Investigation of predictors of air pollution-reducing behaviors among taxi drivers in Tehran based on the health belief model in 2024
Abstract Eco-driving behaviors among taxi drivers can significantly contribute to reducing urban air pollution, particularly in megacities such as Tehran. This study aimed to identify the psychosocial predictors of air pollution-reducing behaviors among taxi drivers based on the Health Belief Model...
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-04288-7 |
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| author | Mohammadreza Mokhtari Farkhondeh Amin Shokravi Hassan Shahbazi |
| author_facet | Mohammadreza Mokhtari Farkhondeh Amin Shokravi Hassan Shahbazi |
| author_sort | Mohammadreza Mokhtari |
| collection | DOAJ |
| description | Abstract Eco-driving behaviors among taxi drivers can significantly contribute to reducing urban air pollution, particularly in megacities such as Tehran. This study aimed to identify the psychosocial predictors of air pollution-reducing behaviors among taxi drivers based on the Health Belief Model (HBM). A cross-sectional descriptive-analytical study was conducted in late 2024 with 401 taxi drivers in Tehran, using structured face-to-face interviews. A validated questionnaire assessed seven HBM constructs and eco-driving behaviors. Pearson correlation and stepwise multiple regression analyses were applied. The findings revealed that self-efficacy was the strongest predictor of eco-driving behavior (β = 0.324, p < 0.001), followed by awareness, perceived benefits, and perceived susceptibility. The final regression model explained 27.1% of the variance in eco-driving behavior (R 2 = 0.271). Although perceived barriers showed a significant negative correlation with eco-driving, it was not a significant predictor in the final model. These results highlight the importance of enhancing drivers’ self-efficacy and awareness of eco-driving benefits, while addressing motivational and contextual barriers. Developing targeted, theory-driven educational interventions based on the HBM may play a critical role in promoting eco-driving practices and improving air quality in high-pollution urban environments. |
| format | Article |
| id | doaj-art-02a707d8ff8a429fb0c016c748e87973 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-02a707d8ff8a429fb0c016c748e879732025-08-20T04:01:36ZengNature PortfolioScientific Reports2045-23222025-07-0115111110.1038/s41598-025-04288-7Investigation of predictors of air pollution-reducing behaviors among taxi drivers in Tehran based on the health belief model in 2024Mohammadreza Mokhtari0Farkhondeh Amin Shokravi1Hassan Shahbazi2 Health Education and Promotion, Faculty of Medical Sciences, Tarbiat Modares University Health Education and Promotion, Faculty of Medical Sciences, Tarbiat Modares University Health Education and Promotion, Faculty of Medical Sciences, Tarbiat Modares UniversityAbstract Eco-driving behaviors among taxi drivers can significantly contribute to reducing urban air pollution, particularly in megacities such as Tehran. This study aimed to identify the psychosocial predictors of air pollution-reducing behaviors among taxi drivers based on the Health Belief Model (HBM). A cross-sectional descriptive-analytical study was conducted in late 2024 with 401 taxi drivers in Tehran, using structured face-to-face interviews. A validated questionnaire assessed seven HBM constructs and eco-driving behaviors. Pearson correlation and stepwise multiple regression analyses were applied. The findings revealed that self-efficacy was the strongest predictor of eco-driving behavior (β = 0.324, p < 0.001), followed by awareness, perceived benefits, and perceived susceptibility. The final regression model explained 27.1% of the variance in eco-driving behavior (R 2 = 0.271). Although perceived barriers showed a significant negative correlation with eco-driving, it was not a significant predictor in the final model. These results highlight the importance of enhancing drivers’ self-efficacy and awareness of eco-driving benefits, while addressing motivational and contextual barriers. Developing targeted, theory-driven educational interventions based on the HBM may play a critical role in promoting eco-driving practices and improving air quality in high-pollution urban environments.https://doi.org/10.1038/s41598-025-04288-7Air pollutionDriversHealth belief modelEco-driving |
| spellingShingle | Mohammadreza Mokhtari Farkhondeh Amin Shokravi Hassan Shahbazi Investigation of predictors of air pollution-reducing behaviors among taxi drivers in Tehran based on the health belief model in 2024 Scientific Reports Air pollution Drivers Health belief model Eco-driving |
| title | Investigation of predictors of air pollution-reducing behaviors among taxi drivers in Tehran based on the health belief model in 2024 |
| title_full | Investigation of predictors of air pollution-reducing behaviors among taxi drivers in Tehran based on the health belief model in 2024 |
| title_fullStr | Investigation of predictors of air pollution-reducing behaviors among taxi drivers in Tehran based on the health belief model in 2024 |
| title_full_unstemmed | Investigation of predictors of air pollution-reducing behaviors among taxi drivers in Tehran based on the health belief model in 2024 |
| title_short | Investigation of predictors of air pollution-reducing behaviors among taxi drivers in Tehran based on the health belief model in 2024 |
| title_sort | investigation of predictors of air pollution reducing behaviors among taxi drivers in tehran based on the health belief model in 2024 |
| topic | Air pollution Drivers Health belief model Eco-driving |
| url | https://doi.org/10.1038/s41598-025-04288-7 |
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