Journal of psychopathology and clinical science最新文献

Recent work by Zarubin et al. (2025) suggests that subtle differences in early parent-child interaction-such as responsiveness, shared emotion, and eye contact-predict later psychotic-like experiences at the transition to adolescence. In this Commentary, I argue that these early social patterns reflect not static "deficits" but rather disruptions in interactive coordination: the real-time give-and-take through which children learn to predict and align with others. Within a broader multifactorial neurodevelopmental framework, psychosis risk may become evident when the developing rhythm of connection between a child and a caregiver becomes mistuned-long before any formal symptoms appear. Viewing parent-child synchrony as a process that can be strengthened rather than as a fixed trait opens translational opportunities for brief, relationship-based interventions that enhance moment-to-moment alignment in interactions. Recognizing this rhythm as both a marker and a potential mechanism of vulnerability may help move the field toward a developmental, prevention-oriented model of psychosis-one that begins not in the clinic but in the everyday exchanges between a child and a caregiver. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

This article discusses chronic suicidal ideation. Millions of people think about ending their own life each year. Suicidal ideation has often been studied in relation to suicidal behavior, with the goal of understanding what facets and features of suicidal ideation predict the risk of future engagement in suicidal behavior. Many people think about suicide for years, however, and never engage in suicidal behavior. In this viewpoint, the authors argue this phenomenon of suicidal ideation that persists over time has been overlooked and is a concern in its own right, separate from suicidal behaviors or acute, transient suicidal thoughts. First, the authors highlight how chronic suicidal ideation is a problem in and of itself-absent risk for death. Next, they highlight what is currently unknown about chronic suicidal ideation, specifically the how and why this phenomena exists and persists. Finally, they provide specific recommendations for the future study of chronic suicidal ideation. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Although depression is heterogeneous in symptoms, few studies have asked whether cognitive features central to its etiology show similar heterogeneity. We addressed this question in a treatment-seeking sample of adults with at least moderate depression (N = 232) by assessing three biases: (a) attentional dwell time on sad stimuli, (b) negative interpretation of ambiguous stimuli, and (c) brooding rumination. The k-means clustering revealed distinct subgroups for each cognitive feature when considered separately. Latent profile analysis combining the three indicators identified two clear profiles: a "high-bias" group (38%) with above-average scores on all three measures-especially interpretation bias-and a "low-bias" group (62%) with below-average scores. Elastic-net regression showed membership in the high-bias profile was associated with greater anhedonia, feelings of inadequacy, generalized anxiety, lower educational attainment, and unemployment. These findings demonstrate that negative cognitive biases are not uniformly present among depressed individuals, highlighting the value of tailoring interventions to bias-defined subgroups. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Advances in artificial intelligence (AI) hold promise for clarifying personality disorder (PD) models, research methodology, understanding, and clinical treatment. This study models personality and personality pathology using natural language. A representative community sample of N = 1,409 older adults from St. Louis (33% Black, 65% White, and 2% other) completed life narrative interviews lasting on average 20 min. Language from the interviews was then used to train and test language-based personality models on scores from the NEO-Personality Inventory-Revised and the Structured Interview for DSM-IV Personality. Criteria measures were used for multimethod construct validation of the language models including self-report measures of physical functioning and depressive symptoms and informant-report measures of personality, general health status, and social functioning. Language models were developed using fine-tuning of the parameters of the RoBERTa language model, BERTopic topic modeling, and Linguistic Inquiry and Word Count. Fine-tuned RoBERTa models predicted personality scores in testing data above r = .40, approaching what is considered a large effect size for convergent validity tests between two self-reports of the same construct. Life narrative language was more readily mapped onto the five-factor model trait domains than onto DSM PD categories, aside from moderate support for borderline pathology. The language-based five-factor model scores were supported by multimethod criteria correlations including informant-report personality scores in the testing data. Findings demonstrate the potential promise of language-based AI to refine conceptual frameworks of PD and provide automatic personality assessment and prediction in research and clinical practice. (PsycInfo Database Record (c) 2025 APA, all rights reserved).