Repositori URV

Identifier: imarina:9156872

Handle: https://hdl.handle.net/20.500.11797/imarina9156872

Authors:
Tàpia-Caballero, P., Serrano-Fernández, M.J., Boada-Cuerva, M., Sora, B., & Boada-Grau, J.

Abstract:
Objectives. Professional drivers drive for many hours without rest. This factor, in addition to the characteristics of the job, the vehicle, the environment and the driver, causes driver fatigue. Fatigue is one of the most common risk factors when driving because it causes drowsiness, decreases drivers’ attention and may make them fall asleep at the wheel. In this article we propose a predictive model for professional drivers using the following variables: age, number of children, time spent at work, time spent inside the vehicle, personality, job characteristics (JDS), job content (JCQ) and burnout. Method. Participants were 509 professional drivers from various transport sectors recruited by non-probabilistic sampling. SPSS version 25.0 was used for statistical analysis. Results. The predictive capacity of variables that cause driver fatigue was determined. Exhaustion best predicts fatigue positively, while openness to experience best predicts it negatively. Burnout and certain personality characteristics are good predictors, whereas other variables, such as JCQ and JDS, are weak predictors. Conclusions. This study extends our knowledge of the factors that cause fatigue in professional drivers and underlines the importance of designing interventions aimed at reducing the incidence of fatigue, promoting greater driver well-being and lowering the incidence of accidents.