Background <p>Health risk behaviors are crucial to developing college students’ mental and physical health. This study aimed to explore the relationship between social media use and health risk behaviors and to examine the structural relationships between the two through network analysis.</p> Methods <p>This study was a cross-sectional design with a convenience sample of 3,489 college students aged 18–22 years, and data were collected using relevant questionnaires. R 4.3.2 software was used to construct the social media use and health risk behaviors network to explore the complex relationship between the variables.</p> Results <p>In the social media use and health risk behaviors network, there are 25 edges connecting two communities. Physiological damage, psychological addiction behaviors, and risky sexual behaviors have the greatest expected impact, with Bridge Expected Influence (BEI) values of 0.15, -0.27, and 0.22, respectively. The Directed Acyclic Graph (DAG) indicates that physiological damage occupies an upstream position (i.e., appearing earlier in the causal pathway) among all influencing factors.</p> Conclusion <p>Physical damage and psychological addiction behaviors are key bridging nodes in the network, playing a central role in increasing participation in inter-symptom interactions. The DAG shows that physical damage is at the top of the network and can influence health risk behaviors through fear of missing out and cognitive failure. The bridge-centered indicators identified in this study can be used as a guide to action for the intervention of college students’ health risk behaviors, to effectively prevent and mitigate the occurrence of college students’ health risk behaviors.</p>

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The relationship between social media use and health risk behaviors among college students: a network analysis

  • Ziting Zhao,
  • Min Zhang,
  • Yang Liu,
  • Lieyuan Sun,
  • Yang Li

摘要

Background

Health risk behaviors are crucial to developing college students’ mental and physical health. This study aimed to explore the relationship between social media use and health risk behaviors and to examine the structural relationships between the two through network analysis.

Methods

This study was a cross-sectional design with a convenience sample of 3,489 college students aged 18–22 years, and data were collected using relevant questionnaires. R 4.3.2 software was used to construct the social media use and health risk behaviors network to explore the complex relationship between the variables.

Results

In the social media use and health risk behaviors network, there are 25 edges connecting two communities. Physiological damage, psychological addiction behaviors, and risky sexual behaviors have the greatest expected impact, with Bridge Expected Influence (BEI) values of 0.15, -0.27, and 0.22, respectively. The Directed Acyclic Graph (DAG) indicates that physiological damage occupies an upstream position (i.e., appearing earlier in the causal pathway) among all influencing factors.

Conclusion

Physical damage and psychological addiction behaviors are key bridging nodes in the network, playing a central role in increasing participation in inter-symptom interactions. The DAG shows that physical damage is at the top of the network and can influence health risk behaviors through fear of missing out and cognitive failure. The bridge-centered indicators identified in this study can be used as a guide to action for the intervention of college students’ health risk behaviors, to effectively prevent and mitigate the occurrence of college students’ health risk behaviors.