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Assessing the effect of inattention-related error and anger in driving on road accidents among Iranian heavy vehicle drivers

Shams, Z ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1016/j.iatssr.2020.09.005
  3. Publisher: Elsevier B.V , 2021
  4. Abstract:
  5. Extensive studies have examined the effect of variables such as demographic characteristics, insomnia, and working conditions of drivers individually on inattention-related error as well as expression of anger in driving. Nevertheless, so far no study has tested the concurrent effect of these factors on crashes. This study has dealt with indirect investigation of the effect of variables including demographic characteristics, insomnia, and working conditions of drivers on inattention-related error and expression of anger in driving (as mediation model). Next, the effect of these two variables on the probability of incidence of road crashes has been assessed among truck drivers. For this purpose, 780 Iranian truck drivers were interviewed by validated questionnaires including insomnia severity index (ISI), attention related driving errors scale (ARDES), and driving anger expression (DAX). To confirm the validity of these questionnaires, confirmatory factor analysis (CFA) was used. Next, structural equation modeling (SEM) was employed for investigating the relationships between these latent variables and truck drivers' demographic characteristics, working conditions and their crash involvement. SEM results indicated that as the severity of insomnia among drivers increased, they committed more inattention-related errors, and also expressed more anger during driving. Generally, the results of this study indicated that with increase in the extent of experience and safety knowledge of drivers and improvement in their working conditions and their sleep status, it is possible to reduce inattention-related error and expression of anger during driving among heavy vehicle drivers. © 2020 International Association of Traffic and Safety Sciences
  6. Keywords:
  7. Errors ; Factor analysis ; Highway accidents ; Population statistics ; Roads and streets ; Truck drivers ; Trucks ; Confirmatory factor analyses (CFA) ; Crash involvement ; Demographic characteristics ; Driving errors ; Heavy vehicle drivers ; Latent variable ; Safety knowledge ; Structural equation modeling ; Surveys
  8. Source: IATSS Research ; Volume 45, Issue 2 , 2021 , Pages 210-217 ; 03861112 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S0386111220300777