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Journal Article

Citation

Rolison JJ. Accid. Anal. Prev. 2019; 135: e105390.

Affiliation

Department of Psychology, University of Essex, UK. Electronic address: jrolison@essex.ac.uk.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.aap.2019.105390

PMID

31830709

Abstract

Worldwide, road crashes are a major course of death and serious injury. Police reports provide a rich source of data on the proximal causes (e.g., impairment by alcohol, failure to look properly) of road traffic collisions. Yet, road safety research has raised concerns about the quality and reliability of police reported data. In the UK crash report form, contributory factors are categorised (e.g., vehicle defects, driver error or reaction) to aid police officers in identifying appropriate factors. However, discord between the classification of contributory factors in crash reports and police officers' own categorical perceptions may lead to misunderstanding, and in turn, misreporting of contributory factors. The current investigation recruited 162 police officers to report their perceptions of the relations among contributory factors in the UK crash report form. Hierarchical clustering analysis was used to identify an optimal category structure based on police officers' perceptions. The clustering analysis identified a classification system with seven or eleven categories of contributory factors, maximising the internal coherence of categories and minimising discord with police officers' perceptions. The findings also yield new insights into police officers' perceptions of crash causation and demonstrate how statistical techniques can be used to inform the design of road traffic collision report forms.

Copyright © 2019 The Author. Published by Elsevier Ltd.. All rights reserved.


Language: en

Keywords

Contributory factors; Crash causation; Crash reporting; Policymaking; Road safety

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