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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Main Authors: Mohammadreza Mokhtari, Farkhondeh Amin Shokravi, Hassan Shahbazi
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
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.
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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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AT hassanshahbazi investigationofpredictorsofairpollutionreducingbehaviorsamongtaxidriversintehranbasedonthehealthbeliefmodelin2024