Acta Psychiatrica Scandinavica最新文献

Background and aims: Mixed Depression (MxD), characterized by the co-occurrence of depressive and excitatory symptoms, is a prevalent yet often underdiagnosed presentation in bipolar disorders (BD), with significant implications for prognosis and treatment. Childhood trauma is a key environmental risk factor associated with a more severe course of BD, as it influences its onset, progression, and clinical presentation. To date, no studies have specifically investigated the relationship between lifetime childhood trauma and lifetime MxD in individuals with BD. The aim of our study was to address this gap in a large and well-characterized sample of patients with BD type I and type II.

Methods: A total of 376 individuals, 220 euthymic outpatients with BD (MxD = 100, non-MxD = 120) and 156 healthy controls (HC), were enrolled. Childhood trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Lifetime MxD was identified according to the Koukopoulos criteria. The relationship between childhood trauma and MxD was evaluated using two different multivariate models.

Results: The first model (Wilks' Lambda = 0.834, p < 0.001) revealed that BD patients with lifetime MxD reported significantly higher CTQ total scores compared to both non-MxD (p = 0.029) and HC (p < 0.001). When examining childhood trauma subtypes, BD patients with MxD reported significantly higher emotional abuse scores than those without MxD (p < 0.001). Furthermore, compared to HC, the MxD group showed significantly elevated scores in emotional abuse, emotional neglect, and physical abuse (all p < 0.001). The non-MxD group scored higher than HC on physical abuse (p = 0.008) and physical neglect (p < 0.001). Regression analyses confirmed specifically emotional abuse as a significant predictor of lifetime MxD.

Conclusions: The findings demonstrate a strong association between childhood trauma, particularly emotional abuse, and lifetime MxD. These results underscore the significance of childhood trauma as a key predictor of clinical outcomes in BD.

Introduction: This case-control study examined social barriers in adults with ADHD compared to non-neurodivergent adults, focusing on autistic traits, cognitive/affective empathy, theory of mind (ToM), and social anxiety/avoidance.

Methods: A total of 142 adults with ADHD and 104 non-neurodivergent groups were assessed using the following self-report measures: the Adult ADHD Self-Report Scale, the Hospital Anxiety Depression Scale, the Autism Spectrum Quotient, the Empathy Quotient, and the Liebowitz Social Anxiety Scale. ToM was evaluated using the Reading the Mind in the Eyes Test. Additionally, psychiatric interviews were conducted, incorporating diagnostic evaluation via the Structured Clinical Interview for DSM-5 Disorders-Clinician Version, along with collection of sociodemographic and clinical data, and documentation of real-life narratives of social struggles to contextualize and deepen the interpretation of the quantitative findings.

Results: Adults with ADHD exhibited significantly higher levels of autistic traits and social anxiety/avoidance, along with lower cognitive and affective empathy scores, compared to controls, while ToM abilities did not differ significantly between groups. Moreover, regression analyses indicated that challenges in social skills and communication, low cognitive empathy, heightened affective empathy, and difficulties in attention switching accounted for variance in social anxiety/avoidance, independent of confounding sociodemographic and clinical factors, including the presence of co-occurring psychiatric conditions and the severity of ADHD, depression, and anxiety symptoms.

Conclusion: While adults with ADHD exhibit intact basic ToM abilities, challenges in social-cognitive processes are associated with their social barriers. Targeted interventions such as social skills training, executive function coaching, and anxiety management may improve social outcomes and quality of life, as also highlighted by the real-life narratives-although further longitudinal, multi-method research is warranted.

Introduction: Social cognition deficits, such as impaired emotion recognition, theory of mind (ToM), and empathy are central to schizophrenia-spectrum disorders and predict poor functional outcomes. Conventional therapies often lack scalability. Technology-based social cognition training (TBSCT), using computerized, web-based, or virtual reality (VR) formats, offers an accessible and adaptive solution.

Methods: Following PRISMA guidelines (PROSPEROCRD420251021242), databases including Embase, MEDLINE, Cochrane, CINAHL, Web of Science, and PsycArticles were searched up to May 2025. Eligible randomized or quasi-experimental studies involved adults with schizophrenia-spectrum disorders receiving TBSCT targeting emotion recognition, ToM, or empathy. Methodological quality was assessed using Joanna Briggs Institute tools. Random-effects meta-analyses estimated pooled effect sizes (Hedges' g), with subgroup analyses by technology type, clinical setting, and intervention focus.

Results: Twenty-one studies (17 in meta-analysis) met inclusion criteria. TBSCT significantly enhanced facial emotion recognition (FER; g = 0.92, p < 0.001) and showed a small effect on ToM (g = 0.22, p = 0.05); empathy improved pre-post (g = 0.58, p = 0.04). FER benefits were strongest in web-based (g = 1.35), followed by VR (g = 0.87) and computerized programs (g = 0.75). ToM gains were significant only among outpatients. Methodological quality was moderate to high, with mild, transient adverse effects and comparable dropout rates (risk difference = -0.03, p = 0.21).

Conclusion: TBSCT effectively improves social cognition, particularly emotion recognition in schizophrenia-spectrum disorders. The interventions are safe, feasible, and scalable, supporting clinical implementation. Future studies should examine long-term efficacy and optimize engagement across diverse psychiatric populations.

Background: Mood episodes in bipolar disorder (BD) follow a seasonal pattern in approximately 25% of patients. We aimed to examine the associations of specific seasonality patterns in BD with various clinical phenotypes and treatment-related outcomes.

Methods: Patients from the Mayo Clinic Bipolar Disorder Biobank with available seasonality data were included in the study. Among those reporting any seasonality, participants were further categorized into four seasonality groups: fall/winter depression, spring/summer (hypo)mania, biphasic (fall/winter depression with spring/summer (hypo)mania), and equinoctial seasonality (any mood episode occurring in spring or fall). Regression models were used, treating seasonality patterns as the predictor of clinical phenotypes (BD subtype, early onset, history of psychosis, suicide attempt, rapid cycling), lifetime medication exposure (number of unique antidepressants, antipsychotics, and any psychotropics) and treatment response to mood stabilizers (Alda A score).

Results: Among 1702 patients with BD (61.5% female, mean age = 41.43 ± 14.73 years), 44.6% reported seasonal mood episodes. Individuals with any seasonality were more likely to have BD-I (OR = 1.29, p = 0.024), early onset (OR = 1.29, p = 0.026), exposure to higher lifetime number of antipsychotics (IRR = 1.20, p < 0.001) and any psychotropics (IRR = 1.13, p < 0.001). Fall/winter depression was associated with a higher lifetime number of antidepressants (IRR = 1.18, p = 0.021), any psychotropics (IRR = 1.14, p = 0.013), worse response to lithium (β = -0.82, p = 0.029) and all mood stabilizers (β = -0.69, p = 0.014). Spring/summer (hypo)mania showed negative associations with rapid cycling (OR = 0.36, p < 0.001) and lifetime number of antidepressants (IRR = 0.70, p = 0.013). Equinoctial seasonality was linked to a history of psychosis (OR = 1.76, p = 0.004).

Conclusion: Seasonality in BD is associated with distinct clinical features and treatment-related outcomes. Specific seasonality patterns, particularly fall/winter depression, may reflect a more complex and difficult-to-treat illness course. These findings highlight the need for research to better characterize seasonality subtypes beyond a binary "seasonal" vs. "non-seasonal" classification and to explore how these patterns influence the illness course and management of BD.