Frontiers in public health · 2026
Network analysis of social support, resilience, quality of life, and insomnia under pandemic control measures.
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Dai Min, Xu Shuyu, Ling Jiaqi, Xiao Lei, Xu Jingzhou, Zhang Ruike, Wang Hao, Su Tong
Аннотация
BACKGROUND: During the COVID-19 pandemic, population mental health and sleep problems have become increasingly prominent. Social support, resilience, and quality of life are key determinants of sleep quality; however, their complex interrelationships remain insufficiently understood. This study used network analysis to examine the connections among social support, resilience, quality of life, and insomnia symptoms.
METHODS: We recruited 662 participants between April and May 2022. Participants completed the Social Support Rating Scale (SSRS), the Connor-Davidson Resilience Scale (CD-RISC), the World Health Organization Quality of Life-Brief (WHOQOL-BREF), and the Athens Insomnia Scale (AIS). We constructed network models with the dimensions of each scale and individual insomnia symptoms as nodes and computed centrality metrics (strength, expected influence) and bridge expected influence (BEI).
RESULTS: The network showed negative associations between insomnia symptoms and social support, resilience, and quality of life. Q2 (psychological) and R2 (strength) had the highest strength and high expected influence. R1 (tenacity), Q2 (psychological), and S1 (objective support) demonstrated the greatest positive bridge expected influence in the network, whereas I6 (sense of well-being during the day) had the greatest negative bridge expected influence within the insomnia symptom community.
CONCLUSION: This study illuminates the complex interconnections among social support, resilience, quality of life, and insomnia symptoms in the context of prolonged pandemic control measures and identifies core and bridge nodes through network analysis. These findings provide a theoretical foundation for improving population mental health and sleep quality. Clinicians should prioritize interventions that target core nodes and bridge symptoms to enhance effectiveness.
METHODS: We recruited 662 participants between April and May 2022. Participants completed the Social Support Rating Scale (SSRS), the Connor-Davidson Resilience Scale (CD-RISC), the World Health Organization Quality of Life-Brief (WHOQOL-BREF), and the Athens Insomnia Scale (AIS). We constructed network models with the dimensions of each scale and individual insomnia symptoms as nodes and computed centrality metrics (strength, expected influence) and bridge expected influence (BEI).
RESULTS: The network showed negative associations between insomnia symptoms and social support, resilience, and quality of life. Q2 (psychological) and R2 (strength) had the highest strength and high expected influence. R1 (tenacity), Q2 (psychological), and S1 (objective support) demonstrated the greatest positive bridge expected influence in the network, whereas I6 (sense of well-being during the day) had the greatest negative bridge expected influence within the insomnia symptom community.
CONCLUSION: This study illuminates the complex interconnections among social support, resilience, quality of life, and insomnia symptoms in the context of prolonged pandemic control measures and identifies core and bridge nodes through network analysis. These findings provide a theoretical foundation for improving population mental health and sleep quality. Clinicians should prioritize interventions that target core nodes and bridge symptoms to enhance effectiveness.