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Purpose <p>This study aimed to investigate the longitudinal dynamics among social networks, trust, and depressive symptoms from a network perspective.</p> Methods <p>Data was collected from three waves (2018, 2020, and 2022) of the China Family Panel Studies (CFPS), with a sample of 15,570 participants aged 16 and older. Social networks were measured using family and interpersonal network indicators, trust was assessed through six types of individual trust, and depressive symptoms were evaluated using the 8-item Center for Epidemiologic Studies Depression Scale. Cross-sectional and cross-lagged panel network analyses were conducted to examine symptom-level interactions and temporal dynamics.</p> Results <p>Cross-sectional network analyses showed that feeling sad (D7) consistently had the highest expected influence across all three waves. Trust in local government officials (T5) also showed relatively high expected influence, whereas trust in neighbors (T2) was comparatively prominent in 2018 and remained moderately central thereafter. Family network (SN1) showed relatively low expected influence across waves. Bridge expected influence was concentrated in the social-network and trust domains, particularly interpersonal network (SN2), as well as trust in neighbors (T2), trust in local government officials (T5), and trust in parents (T1), whereas depressive symptoms showed comparatively weaker bridging roles. Cross-lagged panel network analyses indicated strong autoregressive effects for most nodes. From 2018 to 2020, strong non-autoregressive paths were observed from feeling life is not worth living (D8) to several later depressive symptoms, while feeling sad (D7) showed the highest out-expected influence. From 2020 to 2022, family network (SN1) showed the highest out-expected influence, and social-network and trust-related paths appeared more prominent than in the earlier interval.</p> Conclusion <p>Depressive symptoms, social-network indicators, and trust were dynamically interconnected in the longitudinal network models. Feeling sad (D7) remained a central depressive node, whereas social-network and trust variables—especially interpersonal network (SN2) and family network (SN1)—were more prominent in cross-domain and temporal associations. These findings highlight the relevance of social-resource variables in understanding depression-related experiences and may help inform more targeted prevention and intervention strategies.</p>

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The longitudinal relationships between social networks, trust and depression: a cross-lagged panel network analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月27日

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  • Xinyue Li,
  • Mengmeng Xie,
  • Yingying Sun,
  • Hongyuan Ding,
  • Minghao Zhang,
  • Xue Zhang,
  • Xiaodi Wang,
  • Li Jiang

摘要

Purpose

This study aimed to investigate the longitudinal dynamics among social networks, trust, and depressive symptoms from a network perspective.

Methods

Data was collected from three waves (2018, 2020, and 2022) of the China Family Panel Studies (CFPS), with a sample of 15,570 participants aged 16 and older. Social networks were measured using family and interpersonal network indicators, trust was assessed through six types of individual trust, and depressive symptoms were evaluated using the 8-item Center for Epidemiologic Studies Depression Scale. Cross-sectional and cross-lagged panel network analyses were conducted to examine symptom-level interactions and temporal dynamics.

Results

Cross-sectional network analyses showed that feeling sad (D7) consistently had the highest expected influence across all three waves. Trust in local government officials (T5) also showed relatively high expected influence, whereas trust in neighbors (T2) was comparatively prominent in 2018 and remained moderately central thereafter. Family network (SN1) showed relatively low expected influence across waves. Bridge expected influence was concentrated in the social-network and trust domains, particularly interpersonal network (SN2), as well as trust in neighbors (T2), trust in local government officials (T5), and trust in parents (T1), whereas depressive symptoms showed comparatively weaker bridging roles. Cross-lagged panel network analyses indicated strong autoregressive effects for most nodes. From 2018 to 2020, strong non-autoregressive paths were observed from feeling life is not worth living (D8) to several later depressive symptoms, while feeling sad (D7) showed the highest out-expected influence. From 2020 to 2022, family network (SN1) showed the highest out-expected influence, and social-network and trust-related paths appeared more prominent than in the earlier interval.

Conclusion

Depressive symptoms, social-network indicators, and trust were dynamically interconnected in the longitudinal network models. Feeling sad (D7) remained a central depressive node, whereas social-network and trust variables—especially interpersonal network (SN2) and family network (SN1)—were more prominent in cross-domain and temporal associations. These findings highlight the relevance of social-resource variables in understanding depression-related experiences and may help inform more targeted prevention and intervention strategies.