Psychometric properties of the Persian version of the Fleishman Job Analysis Survey (FJAS).

BACKGROUND: Job analysis is one of the most important and widely used processes to determine job duties, identify and reduce potential risks, and specify the skills and facilities required for each job at the highest level of occupational safety and health. OBJECTIVE: This study aimed to perform psychometric analyses of the Persian version of the Fleishman Job Analysis Survey (FJAS). METHODS: A cross-sectional study was conducted among 31 drivers. Participants were selected by random sampling. Ten occupational health and ergonomics experts confirmed the validity of the survey. First, we calculated the survey's CVR and CVI. Then, we used ICC and Cronbach's alpha coefficients to evaluate the survey's reliability. Data analysis utilized SPSS 21. RESULTS: 78% of the participants were male and 22% were female. The mean age±SD of the participants was 39.1±11.82 years. The reliability and validity of the short version survey showed that the value of ICC and Cronbach's alpha coefficient was 0.96, and CVR was 0.75. Moreover, the values of CVI for simplicity, clarity, and relevance were 0.87, 1, and 0.73, respectively. The long version's ICC and CVR were 0.96 and 0.97, respectively. Simplicity, clarity, and relevance CVI scores were 0.9, 0.94, and 0.95. CONCLUSION: The results of this study showed that the Persian version of the Fleischman Job Analysis Survey has the necessary validity and reliability for job analysis, so it can be used for driving professional or research purposes. Moreover, this survey is an effective tool for obtaining accurate and complete knowledge of job tasks and requirements.

Prioritizing risk factors of hazardous material road transportation accidents using the fuzzy AHP method.

BACKGROUND: Annually, large amounts of hazardous materials (hazmat) are transported through the roads and this movement causes various accidents. Identifying the causes of these accidents is a critical issue for all public governments. OBJECTIVES: This study aimed to identify the effective risk factors for hazmat road transport accidents and determine their relative weight using the fuzzy analytical hierarchy process (AHP) method. METHODS: This qualitative study was conducted in 2021 in Iran and included four steps, i.e., the identification (using literature review and semi-structured interview), determination (according to the expert panel opinion), classification, and prioritization of effective factors in hazmat road transportation accidents. To prioritize and determine the relative weight of the effective factors, the fuzzy AHP technique was used. RESULTS: In total, 159 risk factors were identified, which were classified into six factors (including road, transportation management, vehicle, cargo, driver, and weather conditions) and 24 sub-factors. The main factor (greatest relative weight) with the highest priority was the driver (0.181). The road (0.167), cargo (0.166), vehicle (0.169), transportation management (0.161), and weather conditions (0.159) were the next priorities, in that order. CONCLUSION: The results demonstrated that the driver is the most important factor in causing accidents when transporting hazmat by road. The findings of this study might have the potential to decrease the frequency and consequence of accidents caused by the road transport of hazmat.