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<p>Depressive symptoms are common among rural adolescents and are closely linked to proximal social-ecological factors. However, it remains unclear how specific depressive symptom dimensions are connected with these factors, which proximal factors and depressive symptoms serve as bridge nodes, and whether these patterns differ by gender. A multi-stage cluster sampling method was used to survey 4,070 rural Chinese adolescents. Network analysis was performed using R software, with the model including depressive symptoms and proximal social-ecological factors. Bridge expected influence was calculated to identify bridge nodes. Network comparison tests were used to examine gender differences in network structure and strength. The strongest cross-community edge was observed between social support and anhedonia. Bridge expected influence identified parental rejection, negative mood, and negative coping as the most prominent bridge nodes in the overall network. Network comparison showed a significant difference in network structure, but not in global strength. In the male network, negative mood showed the highest BEI among depressive symptoms, whereas interpersonal problems showed the highest BEI in the female network. Proximal social-ecological factors are connected with depressive symptoms in a specific pathway. Parental rejection, negative coping, and gender-specific bridge symptoms may represent important targets for future interventions.</p>

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Gender differences in associations of proximal social-ecological factors with depressive symptoms among rural Chinese adolescents: a network analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月25日

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  • Ziyue Zhou,
  • Zhenxiang Cui,
  • Zhuo Wang,
  • Yitong Cai,
  • Ziwen Wang,
  • Shuangqi Yan,
  • Tengyun Si,
  • Xiaoyue Zhang,
  • Ruotian Zhou,
  • Dongling Liu

摘要

Depressive symptoms are common among rural adolescents and are closely linked to proximal social-ecological factors. However, it remains unclear how specific depressive symptom dimensions are connected with these factors, which proximal factors and depressive symptoms serve as bridge nodes, and whether these patterns differ by gender. A multi-stage cluster sampling method was used to survey 4,070 rural Chinese adolescents. Network analysis was performed using R software, with the model including depressive symptoms and proximal social-ecological factors. Bridge expected influence was calculated to identify bridge nodes. Network comparison tests were used to examine gender differences in network structure and strength. The strongest cross-community edge was observed between social support and anhedonia. Bridge expected influence identified parental rejection, negative mood, and negative coping as the most prominent bridge nodes in the overall network. Network comparison showed a significant difference in network structure, but not in global strength. In the male network, negative mood showed the highest BEI among depressive symptoms, whereas interpersonal problems showed the highest BEI in the female network. Proximal social-ecological factors are connected with depressive symptoms in a specific pathway. Parental rejection, negative coping, and gender-specific bridge symptoms may represent important targets for future interventions.