Preliminary network analysis of suicide risk and psychosocial factors in Chinese adults and older adults with depression: a cross-sectional study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: The study aims to elucidate the influence of multiple psychosocial determinants on suicidal ideation in late-life depression and to uncover their underlying network of interactions. Methods: This study analyzed patients with depressive disorders. A total of 2,052 patients were included, comprising 1,296 adult group and 756 older adults group. Clinical assessments were conducted using HAMD-17, HAMA, SCL-90, PSQI and NGASR. Data analysis and visualization were performed using R software. The network structure among psychological variables was assessed, and the variable nodes that play a key role in the network were identified. Independent network modeling was conducted separately for the adult group and older adults group, so as to further examine the properties and differences of the network structure between two groups. Results: Depression emerged as the strongest predictor of suicidal ideation in adults, showing the highest degree of association. Anxiety demonstrated a dual role. Among older adults, the coupling between variables was stronger, particularly the combined effects of depression and sleep disturbances. The PSQI node exhibited more pronounced bridging properties in the older adults group, serving as the most significant mediator across the two network structures. The anxiety-depression pathway displayed greater connectivity in the older adults group, with anxiety exerting a stronger indirect effect on suicidal ideation. Conclusions: Depression is a key predictor of suicidal ideation, while anxiety exerts a dual influence. Suicidal ideation among older adults appears to be more strongly shaped by multiple factors, with particular emphasis on the combined effects of depression and sleep disturbances.
Source: Frontiers in Psychiatry
Authors: Zhiyong Li, Yuhang Fan, Chenyu Li, Ting Men, Yang Shen
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7115735701
