Prioritizing decision-making of health and well-being response tactics: Incorporating organizational and individual shared demands.

As a major energy source in China, the occupational health and well-being (OHW) of miners is a priority. Various statistical techniques have been used to identify factors or assess OHW to provide valuable information for the implementation of health promotion activities. The main bottleneck is the limited focus on solutions that address the demands of both organizations and individuals, and scientific and effective decision-making is pending. Therefore, this study describes the OHW mechanism covering both antecedents and consequences through the driving force-pressure-state-impact-response model. A probabilistic model of management tradeoff analysis was established by using a Bayesian decision network. Causal relationships and dependencies between multiple factors are captured visually. The model was verified and applied with samples of miners (N = 816). The results showed that the comprehensive strategy (R5) was the best tactic, and the management effect of stress (R2) and vulnerability (R3) was prominent. This study provides a valuable tool for managers to identify priority management factors. Prioritizing tactics formulated from dual demands of organizational and individual can ensure project feasibility, operability, and effectiveness. This study is a novel attempt to combine theory with practice, which is timely and necessary for management.

Capturing and quantifying the aggregate effects of multi-source factors affecting miners' health and well-being: Construction of Bayesian belief networks.

Factors originating at the organizational, work, and individual levels are closely interrelated and intricately intertwined, affecting health rates. There was limited research on the interdependence and aggregate effects between multi-source factors and occupational health and well-being (OHW). It is challenging to achieve management goals. Therefore, considering cross-level factors and across the "work environment-stress-exposure-OHW" chain, individual vulnerability was considered. A Fuzzy Bayesian Belief Network (FBBN) driven by both domain knowledge and data was constructed to carve out the logic between multi-source factors and OHW. Workers from four coal mines were surveyed twice in 6 months. 714 valid samples were included in the analysis. The interdependencies among multi-source factors were identified by the Interpretive Structure Modeling method and the visual probability estimation was achieved based on FBBN. It revealed that the work and the organizational level were the root factors. Eight factors involved in work stress were mainly mediating, and actual exposure and individual vulnerability were direct factors. Pathway interventions and joint interventions were proposed. The prediction ability and scheme feasibility of FBBN were verified. The approach developed allows robust assessments of aggregate effects and obtains multi-source factor importance. This study provides vital insights and evaluation tools for understanding workplace stress and OHW management.