Decomposition and Comparative Analysis of Urban-Rural Disparities in eHealth Literacy Among Chinese University Students: Cross-Sectional Study.

Background: Mobile health care is rapidly expanding in China, making the enhancement of eHealth literacy a crucial strategy for improving public health. However, the persistent urban-rural divide may contribute to disparities in eHealth literacy between urban and rural university students, potentially affecting their health-related behaviors and outcomes.

Objective: This study aims to examine disparities in eHealth literacy between university students in urban and rural China, identifying key influencing factors and their contributions. The findings will help bridge these gaps, promote social equity, enhance overall health and well-being, and inform future advancements in the digital health era.

Methods: The eHealth Literacy Scale (eHEALS) was used to assess eHealth literacy levels among 7230 university students from diverse schools and majors across 10 regions, including Guangdong Province, Shanghai Municipality, and Jiangsu Province. Descriptive statistics summarized demographic, sociological, and lifestyle characteristics. Chi-square tests examined the distribution of eHealth literacy between urban and rural students. A binary logistic regression model identified key influencing factors, while a Fairlie decomposition model quantified their contributions to the observed disparities.

Results: The average eHealth literacy score among Chinese university students was 29.22 (SD 6.68), with 4135 out of 7230 (57.19%) scoring below the passing mark. Rural students had a significantly higher proportion of inadequate eHealth literacy (2837/4510, 62.90%) compared with urban students (1298/2720, 47.72%; P<.001). The Fairlie decomposition analysis showed that 71.4% of the disparity in eHealth literacy was attributable to urban-rural factors and unobserved variables, while 28.6% resulted from observed factors. The primary contributors were monthly per capita household income (13.4%), exercise habits (11.7%), and 9-item Patient Health Questionnaire (PHQ-9) scores (2.1%).

Conclusions: Rural university students exhibit lower eHealth literacy levels than their urban counterparts, a disparity influenced by differences in socioeconomic status, individual lifestyles, and personal health status. These findings highlight the need for targeted intervention strategies, including (1) improving access to eHealth resources in rural and underserved areas; (2) fostering an environment that encourages physical activity to promote healthy behaviors; (3) expanding school-based mental health services to enhance health information processing capacity; and (4) implementing systematic eHealth literacy training with ongoing evaluation. These strategies will support equitable access to and utilization of eHealth resources for all students, regardless of their geographic location.