Han Zhang, Ye Xia, Peicai Fu, Cun Li, Ke Shi, Yuan Yang
{"title":"抑郁和焦虑的社会心理通路的性别差异:横断面和贝叶斯因果网络研究。","authors":"Han Zhang, Ye Xia, Peicai Fu, Cun Li, Ke Shi, Yuan Yang","doi":"10.2196/76913","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 (R²=72.4%) and anxiety (R²=64%), supporting the robustness of the model. The network structure invariance test between male and female participants was significant (P=.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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e76913"},"PeriodicalIF":6.0000,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12494359/pdf/","citationCount":"0","resultStr":"{\"title\":\"Gender Differences in Psychosocial Pathways to Depression and Anxiety: Cross-Sectional and Bayesian Causal Network Study.\",\"authors\":\"Han Zhang, Ye Xia, Peicai Fu, Cun Li, Ke Shi, Yuan Yang\",\"doi\":\"10.2196/76913\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 (R²=72.4%) and anxiety (R²=64%), supporting the robustness of the model. The network structure invariance test between male and female participants was significant (P=.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.</p><p><strong>Conclusions: </strong>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. 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Gender Differences in Psychosocial Pathways to Depression and Anxiety: Cross-Sectional and Bayesian Causal Network Study.
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 development of depression and anxiety remain unclear.
Objective: 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.
Methods: 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.
Results: 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 (R²=72.4%) and anxiety (R²=64%), supporting the robustness of the model. The network structure invariance test between male and female participants was significant (P=.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.
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 women and emotion regulation for men. Findings support gender-sensitive mental health strategies and emphasize the need for longitudinal validation.
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.