About the research
This study set out to demonstrate that responses to the Driver Behaviour Questionnaire (DBQ) predict driving accidents, and then to estimate the predictive correlations of the questionnaire’s errors and violations factors with regard to both self-reported and registered accidents. The effects of age, gender, and exposure (mileage and hours driven per week) were evaluated as well, as these variables are known confounders of accident involvement.
Using a meta-analysis, this study accurately determined the overall DBQ-to-accident relationship in a total sample of more than 45,000 respondents. The findings show that the DBQ significantly predicts self-reported accidents for both errors and violations, and that the DBQ is able to make prospective as well as retrospective predictions of self-reported accidents.
The meta-analysis also showed that errors and violations correlated negatively with age and positively with exposure. Also, men reported fewer errors and more violations than women. The violation-to-accident correlation was strongest among young drivers.
Methodology
The researchers conducted a literature search to recover studies that used the DBQ. They then noted the correlations between the DBQ factor scores and the following six criteria in each sample, when available:
- self-reported number of accidents
- recorded number of accidents
- gender
- age
- mileage
- hours driven per week
The DBQ factors per sample were coded into errors, violations, and other factors. The meta-analysis was conducted per predictor variable (DBQ errors and DBQ violations), per criterion (number of self-reported accidents, number of recorded accidents, age, gender, mileage, and hours driven per week), and per correlation type (zero-order effects reported in a table, typically a correlation matrix, and effects in multivariate analysis, in a table omitting the insignificant effects, or in the text of a study).
Publications
This study was published as The Driver Behaviour Questionnaire as a predictor of accidents: A meta-analysis, Journal of Safety Research, December 2010.