BMC Medical Informatics and Decision Making (Jul 2024)
Measuring electronic health literacy in the context of diabetes care: psychometric evaluation of a Persian version of the condition-specific eHealth literacy scale for diabetes
Abstract
Abstract Background The rise of the internet and social media has led to increased interest among diabetes patients in using technology for information gathering and disease management. However, adequate eHealth literacy is crucial for protecting patients from unreliable diabetes-related information online. Objective To examine the psychometric characteristics and explore the preliminary validity of the Persian version of the Condition-specific eHealth Literacy Scale for Diabetes (Persian CeHLS-D) to assess eHealth literacy in the context of diabetes care. Methods After adapting, translating, examining content validity, and pilot testing the questionnaire, it was administered to 300 patients with type 2 diabetes mellitus (T2DM). Construct validity was assessed through confirmatory factor analysis, convergent and known-groups validity. The internal consistency (Cronbach’s alpha), composite reliability and maximum reliability, and test-retest correlation were assessed. Results Factor analysis supported the hypothesized two-factor model with 10 items, and the standardized factor loadings ranged from 0.44 to 0.86 (P-values < 0.001). Cronbach’s alpha and test-retest correlation were good for each factor. Convergent validity was confirmed by significant correlations of Persian CeHLS-D with diabetes health literacy, perceived usefulness and importance of using the internet for health information, internet anxiety, and perceived physical and mental health. Know-groups validity determined using groups with different internet-use frequencies, and different attitudes towards providing online healthcare services, were satisfied. Conclusion This study demonstrated the Persian CeHLS-D as a reliable and valid measure of eHealth literacy among patients with T2DM in Iran. Its satisfactory psychometric properties support its use in research and clinical settings to assess eHealth literacy and inform interventions.
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