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BackgroundeHealth resources and interventions promise to promote favorable behavior change, self-efficacy, and knowledge acquisition, thereby improving health literacy. However, individuals with limited eHealth literacy may find it difficult to identify, understand, and benefit from eHealth use. It is necessary to identify the self-assessed eHealth literacy of those who use eHealth resources to classify their eHealth literacy levels and to determine the demographic characteristics associated with higher and lower eHealth literacy skills. ObjectiveThis study aimed to identify notable factors closely associated with limited eHealth literacy among Chinese male populations to provide some implications for clinical practice, health education, medical research, and public health policy making. MethodsWe hypothesized that participants’ eHealth literacy status was associated with various demographic characteristics. Therefore, we elicited the following information in the questionnaire: age and education, self-assessed disease knowledge, 3 well-developed health literacy assessment tools (ie, the All Aspects of Health Literacy Scale, eHealth Literacy Scale, and General Health Numeracy Test), and the 6 Internal items on health beliefs and self-confidence in the Multidimensional Health Locus of Control Scales. Using randomized sampling, we recruited survey participants from Qilu Hospital of Shandong University, China. After validating the data collected through a web-based questionnaire survey via wenjuanxing, we coded all valid data according to predefined coding schemes of Likert scales with different point (score) ranges. We then calculated the total scores of the subsections of the scales or the entire scale. Finally, we used logistic regression modeling to associate the scores of the eHealth Literacy Scale with the scores of the All Aspects of Health Literacy Scale, the General Health Numeracy Test-6, and age and education to ascertain factors considerably associated with limited eHealth literacy among Chinese male populations. ResultsAll data from the 543 returned questionnaires were valid according to the validation criteria. By interpreting these descriptive statistics, we found that 4 factors were significantly correlated with participants’ limited eHealth literacy: older age, lower education attainment, lower levels of all aspects of health literacy (functional, communicative, and critical), and weaker beliefs and self-confidence in internal drivers and strengths to stay healthy. ConclusionsBy applying logistic regression modeling, we ascertained 4 factors that were significantly correlated with limited eHealth literacy among Chinese male populations. These relevant factors identified can inform stakeholders engaging in clinical practice, health education, medical research, and health policy making. |
