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Coping behavior toward occupational health risks among construction workers

Determinant identification using the COM-B model and data mining analysis

Bibliographic Data

ID22080980
AuthorsXuesong Yang (0000-0003-1798-4715, China Academy of Safety Sciences and Technology), Yuyan Ling (China University of Mining and Technology), Liqun Wang (0000-0002-1869-9871, China Academy of Safety Sciences and Technology), Yiqi Li (0000-0002-3730-5743, China Academy of Safety Sciences and Technology), Mingrong Zeng (China Academy of Safety Sciences and Technology, corresponding author)
Year2025
Volume13
Pages1643332-1643332
Publication date2025-09-12
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1643332
PMID41018795
OpenAlexW4414262117
LanguageEN
Citations received1
References cited117

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

Association rule learning · Occupational safety and health · Occupational Health and Safety Research · Pesticide Exposure and Toxicity · Workplace Health and Well-being

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Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1

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