Incorporating ergonomic and psychosocial stressors: A comprehensive model for assessing miners’ work-related musculoskeletal disorders

Abstract

Although the influence of ergonomic and psychosocial stressors on work-related musculoskeletal disorders (WMSDs) has been widely recognized, a risk assessment method that comprehensively considers these stressors is still lacking. As such, this study developed a fuzzy Bayesian network (FBN) model that incorporated a comprehensive set of ergonomic and psychosocial stressors to investigate how they interacted to affect frontline miners’ WMSDs risk. A methodology combining fuzzy set theory, Leaky Noisy-OR gate, and an expert weight dynamic adjustment algorithm was employed to deal with fuzziness, uncertainty, limited data, and conflicting judgments and to provide a probabilistic assessment. Meanwhile, the FBN was validated using 10-fold cross-validation through data collected from 542 frontline miners. Results indicated that the probability of frontline miners suffering from WMSDs is 79.7%. Vibration, awkward posture, inadequate organizational support, inadequate organizational justice, and bad organizational culture were the most influential stressors to frontline miners’ WMSDs. The proposed FBN model can be a powerful decision-support tool to improve frontline miners’ musculoskeletal health by managing a more targeted subset of ergonomic and psychosocial stressors.