eHealth Literacy and Depressive Symptoms Among Adults Aged 50 Years and Older in China: A National Cross‐Sectional Study

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Abstract
Objective: Despite existing research confirming that eHealth literacy promotes healthy lifestyles and subjective well‐being among adults aged 50 years and older, its connection to depressive symptoms remains unclear. This cross‐sectional study explored the association between eHealth literacy and depressive symptoms among adults aged 50 years and older, and investigated potential mechanisms and moderating effects of the association. Methods: Data were obtained from the China Digital Divide and Digital Inclusion Survey (CDDDIS), which provided a nationally representative sample of 4284 participants aged 50 years and older. Ordinary least squares (OLS) regression was employed to analyze the associations between eHealth literacy and depressive symptoms, adjusting for relevant sociodemographic and health‐related covariates. Bootstrap‐based mediation analysis was conducted to evaluate indirect pathways embedded within the correlation network. Income‐stratified analyses were performed to explore differences in the association across income groups. Results: The results revealed that higher eHealth literacy was significantly correlated with fewer depressive symptoms ( β = −0.029, 95% CI = [−0.052, −0.006], p = 0.012). Bootstrapped mediation analysis revealed that physical activity and perceived stress served as significant indirect pathways mediating the association in this correlational analysis, whereas the indirect pathway via online healthcare services utilization was not statistically significant. Income‐stratified analysis showed that the negative association between eHealth literacy and depressive symptoms was statistically significant among middle‐ and high‐income participants, whereas no significant association was observed for low‐income participants. Conclusions: eHealth literacy constitutes a critical resource for promoting healthy aging and mitigating aging‐related stressors among adults aged 50 years and older. These correlational patterns suggest potential utility for targeted eHealth interventions aimed at reducing depressive symptoms in aging populations.
Funding Information
  • National Natural Science Foundation of China (72504278)
  • National Natural Science Foundation of China (72404274)
  • Fundamental Research Funds for the Central Universities
  • National Social Science Fund of China (24&ZD167)

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