ArticleJournal of injury & violence research2022
Design and psychometric evaluation of sociocultural scale predicting the incidence of road traffic crashes in drivers.
Article in Journal of injury & violence research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
backgroundVarious 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.
methodsThis 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.
resultsThe 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.
conclusionsThis 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.
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