RESUMO
Background: Various factors are involved in the occurrence and prediction of road traffic crashes (RTCs). The most important of these are human factors that can be influenced by the sociocultural characteristics of the drivers. This research aimed at identifying the socio-cultural factors (SCFs) in car drivers affecting the RTCs. Methods: In the present study, Web of Science, PubMed, Scopus, ProQuest, Google Scholar, Cochran Library, Magiran, Irandoc, Noor magas, Islamic World Science Citation Center, and Scientific Information Database were searched from 1990 to August 20th, 2021; key journals, the reference lists of the included studies, gray literature, websites of relevant organizations were manually reviewed. Studies that reviewed the effect of SCFs related to car drivers in the incidence or prediction of road traffic crashes were included and analyzed using thematic content analysis. Results were expressed based on the PRISMA guideline. The quality of the included studies was assessed using related checklists. Results: Eighty-four eligible studies were determined from a systematic search and entered into the analysis process. Studies are presented that SCFs affecting the occurrence of RTCs fall into four categories, including (1) sociodemographic characteristics, (2) personality traits, (3) driver behavior (driving style), (4) driver performance (driving skills). Conclusion: In most studies, SCFs have been examined in frames of social-demographic characteristics and risky driving behaviors. While, the impact of personality traits and driver performance, which are very important factors on RTCs, has not been addressed. Therefore, investigating the impact of these factors in occurring RTCs is crucial.
RESUMO
BACKGROUND: Various factors are involved in the occurrence of Road Traffic Crashes (RTCs), one of the most important of these are human factors that can be greatly influenced by the specific sociocultural bases of the drivers. So far, there has not been a scale for measuring Sociocultural Factors (SCFs) predicting the occurrence of RTCs in Iranian drivers. Therefore, the present study was conducted to design and to do psychometric evaluation of a scale for measuring SCFs predicting the occurrence of RTCs in drivers. METHODS: This exploratory sequential mixed method was carried out in three phases. In phases 1 and 2, an initial items pool was created based on systematic literature review (phase1), and semi structured interviews (phase 2). In phase 3, the initial scales were validated using face and content validities. Then, principal component analysis and confirmatory factor analysis were performed to assess the construct validity. Finally, the reliability of the scale was evaluated by examining internal consistency and stability. RESULTS: The scale content validity index was 0.92. Principal component analysis showed seven factors with 27 items, which explain 55.56% of the total variance. In confirmatory factor analysis, model fit indices were satisfactory. Discriminant analysis was also able to distinguish between two groups of accident-involved drivers and accident-free drivers (P less than 0.0001). The reliability of the scale by Cronbach's alpha, Theta, Omega and intra-class correlation coefficients was 0.82, 0.96, 3.07, and 0.80, respectively. CONCLUSIONS: This scale can be used as a valid and reliable scale to evaluate the SCFs predicting the occurrence of RTCs in drivers. Furthermore, the findings of this study will be useful in identifying and planning to reduce RTCs, especially in accident-prone drivers.
