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Identifying potential intervention targets for eating behaviors among Chinese nursing students: a cross-sectional study
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DOI：10.1186/s12912-026-05200-y.png)
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Abstract
En 中文
Although unhealthy eating behaviors are increasingly recognized among university students, their specific manifestations and behavior patterns remain insufficiently understood in nursing students. This study identified the key eating behaviors and potential intervention targets among Chinese nursing students. In this cross-sectional study, 437 Chinese nursing undergraduates completed a demographic questionnaire and the Dutch Eating Behavior Questionnaire between October 2023 and July 2024 through the “Be Resilient to Nursing Career” project from four universities. We used Gaussian network analysis to identify central eating behavior, Bayesian network analysis to identify the upstream behaviors, and computer-simulated interventions to identify potential targets. Deliberately eating less to avoid weight gain (D7) and eating when things are going against oneself (D19) were the most central behavior. Bayesian network analysis further identified avoiding eating between meals to control weight (D8) as a key upstream behavior. Simulation analyses identified deliberately eating less to avoid weight gain (D7) as the main alleviation target and eating when things are going against oneself (D19) as the main aggravation target. This study identifies specific eating-behavior targets among nursing students, highlighting restraint-oriented weight-control behaviors and emotion-related eating as priority domains for intervention. These findings inform the development of precise student-support strategies and provide a network-informed foundation for targeted prevention and health-promotion initiatives in nursing education and clinical practice.
Keywords:
Eating behavior
Nursing students
Gaussian network analysis
Bayesian network analysis
Computer-simulated intervention
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