Stigma-related beliefs toward mental illness may change during psychiatric clinical exposure, but individual differences in this process remain insufficiently understood. This single-center observational pre–post study examined observed changes in mental illness-related beliefs among 185 medical interns who completed an approximately 30-day psychiatry clerkship between May 2025 and May 2026, with perceived dangerousness defined as the primary outcome. Beliefs were assessed before and after the exposure period using the Beliefs Toward Mental Illness Scale. Associations between baseline cognitive–metacognitive characteristics and observed change were evaluated using paired comparisons, linear mixed-effects models, and sensitivity analyses. Dangerousness scores decreased by the end of the exposure period, mean change = −2.66, 95% CI [−3.48, −1.81], q < 0.001, d_z = −0.47. Smaller decreases were observed in Helplessness and Deterioration in Interpersonal Relationships, whereas no significant change was found in the two-item Shame subscale. Higher baseline ruminative thought style was associated with a more limited decrease in dangerousness scores; B = 1.70, SE = 0.55, 95% CI [0.62, 2.77], q = 0.023. Although this association was consistent across sensitivity analyses, its incremental contribution was small (ΔR²_marginal = 0.017; f² = 0.018 in the focused model). The finding should therefore be interpreted as a quantitatively modest association with observed belief change, not as a clinically meaningful predictor. Because the study included no concurrent control group or experimental manipulation and was conducted at one center, it does not establish a causal clerkship effect or support educational screening based on ruminative thought style.

Aim: This study aimed to examine regional cortical and subcortical brain volume differences in children with autism spectrum disorder (ASD). By comparing the ASD group with healthy individuals, the effects of the disorder on brain morphology will be evaluated. We hypothesized that children with ASD would exhibit increased volumes in selected cortical and subcortical brain regions.Material and Methods: The brain magnetic resonance images (MRI) of 33 children with ASD and 33 healthy controls were analyzed and compared. The VolBrain automated segmentation method was used to process the MRI and detect volumetric differences. The resulting measurements were statistically analyzed to identify significant volumetric differences between the ASD and control groups.Results: The findings of this study revealed that children with ASD exhibited significantly larger volumes in the cerebrum, white matter, grey matter, frontal lobe, postcentral gyrus, amygdala, thalamus, putamen, and hippocampus compared to healthy controls (p < 0.05). However, no significant differences were observed between the groups in the volumes of the precentral gyrus, parietal lobe, and caudate nucleus (p > 0.05). Conclusion: The present findings indicate that autism spectrum disorder (ASD) is associated with widespread volumetric enlargement across both cortical and subcortical brain regions. These results contribute to a clearer characterization of the neuroanatomical profile of ASD and underscore the value of automated volumetric neuroimaging approaches for detecting disorder-related structural brain patterns.

Background/Objectives: Child and adolescent psychiatry consultation-liaison services address heterogeneous management demands, while referral pathways and service organization may change over time. We examined whether information available before psychiatric assessment could predict six subsequent documented clinical management decisions and whether predictive performance remained transportable to a later service period. Methods: This retrospective prediction study included 656 unique patients aged 1–18 years. Six management domains coded from psychiatric consultation-response documentation were modeled using referral-note text, age, sex, and clinically harmonized referring department. L2-regularized logistic regression models incorporated term frequency–inverse document frequency text features. Internal performance was assessed using grouped repeated cross-validation. Temporal transportability was evaluated by applying models developed on 2013–2019 records (n = 447) to the 2022–2025 cohort (n = 209) without retraining or recalibration. The area under the precision–recall curve (AUPRC) was the primary metric. Results: Full-cohort cross-validated AUPRC ranged from 0.282 to 0.721. Temporal AUPRC ranged from 0.136 for psychosocial management to 0.663 for medication management decision; corresponding values were 0.282 for additional assessment, 0.586 for follow-up/reassessment, 0.415 for safety/disposition, and 0.575 for liaison/medical integration. Temporal discrimination was particularly weak for psychosocial management (AUROC = 0.532) and remained limited for additional assessment (AUROC = 0.587). Referring-department composition and several outcome prevalences changed substantially between periods. Although referral-note text contributed within the fitted models, its incremental temporal value over structured predictors was not established after false discovery rate correction; confidence intervals remained compatible with modest benefit or harm. Conclusions: Pre-assessment information contained management-domain-specific predictive signal for subsequent documented clinical management decisions, but transportability varied across clinical targets and service periods. These findings should be interpreted as evidence about temporal transportability rather than clinical implementation readiness. The results do not support automated clinical decision-making. Multicenter, preferably prospective, validation and evaluation of clinical utility and workflow impact are required before implementation.