Validation of Driver Behavior Questionnaire on Nigerian Truck Drivers: A Structural Equation Modeling Approach
DOI: 10.55463/issn.1674-2974.50.1.13
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Summary
This study addresses the critical need for a validated measurement tool to assess the driving behaviors of commercial truck drivers in Nigeria, a population significantly involved in fatal road traffic accidents (RTAs). While the Driver Behavior Questionnaire (DBQ) is widely used globally, its validity and reliability for specific driver subgroups, particularly Nigerian truck drivers, had not been established using structural equation modeling (SEM). Given that human behavior contributes to over 80% of RTAs and truck crashes cause disproportionate fatalities and economic losses, the authors aimed to validate the DBQ to enable consistent assessment of risky driving behaviors and support safety interventions. The researchers employed a cross-sectional survey design, collecting data from 880 commercial truck drivers purposively selected from major transit hubs in Nigeria between April and October 2022. The instrument was a 30-item DBQ adapted from previous studies, measuring four constructs: driving violations, driving errors, inattention errors, and positive driving behaviors. Items were rated on a five-point Likert scale. Data analysis was conducted using SPSS for descriptive statistics and SmartPLS4 for Structural Equation Modeling. The study evaluated the measurement model’s reliability using composite reliability and Cronbach’s alpha, and its validity through Average Variance Extracted (AVE) for convergent validity and the Heterotrait-Monotrait (HTMT) ratio for discriminant validity. The results demonstrated that the DBQ is both reliable and valid for this specific population. After removing items with low loadings to meet validity thresholds, the final model showed composite reliability values ranging from 0.738 to 0.877, exceeding the 0.7 threshold. Convergent validity was established with AVE values above 0.5 for all constructs (Driving Errors: 0.560; Driving Violations: 0.560; Inattention Errors: 0.522; Positive Driving Behavior: 0.648). Discriminant validity was confirmed as all HTMT ratios were below the 0.9 threshold. Specific findings indicated that "disregarding speed limits on residential roads" had the highest loading for violations, while "switching on the wrong control" was the most prominent inattention error. The significance of this study lies in providing a psychometrically sound tool for evaluating the driving behaviors of Nigerian commercial truck drivers. The validated DBQ can be utilized for targeted driver training, policy development, and further research aimed at reducing RTAs. The authors conclude that SEM offers a more robust assessment than traditional methods and recommend validating the DBQ for other commercial driver groups, such as taxi and bus drivers, to address broader traffic safety challenges in Nigeria.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | pdftotext | — | — | 4 | 2026-08-10 |
| clean | success | clean | — | — | 2 | 2026-08-10 |
| chunk | success | chunk | — | — | 2 | 2026-08-10 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 2 | 2026-08-10 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 17 | 2026-08-11 |
| verify | partial | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified_with_issues.
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Information type
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- Empirical Findings: observational prevalence
- Methodological Resource: validation psychometrics
- Theoretical Contribution: computational model