Fakhradin Ghasemi1, Omid Kalatpour1, Abbas Moghimbeigi2, Iraj Mohammadfam3. 1. Center of Excellence for Occupational Health, Research Center for Health science, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran. 2. Modeling of Non communicable Diseases Research Center and Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran. 3. CCenter of Excellence for Occupational Health, Research Center for Health science, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran. mohammadfam@umsha.ac.ir.
Abstract
BACKGROUND: High-risk unsafe behaviors (HRUBs) have been known as the main cause of occupational accidents. Considering the financial and societal costs of accidents and the limitations of available resources, there is an urgent need for managing unsafe behaviors at workplaces. The aim of the present study was to find strategies for decreasing the rate of HRUBs using an integrated approach of safety behavior sampling technique and Bayesian networks analysis. STUDY DESIGN: A cross-sectional study. METHODS: The Bayesian network was constructed using a focus group approach. The required data was collected using the safety behavior sampling, and the parameters of the network were estimated using Expectation-Maximization algorithm. Using sensitivity analysis and belief updating, it was determined that which factors had the highest influences on unsafe behavior. RESULTS: Based on BN analyses, safety training was the most important factor influencing employees' behavior at the workplace. High quality safety training courses can reduce the rate of HRUBs about 10%. Moreover, the rate of HRUBs increased by decreasing the age of employees. The rate of HRUBs was higher in the afternoon and last days of a week. CONCLUSIONS: Among the investigated variables, training was the most important factor affecting safety behavior of employees. By holding high quality safety training courses, companies would be able to reduce the rate of HRUBs significantly.
BACKGROUND: High-risk unsafe behaviors (HRUBs) have been known as the main cause of occupational accidents. Considering the financial and societal costs of accidents and the limitations of available resources, there is an urgent need for managing unsafe behaviors at workplaces. The aim of the present study was to find strategies for decreasing the rate of HRUBs using an integrated approach of safety behavior sampling technique and Bayesian networks analysis. STUDY DESIGN: A cross-sectional study. METHODS: The Bayesian network was constructed using a focus group approach. The required data was collected using the safety behavior sampling, and the parameters of the network were estimated using Expectation-Maximization algorithm. Using sensitivity analysis and belief updating, it was determined that which factors had the highest influences on unsafe behavior. RESULTS: Based on BN analyses, safety training was the most important factor influencing employees' behavior at the workplace. High quality safety training courses can reduce the rate of HRUBs about 10%. Moreover, the rate of HRUBs increased by decreasing the age of employees. The rate of HRUBs was higher in the afternoon and last days of a week. CONCLUSIONS: Among the investigated variables, training was the most important factor affecting safety behavior of employees. By holding high quality safety training courses, companies would be able to reduce the rate of HRUBs significantly.
Entities:
Keywords:
Accident Prevention; Behavior; Construction Industry; Data Mining; Occupational Injuries; Safety Management
Authors: Lluís Sanmiquel; Marc Bascompta; Josep M Rossell; Hernán Francisco Anticoi; Eduard Guash Journal: Int J Environ Res Public Health Date: 2018-03-07 Impact factor: 3.390