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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 4, 2025
Date Accepted: Aug 19, 2025

The final, peer-reviewed published version of this preprint can be found here:

Gender Differences in Psychosocial Pathways to Depression and Anxiety: Cross-Sectional and Bayesian Causal Network Study

Zhang H, Xia Y, Fu P, Li C, Ke S, Yang Y

Gender Differences in Psychosocial Pathways to Depression and Anxiety: Cross-Sectional and Bayesian Causal Network Study

J Med Internet Res 2025;27:e76913

DOI: 10.2196/76913

PMID: 41043132

PMCID: 12494359

Gender Differences in Psychosocial Pathways to Depression and Anxiety: A Cross-Sectional and Bayesian Causal Network Study

  • Han Zhang; 
  • Ye Xia; 
  • Peicai Fu; 
  • Cun Li; 
  • Shi Ke; 
  • Yuan Yang

ABSTRACT

Background:

Depression and anxiety are widespread disorders with documented gender differences in symptom progression and associated psychosocial factors. However, the complex interrelationships between childhood trauma, self-esteem, social support, emotion regulation, and their gender-specific impacts on the develop of depression and anxiety remain unclear.

Objective:

To investigate the network structures of depression, anxiety, and psychosocial factors, and to examine the pathways contributing to the development of depression and anxiety, with a focus on gender-specific differences.

Methods:

This study included 6518 participants from across China, collecting their sociodemographic characteristics and psychological scale data. Cross-sectional network analysis was employed to explore the complex relationships between depression, anxiety, insomnia, somatic symptoms, childhood trauma, self-esteem, social support, and emotional regulation. Subsequently, Bayesian network analysis was used to infer potential causal pathways. Gender differences in the network structures were specifically examined.

Results:

Network analysis revealed strong associations among depression, anxiety, insomnia, and somatic symptoms, with a more intricate structure observed in females compared to males. Network predictability was strong, with depression (72.4%) and anxiety (64.0%) demonstrating robust predictive power, thereby confirming the model’s reliability. Bayesian network analysis showed gender-specific symptom progression, where anxiety preceded depression in males, while depression preceded anxiety in females. Self-esteem, social support and insomnia were central nodes in females, whereas emotion regulation was more influential in males. Additionally, childhood trauma influenced depression or anxiety indirectly through self-esteem and social support both in males and females.

Conclusions:

This study presents a novel application of network analyses to delineate distinct gender-specific pathways in the development of depression and anxiety. The findings underscore insomnia, self-esteem, and social support as intervention targets for females and emotion regulation for males. Findings support gender-sensitive mental health strategies and emphasize the need for longitudinal validation. Clinical Trial: It was registered in the Chinese Clinical Trial Registry (Registration number: ChiCTR2200059155).


 Citation

Please cite as:

Zhang H, Xia Y, Fu P, Li C, Ke S, Yang Y

Gender Differences in Psychosocial Pathways to Depression and Anxiety: Cross-Sectional and Bayesian Causal Network Study

J Med Internet Res 2025;27:e76913

DOI: 10.2196/76913

PMID: 41043132

PMCID: 12494359

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