Predicting personal injury crash risk through working conditions, job strain, and risky driving behaviors among taxi drivers

Abstract Introduction Taxis play an important role among public transport modes in China, but there has been very little in-depth research regarding taxi drivers’ crash risk. Thus, this study aimed to develop a quantitative method to predict taxi drivers’ crash risk and identify contributory factors. Methods Nine hundred fourty-eight professional taxi drivers in Xi’an, China completed an anonymous, structured face-to-face questionnaire reporting their demographic information, work-related stress, daily risky driving behaviors, and crash experience within the 3 years prior to the survey. A Negative-Binomial regression model was used to predict the risk of personal injury collisions for taxi drivers. Results Drivers’ 7 risky driving behaviors (e.g., disregarding red lights, speeding, aggressive driving, driving while sleepy or fatigued, etc.) were significantly and positively related to the risk of personal injury collisions, while driver’s parking at will to pick up/drop off passengers was not a significant predictor of such risk for taxi drivers. Furthermore, driver’s sociodemographic characteristics and level of occupational workload were not found to be significantly correlated with the personal injury crash risk. Conclusions Risk traits appear to peak among male taxi drivers who drive more hours per day, pay high management fees, and frequently engage in risky behaviors while driving. These findings provide implications to design potentially useful policy initiatives as well as targeted safety promotion programs to prevent road crashes involving professional taxi drivers