Background: Some researchers state that they are not yet able to provide a deep understanding of the underlying causes of unsafe behaviors (UBs). Therefore, the present study was conducted to investigate the attitudes and experiences of Iranian workers of UBs. Methods: This present study was conducted in 35 industries using a semistructured interview based on grounded theory. Forty participants were interviewed, including 13 industrial safety and health experts and 27 workers and supervisors. The analysis of the present study consisted of a three-step coding process including open, axial, and selective coding. Results: The results showed that the factors affecting UBs could be classified into three categories: organizational, individual, and socioeconomic factors. Organizational factors were divided into 6 parts: procedure and environmental conditions, communications, monitoring, organizational safety culture, resource allocation, and human resources. Socioeconomic factors had three subcategories: community safety culture, type of organizational ownership, and economic problems. Finally, the individual factors were classified into two categories of personality traits and individual competence. Conclusion The results showed that organizational factors were the most categorized, and it is estimated that this factor has a more important role in the UBs. Of course, to better understand the close relationship between these factors and find the weight and importance of each factor, it needs to measure it with multicriteria decision systems.

Background: Some researchers state that they are not yet able to provide a deep understanding of the underlying causes of unsafe behaviors (UBs). Therefore, the present study was conducted to investigate the attitudes and experiences of Iranian workers of UBs. Methods: This present study was conducted in 35 industries using a semistructured interview based on grounded theory. Forty participants were interviewed, including 13 industrial safety and health experts and 27 workers and supervisors. The analysis of the present study consisted of a three-step coding process including open, axial, and selective coding. Results: The results showed that the factors affecting UBs could be classified into three categories: organizational, individual, and socioeconomic factors. Organizational factors were divided into 6 parts: procedure and environmental conditions, communications, monitoring, organizational safety culture, resource allocation, and human resources. Socioeconomic factors had three subcategories: community safety culture, type of organizational ownership, and economic problems. Finally, the individual factors were classified into two categories of personality traits and individual competence. Conclusion The results showed that organizational factors were the most categorized, and it is estimated that this factor has a more important role in the UBs. Of course, to better understand the close relationship between these factors and find the weight and importance of each factor, it needs to measure it with multicriteria decision systems.

BACKGROUND: Workforce health is one of the primary and most challenging issues, particularly in industrialized countries. This article aims at modeling the major factors affecting accidents in the workplace, including general health, work-family conflict, effortereward imbalance, and internal and external locus of control. METHODS: A cross-sectional study was conducted in Esfahan Steel Company in Iran. A total of 450 participants were divided into two groups—control and case—and the questionnaires were distributed among them. Data were collected through a 7-part questionnaire. Finally, the results were analyzed using SPSS 22.0 and Amos software. RESULTS: All the studied variables had a significant relationship with the accident proneness. In the case group, general health with a coefficient of −0.37, work-family conflict with 0.10, effort-reward imbalance with 0.10, internal locus of control with −0.07, and external locus of control with 0.40 had a direct effect on occupational stress. Occupational stress also had a positive direct effect on accident proneness with a coefficient of 0.47. In addition, fitness indices of control group showed general health (−0.35), work-family conflict (0.36), effort-reward imbalance (0.13), internal locus of control (−0.15), and external locus of control (0.12) have a direct effect on occupational stress. Besides, occupational stress with a coefficient of 0.09 had a direct effect on accident proneness. CONCLUSION: It can be concluded that although previous studies and the present study showed the effect of stress on accident and accident proneness, some hidden and external factors such as workefamily conflict, effortereward imbalance, and external locus of control that affect stress should also be considered. It helps industries face less occupational stress and, consequently, less occurrence rates of accidents.
Accident Proneness ; Accidents, Occupational ; Cross-Sectional Studies ; Developed Countries ; Internal-External Control ; Iran ; Steel

BACKGROUND: Occupational contact with blood and body fluids poses a significant risk to healthcare workers. The aim of this systematic review is to investigate the epidemiology and risk factors affecting needlestick injuries (NSI) in healthcare personnel in Iran. METHODS: In March 2020, researchers studied six international databases such as Medline/PubMed, ProQuest, ISI/WOS, Scopus, Embase, and Google Scholar for English papers and two Iranian databases (MagIran and SID) for Persian papers. Joanna Briggs Institute (JBI) Critical Appraisal Checklist was used to assess quality of studies. The method of reporting was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. RESULTS: A total of 43 articles were included in the analysis. Results showed that females (OR = 1.30, 95 % CI 1.06-1.58, P value = 0.009), younger age (OR = 2.75, 95 % CI 2.27-3.33, P value < 0.001, rotated shift workers (OR = 2.16, 95 % CI 1.47-3.15, P value < 0.001), not attending training courses (OR = 1.30, 95 % CI 1.07-1.56, P value = 0.006), working in the surgery ward (OR = 1.83, 95 % CI 1.33-2.50, P value < 0.001), less work experience (OR = 1.43, 95 % CI 1.04-1.95, P value = 0.025) apposed a greater risk factors for NSI among healthcare workers. CONCLUSION Based on the results of this review, factors such as young age, less work experience, work shift, and female gender are considered as strong risk factors for NSI injury in Iran. Preventive measures including education programs can reduce the burden of NSI among healthcare personnel.
Health Personnel/statistics & numerical data* ; Humans ; Incidence ; Iran/epidemiology* ; Needlestick Injuries/epidemiology* ; Prevalence ; Risk Factors