the authors.

Purpose of review: The purpose of this review is to synthesize recent advancements over the last four years in eating disorder prevention and early intervention research.

Recent findings: Our comprehensive review identified over 140 prevention and early intervention articles published from 2021 to 2024, with themes focused on specific intervention strategies or targets (e.g., dissonance, mindfulness, weight stigma), targeted populations (e.g., adolescents/school-based programs, athletes), digital-based interventions, system-level interventions, and early interventions. The eating disorder prevention and early intervention literature has expanded over the last several years. Based on the current state of the evidence, we outline future directions to help inform the field and continue movement towards accessible and inclusive eating disorder prevention.

Purpose: This critical review examines literature published between January 2020 and January 2025, focusing on overlapping pain-related factors during and after childbirth (e.g., pain experiences and management). These factors may increase vulnerability to postpartum depression, especially among racial and ethnic minorities.

Recent findings: The findings from the 23 studies reviewed indicate that several factors contribute to peripartum pain experienced by individuals giving birth. Factors influencing the birthing person's pain experiences include their mental health during pregnancy (such as depression and anxiety), delivery method (especially cesarean), pain management practices, discrimination toward racial and ethnic minorities, and overall neglect of pain. Additionally, healthcare providers' beliefs about pain management play a role in postpartum pain experiences. Individuals with a history of depression or anxiety often experience more severe postpartum pain. Mode of delivery is an important factor, as cesarean deliveries are associated with more severe pain than vaginal deliveries. However, intrapartum experiences and pain management significantly influence pain ratings. Analgesics during and after labor may buffer postpartum pain, but not always. Additionally, pain relief medications for patients with opioid use disorders can impact postpartum pain management. While healthcare providers rely on clinical assessments and patient-centered approaches to inform postpartum pain management, data from racial and ethnic minorities revealed that healthcare professionals often fail to recognize these patients' pain. This underscores the disparities in perspectives and experiences among patients. Post-childbirth pain experiences and their management strategies may increase the risk of postpartum depression, highlighting the necessity for researchers and practitioners to consider them.

Purpose of review: To investigate the prevalence of self-reported diagnoses of ADHD among U.S. post-secondary students.

Recent findings: We identified fifteen empirical studies published in academic journals between 2008 and 2023 that reported ADHD prevalence estimates. These studies had variability in samples and methods and produced a wide range of prevalence estimates-3.4% to 11.2%-and an overall prevalence estimate of 9.1%. We supplemented the academic literature with data from two multi-institutional, annual surveys-the Healthy Minds Study and National College Health Assessment (NCHA III/IIIb). Their prevalence estimates for the 2024-2025 academic year were 14% and 15%, respectively, which reflected significant increases from their 2019-2020 estimates of 4% and 8%. Estimates for the prevalence of ADHD diagnoses vary by data source and method. Multi-institutional, annual surveys suggest an increase in prevalence in recent years. These data might warrant the strengthening of ADHD services provided by campus clinics.

Purpose of review: We review the published literature on children's coping in disasters, focusing on disaster type, cultural and socio-demographic influences, and the methods used to assess coping.

Recent findings: Disasters affect children and youth in diverse ways, shaped by both disaster type and broader contextual factors. Research has grown considerably over the past two decades, offering insights into adaptive and maladaptive coping in disaster contexts. However, the field remains constrained by several limitations: a lack of consensus on how coping is conceptualized in children, limited standardized measures specific to disaster contexts, and few culturally adapted tools that capture diverse coping processes across settings. A deeper understanding of children's disaster coping can be achieved by addressing gaps in definitions and tools through clearer conceptualization, culturally grounded measures, and longitudinal, multi-systems approaches. Addressing these gaps will help strengthen supports for children facing the increasing frequency and severity of disasters.

Purpose of review: Changes in youth mental health during the pandemic have been well documented globally, but research on how mental health changed when schools returned to in-person learning is just emerging. This review summarizes the available global research on child and youth mental health following school reopening for in-person learning.

Recent findings: Results varied by the mental health indicator being assessed and by subgroups of children and youth, with age-related differences, and possible gender-related influences. Some modifiable risk and protective factors examined included time spent on homework; internet and social media use; physical activity; communication/conflict with others; optimism; social relationships with family, teacher and peers; parental mental health; and inconsistent discipline. Some youth fared better when schools reopened in-person, but for others mental health challenges persisted. Mental health services shifted during the height of the pandemic, and some supports are no longer available. Continued monitoring is needed to help with recovery and resilience.

Purpose of review: Mood in bipolar disorder (BP) fluctuates in complex and unpredictable ways that resist simple explanation. To capture this complexity, researchers have turned to modeling mood dynamics. This review organizes the recent literature around three key questions: How can modeling help phenotype BP? Can models accurately predict future mood? And can modeling clarify mechanisms underlying mood instability?

Recent findings: Models of mood dynamics carry clinically relevant information beyond standard measures, differentiating BP from other disorders and reflecting treatment response and impairment. Yet their ability to forecast mood tends to deteriorate within days, raising the possibility that fleeting predictability may be intrinsic to BP, not simply a technical limitation. Mood also appears to be best represented by two or more continuous latent dimensions, with states like mania and depression appearing as loosely defined regions. However, how mood unfolds over time remains poorly understood, particularly the relative influence of internal dynamics versus external triggers. Looking ahead, two priorities stand out: applying these models in real time to support clinical and research decisions, and validating them systematically through standardized forecasting tasks and shared longitudinal datasets integrating mood and physiological data. Together, these steps can help turn modeling into a practical tool for understanding and managing mood in BP.