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Background <p>Depressive and anxiety disorders represent globally significant mental health burdens, imposing substantial impacts on individuals, societies, and healthcare infrastructure. In China, nationally representative epidemiological studies report a lifetime prevalence of 7.6% for anxiety disorders and 6.6% for depressive disorders. Both conditions demonstrate age-dependent heterogeneity, with older populations exhibiting significantly higher susceptibility and elevated comorbidity.</p> Methods <p>The cross-sectional study of community populations constructed Ising network models for different age groups, and then applied the NodeIdentifyR algorithm (NIRA) to identify dual-pathway intervention targets — nodes projected to alleviate (treatment) or aggravate (prevention) symptoms.</p> Results <p>The analysis indicated a heterogeneous link between coping styles and anxiety and depression, with notable age differences observed. Further simulation of intervention outcomes suggested that age-specific coping profiles emerged as viable targets for clinical intervention.</p> Conclusions <p>Using psychopathological network modeling, this study reveals age-related heterogeneity in the association patterns between coping styles and anxiety-depression symptoms, as well as in the corresponding intervention targets.</p>

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Computational simulation of intervention targets: elucidating coping style mechanisms in anxiety and depressive symptom networks in community populations

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月21日

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  • Zhenxuan Dong,
  • Dingchao Wu,
  • Xiujun Zhang,
  • Haitao Wang,
  • Hongge Luo

摘要

Background

Depressive and anxiety disorders represent globally significant mental health burdens, imposing substantial impacts on individuals, societies, and healthcare infrastructure. In China, nationally representative epidemiological studies report a lifetime prevalence of 7.6% for anxiety disorders and 6.6% for depressive disorders. Both conditions demonstrate age-dependent heterogeneity, with older populations exhibiting significantly higher susceptibility and elevated comorbidity.

Methods

The cross-sectional study of community populations constructed Ising network models for different age groups, and then applied the NodeIdentifyR algorithm (NIRA) to identify dual-pathway intervention targets — nodes projected to alleviate (treatment) or aggravate (prevention) symptoms.

Results

The analysis indicated a heterogeneous link between coping styles and anxiety and depression, with notable age differences observed. Further simulation of intervention outcomes suggested that age-specific coping profiles emerged as viable targets for clinical intervention.

Conclusions

Using psychopathological network modeling, this study reveals age-related heterogeneity in the association patterns between coping styles and anxiety-depression symptoms, as well as in the corresponding intervention targets.