Abstract
E-bikes have gained significant popularity in China from their convenience and eco-friendliness, but the lack of helmet use among riders poses serious head injury risks. This study evaluated the effectiveness of safety campaigns and educational initiatives in promoting helmet adoption among e-bike riders in Guangdong Province, China, across three perceived effectiveness levels: ineffective, moderately effective, and effective. Data from a questionnaire survey were analyzed using an optimized eXtreme Gradient Boosting (XGBoost) model, with hyperparameters tuned via Optuna and performance validated through 10-fold cross-validation, achieving 84.6% accuracy. Class imbalance was addressed using the synthetic minority over-sampling technique, yielding macro-averaged precision, recall, and F1-scores of approximately 0.82, indicating balanced predictive performance. Model interpretability with SHapley Additive exPlanations (SHAP) identified safety education frequency, enforcement of helmet use, riding experience, ideal education locations, attitudes toward helmet use, and age group as the most influential predictors of helmet adoption effectiveness. Safety education frequency contributed most at the ineffective (25.36%) and effective (18.65%) levels, while enforcement was most influential at the moderately effective level (19.11%), with persuasion-plus-fines outperforming education-only strategies. Partial dependence plots (PDPs) and individual conditional expectation (ICE) plots showed that monthly or quarterly education substantially improves perceived effectiveness, whereas infrequent or no education increases perceived ineffectiveness. Younger riders (under 25 years) and those with negative helmet attitudes were more likely to perceive initiatives as ineffective. Findings highlight actionable recommendations: institutionalizing frequent safety education in high-impact locations, integrating enforcement with education, and tailoring interventions to demographic and attitudinal profiles, offering policymakers evidence-based approaches to enhance helmet adoption and rider safety.
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