Department of Education Sciences and Psychology, Universitat Rovira i Virgili, Spain.
Department of Economy and Business, Universitat Oberta de Catalunya, Spain.
Int J Occup Saf Ergon. 2022 Sep;28(3):1331-1341. doi: 10.1080/10803548.2021.1888019. Epub 2021 Mar 19.
. 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. . Participants were 509 professional drivers from various transport sectors recruited by non-probabilistic sampling. SPSS version 25.0 was used for statistical analysis. . 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. . 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.
. 职业驾驶员长时间连续驾驶而不休息。除了工作、车辆、环境和驾驶员本身的特点外，这一因素导致了驾驶员疲劳。疲劳是驾驶时最常见的风险因素之一，因为它会导致困倦，降低驾驶员的注意力，并可能导致驾驶员在驾驶时睡着。在本文中，我们使用以下变量为职业驾驶员提出了一个预测模型：年龄、子女数量、工作时间、车内时间、个性、工作特征（JDS）、工作内容（JCQ）和倦怠。. 参与者为来自不同交通部门的 509 名职业驾驶员，采用非概率抽样方法招募。使用 SPSS 版本 25.0 进行统计分析。. 确定了导致驾驶员疲劳的变量的预测能力。倦怠感对疲劳感的正向预测作用最佳，而开放性体验对疲劳感的负向预测作用最佳。倦怠和某些个性特征是很好的预测因素，而其他变量，如 JCQ 和 JDS，则是较弱的预测因素。. 这项研究扩展了我们对导致职业驾驶员疲劳的因素的认识，并强调了设计旨在减少疲劳发生率、促进驾驶员健康和降低事故发生率的干预措施的重要性。
