Modeling the Factors Affecting Unsafe Behaviors using Fuzzy Logic in an Iranian Steel Industry

Document Type : Original Article


1 Department of Occupational Health Engineering, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran

2 Department of Occupational Health, School of Public Health, Kashan University of Medical Sciences, Kashan, Iran

3 Department of Occupational Health, School of Public Health, Sirjan University of Medical Sciences, Sirjan, Iran

4 Department of Occupational Health, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran



Unsafe behaviors (UBs) are the most important cause of accidents, so there is a need to identify the factors effective on it. The purpose of this study was to identify the factors affecting the occurrence of UBs and also to build a strong theoretical model with fuzzy logic.
Materials and Methods: 
This study was conducted among 270 participants in the steel industry in Iran. The factors, such as work-family conflict, job stress, and general health were investigated using relevant questionnaires, and the prevalence of UBs was investigated with the safety behavior sampling technique. Finally, the results were analyzed with SPSS 21.0 and MATLAB software.
The results showed that out of 1310 samples of observed behavior, 531 UBs were observed (39.81%). There were 202 cases of nonuse or inappropriate use of personal protective equipment. General health, job stress in the supervisor, and colleagues' support were significantly associated with UBs (P < 0.05). In addition, general health, work-family conflict, job stress and were significantly correlated with each other (P < 0.001). Diffuse results using fuzzy logic predicted 56% of the behavioral conditions.
This study showed that managing UBs is possible by controlling factors such as the support of supervisors and the way of management, as well as the reduction of social stresses such as work-family conflict, in addition to being able to increase people's health, also reducing accidents and UBs. Finally, using fuzzy logic, it is able to predict reality, and by knowing several behaviors, better models can be obtained.