Investigation of predictors of air pollution-reducing behaviors among taxi drivers in Tehran based on the health belief model in 2024
DOI: 10.1038/s41598-025-04288-7
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Summary
This study investigates the psychosocial predictors of eco-driving behaviors among taxi drivers in Tehran, Iran, using the Health Belief Model (HBM). The research was motivated by the critical role of the transportation sector in urban air pollution, which accounts for the majority of carbon monoxide, nitrogen oxides, volatile organic compounds, and fine particulate matter emissions in Tehran. Since driving behavior significantly influences fuel consumption and pollutant diffusion, identifying factors that promote eco-driving—a sustainable approach optimizing driving patterns to reduce emissions—is essential for improving air quality in high-pollution megacities. The researchers conducted a cross-sectional, descriptive-analytical study between November 6 and December 2, 2024. The sample consisted of 401 station-based official taxi drivers selected via stratified random sampling from Tehran’s taxi stations; app-based and telephone-dispatched taxis were excluded. Data were collected through structured face-to-face interviews using a validated, researcher-developed questionnaire assessing seven HBM constructs (awareness, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action, and self-efficacy) and eco-driving behaviors. The instrument underwent expert review for content validity and pilot testing for reliability, with Cronbach’s alpha values exceeding 0.70. Statistical analyses included Pearson correlation tests and stepwise multiple regression to determine the predictive power of HBM constructs on eco-driving behaviors. The results indicated that self-efficacy was the strongest predictor of eco-driving behavior (standardized beta = 0.324, p < 0.001), followed by awareness, perceived benefits, and perceived susceptibility. The final regression model, comprising these four predictors, explained 27.1% of the variance in eco-driving behavior (R² = 0.271). While perceived barriers showed a significant negative correlation with eco-driving, it was not retained as a significant predictor in the final model. Similarly, perceived severity and cues to action were excluded from the final model due to non-significant predictive value. Descriptive data revealed that participants scored highest on perceived susceptibility (93.37%) and self-efficacy (87.93%), but lowest on cues to action (39.4%), suggesting a gap in external motivational triggers. The findings underscore the importance of enhancing drivers’ self-efficacy and awareness of the benefits of eco-driving to promote pollution-reducing behaviors. The low scores for cues to action highlight a need for structured educational interventions and accessible awareness campaigns, as drivers currently have limited exposure to such prompts. The study concludes that theory-driven educational programs based on the HBM, specifically targeting self-efficacy and awareness, can effectively encourage eco-driving practices. This approach offers a viable strategy for mitigating urban air pollution by leveraging behavioral interventions among a key demographic in the transportation sector.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | DOAJ | — | — | 1 | 2026-06-10 |
| archive | success | unpaywall | — | — | 1 | 2026-06-25 |
| extract | success | cached | — | — | 2 | 2026-06-25 |
| clean | success | clean | — | — | 1 | 2026-06-11 |
| chunk | success | chunk | — | — | 1 | 2026-06-11 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-11 |
| promote | success | — | — | — | 1 | 2026-06-10 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-25 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-11 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-25; verification: verified.
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