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Cross-sectional study finds that behavioral factors predict digital health literacy in medical undergraduates, indicating a need for targeted training.
Background Digital health literacy (DHL) is a core competency for future healthcare workers, yet its predictors determinants among medical undergraduates in Central China remain unclear. Methods A cross-sectional study was conducted among 1,130 medical undergraduates in Anhui Province using stratified cluster sampling. DHL was assessed using the validated Chinese version of the eHealth Literacy Scale (eHEALS). Hierarchical multiple linear regression was used to identify independent predictors of DHL. Results The mean DHL score was 29.78 ± 5.57, indicating a moderate level. After adjusting for confounders, health information retrieval efficiency, authoritative source identification ability, and reliance on professional medical databases were the strongest positive predictors of DHL. Sociodemographic factors showed no significant independent association with DHL. Conclusions DHL among medical undergraduates is primarily predicted by modifiable behavioral factors rather than innate sociodemographic backgrounds. Universal competency-oriented training programs are needed to improve DHL in this critical public health workforce.
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Wang et al. (2026) studied this question.
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