{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T22:33:48Z","timestamp":1791844428791,"version":"4.3.4"},"reference-count":65,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n 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 development of depression and anxiety remain unclear.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n The objective of this study was 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.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n This study included 6105 participants from across China, collecting their sociodemographic characteristics and psychological scale data. Cross-sectional network analysis was used 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.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Network analysis revealed strong associations among depression, anxiety, insomnia, and somatic symptoms. Network strength centrality exhibited the highest stability across overall networks (CS-C=0.75), with high predictability for depression (\n R<\/jats:italic>\n \u00b2=72.4%) and anxiety (\n R<\/jats:italic>\n \u00b2=64%), supporting the robustness of the model. The network structure invariance test between male and female participants was significant (\n P<\/jats:italic>\n =.001). Furthermore, the Bayesian network analysis showed gender-specific symptom progression, where anxiety preceded depression in male participants, while depression preceded anxiety in female participants (with edges retained in nearly 100% of bootstrap samples). Self-esteem, social support, and insomnia were central nodes in female participants, whereas emotion regulation was more influential in male participants. Additionally, childhood trauma influenced depression or anxiety indirectly through self-esteem and social support in both male and female participants.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n 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 women and emotion regulation for men. Findings support gender-sensitive mental health strategies and emphasize the need for longitudinal validation.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/76913","type":"journal-article","created":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T20:41:08Z","timestamp":1759524068000},"page":"e76913-e76913","source":"Crossref","is-referenced-by-count":16,"title":["Gender Differences in Psychosocial Pathways to Depression and Anxiety: Cross-Sectional and Bayesian Causal Network 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