ArticleFrontiers in public health2025
Coping behavior toward occupational health risks among construction workers: determinant identification using the COM-B model and data mining analysis.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Dynamic reward-penalty incentives and occupational health governance: an evolutionary game analysis with public health implications.Frontiers in public health · 2026Article
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5 authors.
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Abstract
Background: China has the largest construction workforce in the world but faces severe occupational health challenges. Coping behaviors related to occupational health risks (CBOHR) are key to mitigating these hazards but remain understudied. Materials and methods: A cross-sectional survey of 484 construction workers was conducted to assess Capability, Opportunity, Motivation, and Behavior using the COM-B model. Structural equation modeling (SEM) was employed to test mediating pathways, and association-rule mining (ARM) was used to identify determinants of high- and low-level CBOHR. Results: The results showed that the COM-B framework-comprising three modules (Capability, Opportunity, and Motivation) with 15 behavior change domains, and a Behavior module with eight specific CBOHRs-demonstrated satisfactory fit, reliability, and validity. Bootstrapping confirmed that Motivation fully mediates the relationship between Capability and Behavior and partially mediates the relationship between Opportunity and Behavior. ARM further identified key domains associated with high and low levels of CBOHR. Conclusion: Strongly correlated item sets identified through association rule analysis revealed domains strongly linked to both high (and low) levels of each CBOHR. This study is the first to integrate the COM-B model with data mining in the context of occupational health, highlighting "motivation-values-policy" as actionable levers for CBOHR interventions. The findings provide preliminary evidence to support the development of scalable worker health programs.
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