Urban-Rural Differences in Pedestrians' Unsafe Behaviors: A Multigroup SEM Based on the Health Belief Model

• Applied HBM to examine pedestrian risk behavior in urban and rural Thailand. • Identified six-factor model of unsafe pedestrian behavior via EFA and CFA. • Conducted multi-group SEM to compare psychological drivers across contexts. • Perceived barriers were key predictors in urban, benefits in rural pedestrians. • Findings support context-specific interventions for pedestrian safety policies. Pedestrian safety remains a critical public health concern, particularly in low- and middle-income countries like Thailand, where rapid urbanization and infrastructure disparities contribute to elevated pedestrian crash risks. This study investigates unsafe pedestrian behavior across urban and rural contexts using a multi-group Structural Equation Modeling (SEM) approach grounded in the Health Belief Model (HBM). Data were collected from 1600 respondents across 16 Thai provinces, with equal representation from urban and rural populations. The analysis identified six key dimensions of pedestrian behavior: violations, errors, lapses, social media use, aggressive behavior, and positive behavior. Exploratory and confirmatory factor analyses confirmed a consistent six-factor structure across both contexts, while multi-group SEM revealed significant differences in psychological determinants. In urban areas, perceived barriers and susceptibility were the strongest predictors, with social media distraction being the most influential behavioral component. In contrast, rural pedestrian behavior was more strongly influenced by perceived benefits and health motivation, with aggressive behavior and violations posing greater risks. These findings underscore the need for context-sensitive interventions. Urban strategies should address perceived barriers and risk perception, whereas rural interventions should emphasize the benefits of safe behavior and promote health-conscious attitudes. This study extends the application of HBM in transportation research, highlights the psychological underpinnings of pedestrian risk, and offers evidence-based guidance for geographically tailored pedestrian safety policies and educational campaigns.

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Publication Details

Journal
Sustainable Futures
Published
2025-09-27
DOI
https://doi.org/10.1016/j.sftr.2025.101375
Citations
1
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
1.30
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article

Urban-Rural Differences in Pedestrians' Unsafe Behaviors: A Multigroup SEM Based on the Health Belief Model

Manlika Seefong, Thanapong Champahom, Panuwat Wisutwattanasak, Kestsirin Theerathitichaipa et al.
1 citations
Sustainable Futures
Traffic and Road Safety
1.30
article

Urban-Rural Differences in Pedestrians' Unsafe Behaviors: A Multigroup SEM Based on the Health Belief Model

Manlika Seefong, Thanapong Champahom, Panuwat Wisutwattanasak, Kestsirin Theerathitichaipa, Vatanavongs Ratanavaraha, Sajjakaj Jomnonkwao
article en
1 citations

Abstract

• Applied HBM to examine pedestrian risk behavior in urban and rural Thailand. • Identified six-factor model of unsafe pedestrian behavior via EFA and CFA. • Conducted multi-group SEM to compare psychological drivers across contexts. • Perceived barriers were key predictors in urban, benefits in rural pedestrians. • Findings support context-specific interventions for pedestrian safety policies. Pedestrian safety remains a critical public health concern, particularly in low- and middle-income countries like Thailand, where rapid urbanization and infrastructure disparities contribute to elevated pedestrian crash risks. This study investigates unsafe pedestrian behavior across urban and rural contexts using a multi-group Structural Equation Modeling (SEM) approach grounded in the Health Belief Model (HBM). Data were collected from 1600 respondents across 16 Thai provinces, with equal representation from urban and rural populations. The analysis identified six key dimensions of pedestrian behavior: violations, errors, lapses, social media use, aggressive behavior, and positive behavior. Exploratory and confirmatory factor analyses confirmed a consistent six-factor structure across both contexts, while multi-group SEM revealed significant differences in psychological determinants. In urban areas, perceived barriers and susceptibility were the strongest predictors, with social media distraction being the most influential behavioral component. In contrast, rural pedestrian behavior was more strongly influenced by perceived benefits and health motivation, with aggressive behavior and violations posing greater risks. These findings underscore the need for context-sensitive interventions. Urban strategies should address perceived barriers and risk perception, whereas rural interventions should emphasize the benefits of safe behavior and promote health-conscious attitudes. This study extends the application of HBM in transportation research, highlights the psychological underpinnings of pedestrian risk, and offers evidence-based guidance for geographically tailored pedestrian safety policies and educational campaigns.

Sustainable FuturesVol. 10
Rajamangala University of Technology Isan (TH), Suranaree University of Technology (TH)
Openalex Percentile: Top 17%
Traffic and Road Safety
1.30
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