2025/11/09 by Rahul Kshatriya, K M Pooja, Yogeshwar V. Navandar +1 · 1 voice
Engineering · Health Professions · Psychology · #Human-Automation Interaction and Safety #Older Adults Driving Studies #Traffic and Road Safety
paper · pdf · doi:10.55329/rffp3251
openalex created_date 2025/11/09 · openalex publication_date 2025/11/09 · openalex updated_date 2026/07/07
The Driver Behaviour Questionnaire (DBQ) is a widely used tool for assessing driving behaviours and their implications for road safety. This study examined the factor structure of the DBQ in an Indian context, where cultural and regulatory conditions may shape aberrant driving patterns differently. Data were collected from 1,665 drivers across multiple states through both online and in-person surveys, with 1,657 valid responses retained after outlier removal. The dataset included 28 DBQ items rated on a 5-point Likert scale, along with demographic variables. Exploratory Factor Analysis (EFA) was conducted to explore alternative two-, three-, and four-factor structures, followed by Confirmatory Factor Analysis (CFA) to evaluate the model fit. EFA suggested a two-factor solution as a simpler data-driven representation; however, it demonstrated weak reliability in one factor and a limited ability to distinguish between constructs. In contrast, the four-factor solution not only explained more variance (37.55%) with balanced reliability across factors, but also aligned with theoretical expectations and prior DBQ research. CFA further confirmed the superiority of the four-factor model, which yielded stronger fit indices (χ²/df = 7.601, CFI = .851, RMSEA = .063) and demonstrated measurement invariance across gender, age, and driving frequency. The four factors—Risky and Rule-Violating Behaviours, Safe and Responsible Driving Practices, Driving Errors and Cognitive Lapses, and Distracted and Emotionally Influenced Driving—offer a robust, culturally adapted framework for understanding driver behaviour in India. This validated structure provides a reliable basis for identifying high-risk behaviours and guiding evidence-based road safety interventions.