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Individual,business-related,and work environment factors associated with driving tired among taxi drivers in two metropolitan U.S. cities
Institution:1. Center for Transportation Research, University of Tennessee – Knoxville, 600 Henley Street, 309 Conference Center Building, Knoxville, TN 37996-4133, USA;2. Division of Unintentional Injury Prevention, Centers for Disease Control, Atlanta, GA 30030, USA;1. University of Paris VIII and French Institute of Science and Technology for Transport, Development and Networks (Ifsttar), AME-LPC, 25 allée des Marronniers, CS 90508, 78008 VERSAILLES Cedex, France;2. Federal University of Paraná, Department of Psychology, Praça Santos Andrade, 50 – Prédio Histórico da UFPR, Sala 214, CEP 80020-300 Curitiba, Brazil;3. Ifsttar, AME-LPC, 25 allée des Marronniers, CS 90508, 78008 VERSAILLES Cedex, France;1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu,China;2. National Engineering Laboratory of Integrated Transportation Big Data Application Technology, West Park, High-Tech District, Chengdu, China;3. Department of Statistics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, United States;1. Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, Division of Unintentional Injury Prevention, 4770 Buford Highway, Atlanta, GA 30341, United States;2. Oak Ridge Institute for Science and Education, Oak Ridge, TN 37830, United States
Abstract:Introduction: Violence-related events and roadway incidents are the leading causes of injury among taxi drivers. Fatigue is under-recognized and prevalent in this workforce and is associated with both injury outcomes. We describe the association of individual, business-related, and work environment factors with driving tired among taxi drivers in two very different cities. Method: We developed a comprehensive survey for licensed taxi drivers. We trained surveyors to administer the 30-min survey using systematic sampling among taxi drivers waiting for fares in two large U.S. cities: the Southwest (City 1) and the West (City 2). A driving tired scale of the Occupational Driver Behavior Questionnaire was the outcome. Multivariate logistic models described driving tired behavior in city-specific models using adjusted Odds Ratios (ORadj). Results: City 1 and City 2 had 496 and 500 participants, respectively. Each driving tired behavior was significantly more prevalent in City 2 than City 1 (p < .05). There were more variables and a greater diversity of variables in the models describing drowsy driving in City 1 than City 2. In City 1, variables describing negative safety climate (ORadj = 1.15), socio-demographic groups (identifying as Asian, educational attainment), passenger-related violence (ORadj = 1.79), and company tenure (ORadj = 1.15) were associated with driving tired. In City 2, high perceived safety training usefulness (ORadj = 0.48) was associated with driving tired. A risk factor for driving tired that was common to both cities was job demands (ORadj = 1.21 in City 1; 1.43 in City 2). Conclusions: These findings represent two diverse taxi populations driving in two geographically distinct regions that differ in safety regulation. It is important that safety measures that include fatigue awareness training are reaching all drivers. Fatigue management training should be integrated into driver safety programs regardless of location. Practical applications: Fatigue management strategies that recognize individual factors, business-related characteristics, and work environment are an important component of road safety and are particularly relevant for occupational drivers.
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