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Citation |
Campos CI, Pitombo CS, Delhomme P, Ferreira S. Case Stud. Transp. Policy 2021; 9(4): 1746-1756. |
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Copyright |
(Copyright © 2021, World Conference on Transport Research Society, Publisher Elsevier Publishing) |
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DOI |
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PMID |
unavailable |
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Abstract |
Brazil and Portugal are historically related; however, they differ regarding at least economic development, infrastructure, and road safety. Identifying risk behaviors contributes to supporting actions focused on the human factor to mitigate crashes. In this study, as part of an electronic survey, we examined the risk behaviors that drivers from Brazil (n = 1,354) and Portugal (n = 348) self-reported adopting while driving. We used the short version of the Driver Behavior Questionnaire (DBQ) and a specific scale for risk behaviors (Updated Risk Behavior Items - URBI) developed by the authors. We identified risk behaviors for the two countries through an exploratory validation approach (Categorical Principal Component Analysis - CATPCA). We used the self-reported data and CATPCA technique, considering interpretability, variance explained, cross-loading, Cronbach Alpha and Spearman correlation. The exploratory analysis resulted in a structure with 22-items from DBQ and URBI scales organized in seven dimensions representing the risk behaviors: Errors, Speeding, Driving under the influence of alcohol, Seat Belt Not-wearing, Cell phone use while driving in hands-free mode, Fatigue, and Driver Anger Expression. Our approach enables us to identify the risk behaviors among Brazilian and Portuguese drivers from DBQ and URBI. The URBI items made it possible to update the risk behavior scale considering the driver's behavior related to alcohol, fatigue, cell phone and use of seat belts. The quality of road infrastructure and legislation on drinking and driving could explain the difference in crash involvement due to speeding behavior and driving under the influence of alcohol in each country. Language: en |
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Keywords |
Drivers risk behavior; E-survey; Non-linear principal component analysis; Validity |