Iranian Journal of Ergonomics

Background and Objectives: Most accidents are caused by unsafe behaviors or human errors. Safety experts have argued that with the increasing focus on human behavior, it can significantly reduce accidents. The aim of the present study was to examine neuroticism, safety efficacy and regulatory focus as predictors of unsafe work behavior of employee Bidboland Gas Refining Company.
Methods: The statistical population of the study consisted of all employees of operational and staffing departments of Bidboland Gas Refining Company in Khuzestan. The sample consisted of 273 employees who were selected using stratified random sampling. At first, the participants were divided into two groups, safe employees and unsafe employees by using Safety Behavior Scale (Salleh, 2010). Then to evaluate the variables studied, NEO personality characteristics (Costa & McCrae, 1992), safety efficacy (Brown, et al., 2000) and regulatory focus at work (Wallace & Chen, 2006) questionnaires were used. Data were analyzed through discriminant analysis and using SPSS 16 software.
Results: According to the results, unsafe behavior of employees can be predicted from neuroticism, safety efficacy and regulatory focus and its dimensions (prevention focus and promotion focus).
Conclusion: Neuroticism increases unsafe behaviors and safety efficacy and regulatory focus (prevention focus and promotion focus) decrease unsafe behaviors of employees.

Background and aim: Traffic accidents are a leading cause of mortality and severe injuries. Driver behavior is a significant factor influencing this issue. This study aimed to investigate the status of unsafe driving behaviors and their relationship with road accidents among intercity drivers in Urmia.

Methods: This cross-sectional study conducted on 378 intercity drivers visiting the Occupational Medicine Center at Urmia University of Medical Sciences. Sampling was performed using a convenience method. The Driver Behavior Questionnaire (DBQ) was employed as the standard instrument. Data analysis was conducted using SPSS version 24 at the significance level of 0.05.

Findings: The highest score for unsafe behaviors was related to non-routine violations, with a mean of 1.33 ± 0.44. Significant positive correlations were found between all four DBQ subscales and road accidents (p < 0.001). Linear regression analysis revealed that routine violations and errors significantly predicted 24.3% of the variance in annual accidents.

Conclusion: This study demonstrated significant associations between unsafe driving behaviors and traffic accidents, emphasizing the need for targeted interventions to reduce high-risk driving behaviors.