Utilising the Driver Behaviour Questionnaire in an Australian Organisational Fleet Setting: Can It Identify Risky Drivers?

Abstract

In this study the Manchester Driver Behaviour Questionnaire (DBQ) was employed in an Australian fleet setting to examine the self-reported driving behaviours of a group of professional drivers (N = 4792). Participants agreed to complete surveys advertised through the internal mail system. Analysis of the DBQ revealed a three factor solution with two of these factors consisting of a combination of both aggression and highway code violations from the original DBQ. The results indicate that further to the driving error construct common to both the original and present study’s DBQ factor structures, the two additional factors are most accurately represented by aberrant driving behaviours involving low-level aggression and serious highway code violations. Logistic regression analysis revealed that, of the traditional DBQ factors, driving errors was the only significant predictor of self-reported crashes after controlling for driving exposure. However, similar analysis with the modified DBQ factors revealed that both driving errors made and low-level aggression were significant predictors of self-reported crashes. This paper further outlines the major findings of the study, highlights implications regarding professional drivers’ involvement with aberrant driving behaviours in fleet-based settings and considers the utility of self-report measures to identify “at risk” drivers.