Individual Differences in Driver Inattention: The Attention-Related Driving Errors Scale

Abstract

Objectives: Driver inattention is one of the most common causes of traffic collisions. The aim of this work was to study the reliability and validity of the Attention-Related Driving Errors Scale (ARDES), a novel self-report measure that assesses individual differences in driving errors resulting from failures of attention. The relationship between driver inattention and general psychological variables that could be connected to these phenomena was also explored. Methods: Participants were a convenience sample of drivers drawn from the general population of Mar del Plata, Argentina (n = 301). Drivers responded to ARDES items, a sociodemographic questionnaire, and several validation measures. The internal structure of ARDES was assessed by factor analysis and internal consistency analysis. Analysis of covariance (ANCOVA) was applied to examine differences in ARDES scores due to sociodemographic variables. Logistic regression analysis was used to determine the association between ARDES and self-reported traffic crashes and tickets. Pearson?s correlations were calculated between ARDES and validation measures. Results: Factor analysis suggested the existence of one underlying factor. The 19 items proved to have discriminative power. The scale?s internal consistency was high (Cronbach?s alpha = .86). ARDES discriminated those who had reported road crashes and traffic tickets from those who had not. Correlations with validation measures were robust and theoretically consistent. Findings suggested that driving errors are strongly associated with general error proneness, lack of attention when performing everyday activities, and dissociative personality traits. Conclusion: The present study provides preliminary evidence for the validity and reliability of the ARDES scores. Further validation studies should be conducted applying other methodologies and sources of information, such as traffic records, driving simulations, or naturalistic methodologies.