The Relation Between the Driver Behavior Questionnaire, Demographics, and Driving History

Donmez, Birsen; Mehler, Alea; Lee, Joonbum; Mehler, Bruce; Reimer, Bryan · 2017 · Crossref

DOI: 10.17077/drivingassessment.1623

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Summary

This study investigates the relationships between self-reported driving behaviors, demographic factors, and driving history, specifically focusing on crashes, citations, and warnings. The research addresses a gap in previous literature by utilizing a large, demographically balanced sample to statistically control for age and gender, which are known to influence both driver behavior and crash risk. The authors aim to determine if specific driving behaviors, as measured by the Driver Behavior Questionnaire (DBQ), predict negative driving outcomes independent of these demographic variables. The analysis utilized data from 562 drivers (288 female, 274 male) aged 20–69, recruited from eastern Massachusetts for on-road studies conducted between 2012 and 2015. Participants completed intake questionnaires reporting their demographics, education, and the frequency of crashes, citations, and warnings received over the past five years. Driving behaviors were assessed using the U.S. version of the DBQ, which measures three subscales: Errors (misjudgments), Lapses (absent-minded behaviors), and Violations (deliberate contraventions of rules). Logistic regression models were employed to analyze the associations between DBQ scores and driving history while controlling for age and gender. The results indicated that age and gender significantly influenced both DBQ scores and driving history. Drivers aged 20–24 reported higher odds of crashes and citations compared to older groups, while males reported higher citation rates than females. Regarding DBQ subscales, younger drivers scored higher on violations, whereas females scored higher on errors and lapses. Crucially, when controlling for demographics, higher violation scores were positively associated with increased likelihoods of self-reported crashes and citations. For warnings, higher scores in both violations and lapses were positively associated with receiving a warning, whereas higher error scores were inversely associated with warnings. The findings confirm that deliberate violations are a significant predictor of crashes and citations, even after accounting for age and gender. The study highlights the importance of using large, balanced samples to isolate behavioral effects from demographic confounds. The authors note that while the sample may not be fully representative of the general population due to recruitment criteria and self-reporting biases, the results reinforce the validity of the DBQ as a tool for assessing risky driving behaviors. The inverse relationship between error scores and warnings suggests a need for further investigation into how unintentional errors are perceived or penalized compared to deliberate violations.

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Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• dbq psychometrics
• sex gender
• human error taxonomy
• cultural cross national
• incidence prevalence
• novice drivers

Information type

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• Empirical Findings: observational prevalence, crash risk outcomes
• Methodological Resource: dataset resource