Risk Assessment by Job Safety Analysis and William Fine Method and Comparison with Workers' Risk Perception Results

Abstract

Background: Job analysis, detecting hazards, and measuring their relationship with risk perception in workers are efficient ways of preventing accidents. Therefore, the present study is an attempt to identify and assess the risk of job accidents in steel industry in the south of Iran in 2020 using job safety analysis and the William Fine method. The results are also compared with the workers' perception of risk. Methods: The study population consisted of workers in the supplementary section of the studied steel industry(N=169). All the collected data were analyzed in SPSS using frequency and percentage for description and simple/multivariate logistic regression for analysis with sig. equal to 0.05.  To determine the risks, JSA was used. Risk assessment was also performed using William Fine method, and then risk scores were obtained. Afterwards, Risk Perception Questionnaire was used to collect information about risk perception in the workers. Results: In total, 265 job activities along with 2684 risks were identified and evaluated in 7 units of sections in the steel industry. Conclusion: The results of risk assessment and risk perception in this study indicate that when safety risk is properly perceived by workers, the chance of observing safety codes and better detection of risks increases. Therefore, in the face of an unsafe condition at work, workers will be abed to make the right decision and control the risk and prevent work accidents by taking corrective measures and making safe and efficient decisions.