A network analysis of personality traits, mentalizing, and psychological health in Chinese college students.

Authors

Langbin Zhou, Xiaoyu Huang

Published in

Scientific reports. Jul 03, 2026. Epub Jul 03, 2026.

Abstract

The rising prevalence of anxiety and depression among college students constitutes a significant public mental health challenge. While personality traits (e.g., neuroticism) and impairments in mentalizing capacity are recognized as key vulnerability factors, their complex interplay in contributing to psychological distress remains inadequately elucidated. Network analysis offers a novel paradigm for visualizing this intricate system as an interconnected web of symptoms and traits. This study employed a network approach to investigate the interrelationships among personality traits, mentalizing, and psychological distress in a large sample of Chinese college students. The primary aims were to identify the most central (influential) elements within the network and, crucially, to detect bridge nodes that connect different psychological domains, thereby pinpointing potential targets for precise intervention. A cross-sectional survey was conducted among 5,140 Chinese undergraduates. Assessments included the Symptom Checklist-90 (SCL-90), Mentalizing Questionnaire (MZQ), Reflective Functioning Questionnaire-8 (RFQ-8), Eysenck Personality Questionnaire (EPQ), and University Personality Inventory (UPI). Regularized partial correlation networks were estimated using the LASSO-EBIC method (γ = 0.5), which inherently controls for multiple comparisons through regularization. Node centrality was indexed by expected influence (EI), and bridge centrality by bridge expected influence (bEI). Non-parametric bootstrap tests with 20,000 resamples were used to evaluate network accuracy and stability. Depressive symptoms (SCL-3) and neuroticism (EPQ-2) showed the highest centrality. Neuroticism (EPQ-2) was the strongest bridge node (bEI = 0.93), with the strongest edge in the network linking to impaired mentalizing (MZQ-1; weight = 0.474). Mean node predictability was 0.51. Network stability was excellent (CS coefficient = 0.75). Mentalizing constructs were represented by MZQ subscales, which also reflect the conceptual content of the RFQ-8: hypermentalizing (MZQ-2) corresponds to RFQ-C (certainty), and hypomentalizing (MZQ-3) corresponds to RFQ-U (uncertainty). Findings highlight robust concurrent associations between neuroticism, mentalizing impairment, and psychological distress in Chinese college students. Neuroticism is strongly associated with distress partly through its link to reduced mentalizing capacity. These cross-sectional results provide a framework for targeted preventive strategies in student populations, although causal inferences cannot be drawn from this observational design.

PMID:
42399705
Bibliographic data and abstract were imported from PubMed on 04 Jul 2026.

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