Exploring influences on radiation protection compliance: a directed acyclic graph-based cross-sectional study in a non-teaching hospital in western China

探究影响辐射防护依从性的因素:一项基于有向无环图的横断面研究(中国西部一家非教学医院)

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Abstract

BACKGROUND: Occupational radiation exposure poses significant health risks to medical personnel. However, the causal pathways linking protective knowledge, attitudes, and behavior (KAB) remain underexplored. Therefore, this study aimed to apply directed acyclic graphs (DAGs) to clarify the mechanistic relationships among these factors. METHODS: A cross-sectional survey of 335 radiation workers from a non-teaching level III general hospital in western China used validated scales to measure KAB. DAGs were constructed based on theoretical frameworks and previous evidence, complemented by correlation analyses, multivariate linear regression, and structural equation modeling. RESULTS: Radiation protection knowledge exerted the strongest direct effect on protective behavior (β = 0.55 5, p < 0.001). Attitude mediated 18.3% of the total effect (β = 0. 024, 95% confidence interval [0.0 03-0. 045]). Age was a significant negative predictor of compliance (β = -0. 390, p < 0.001), while training improved both knowledge (β = 0. 394, p < 0.001) and behavior (β = 0.1 47, p < 0.001). Educational level was significantly correlated with knowledge acquisition (β = 0.101, p = 0.029) but did not directly influence behavior. Participants demonstrated positive attitudes (mean = 21.35/25) and behaviors (mean = 28.99/35). However, critical knowledge gaps persisted in radiation culture (28% correct) and emergency protocols (25% correct). CONCLUSIONS: This study applied DAGs to clarify causal mechanisms in radiation protection, highlighting knowledge acquisition as a key driver of safe practices. Age-specific interventions and standardized training programs are recommended to address knowledge deficits and mitigate age-related behavioral decline. These findings provide a methodological foundation for optimizing occupational health strategies, with implications for policy design and future longitudinal validation.

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