BackgroundThe eHealth Literacy Scale (eHEALS) is the most widely used instrument in health studies to measure individual’s electronic health literacy. Nonetheless, despite the rapid development of the online medical industry and increased rural-urban disparities in China, very few studies have examined the characteristics of the eHEALS among Chinese rural people by using modern psychometric methods. This study evaluated the psychometric properties of eHEALS in a Chinese rural population by using both the classical test theory and item response theory methods.ObjectiveThis study aimed to develop a simplified Chinese version of the eHEALS (C-eHEALS) and evaluate its psychometric properties in a rural population.MethodsA cross-sectional survey was conducted with 543 rural internet users in West China. The internal reliability was assessed using the Cronbach alpha coefficient. A one-factor structure of the C-eHEALS was obtained via principal component analysis, and fit indices for this structure were calculated using confirmatory factory analysis. Subsequently, the item discrimination, difficulty, and test information were estimated via the graded response model. Additionally, the criterion validity was confirmed through hypothesis testing.ResultsThe C-eHEALS has good reliability. Both principal component analysis and confirmatory factory analysis showed that the scale has a one-factor structure. The graded response model revealed that all items of the C-eHEALS have response options that allow for differentiation between latent trait levels and the capture of substantial information regarding participants’ ability.ConclusionsThe findings indicate the high reliability and validity of the C-eHEALS and thus recommend its use for measuring eHealth literacy among the Chinese rural population.

The objectives of this study were to develop the Self-Awareness of Falls in Elderly (SAFE) scale and test its reliability and validity among elderly inpatients. A cross-sectional study design and convenience sampling were used to test the validity and reliability of the SAFE scale. Explanatory factor analysis and confirmatory factor analysis yielded an acceptable goodness of model fit, confirming the 21 items in the SAFE scale that were distributed among four factors: awareness of activity safety and environment, awareness of physical functions, awareness of medication, and awareness of cognitive behavior. The values of interrater reliability and Cronbach's alpha were at least .70, indicating that reliability of the SAFE scale was acceptable. The SAFE scale is the first instrument to measure self-awareness of fall risk among high-risk groups. Further management and fall prevention can then be designed to reduce the incidence of falls among elderly people in clinical care.

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BACKGROUND The eHealth Literacy Scale (eHEALS) is the most widely used instrument in health studies to measure individual’s electronic health literacy. Nonetheless, despite the rapid development of the online medical industry and increased rural-urban disparities in China, very few studies have examined the characteristics of the eHEALS among Chinese rural people by using modern psychometric methods. This study evaluated the psychometric properties of eHEALS in a Chinese rural population by using both the classical test theory and item response theory methods. OBJECTIVE This study aimed to develop a simplified Chinese version of the eHEALS (C-eHEALS) and evaluate its psychometric properties in a rural population. METHODS A cross-sectional survey was conducted with 543 rural internet users in West China. The internal reliability was assessed using the Cronbach alpha coefficient. A one-factor structure of the C-eHEALS was obtained via principal component analysis, and fit indices for this structure were calculated using confirmatory factory analysis. Subsequently, the item discrimination, difficulty, and test information were estimated via the graded response model. Additionally, the criterion validity was confirmed through hypothesis testing. RESULTS The C-eHEALS has good reliability. Both principal component analysis and confirmatory factory analysis showed that the scale has a one-factor structure. The graded response model revealed that all items of the C-eHEALS have response options that allow for differentiation between latent trait levels and the capture of substantial information regarding participants’ ability. CONCLUSIONS The findings indicate the high reliability and validity of the C-eHEALS and thus recommend its use for measuring eHealth literacy among the Chinese rural population.