JMIR Publications

ABSTRACT

Background:

With the growth of the Internet, patients tend to choose the Internet as their first source of information on their health conditions before seeking professional advice. However, in China, the lack of a valid instrument to evaluate patients’ eHealth literacy complicates government efforts to provide information on health and healthcare to patients in a way they can understand and use to improve health outcomes.

Objective:

The aim of this study was to examine the psychometric properties of a Simplified Chinese version of the eHealth Literacy Scale (SC-eHEALS).

Methods:

Data used for analysis in this study came from a cross-sectional survey conducted in eight hospitals in Guangdong, China. Confirmatory factor analysis (CFA) was used to examine the structure of the SC-eHEALS. Methods based on the classical test theory (CTT) and the item response theory (IRT) were adopted to evaluate the psychometric properties of the SC-eHEALS. Cronbach’s alphas, item-total correlation coefficients, and alpha values if items were deleted from the SC-eHEALS were reported. Associations with ICECAP-A and overall health condition were estimated to confirm the concurrent validity of the SC-eHEALS. A general partial credit model was used to perform the IRT analysis. Difficulty, discrimination, and fit for each item were reported. Item-category characteristic curves (ICCs) and item and test information curves were used to graphically present the validity and reliability of the SC-eHEALS. Differential item functioning (DIF) was used to check for the possible item bias caused by the responses of the different subgroups.

Results:

Overall, 574 patients completed the SC-eHEALS. CFA suggested the performance of 4-factor model was better than the other three models. The Cronbach’s alpha (α) was 0.96, no item had the α lower than 0.95. The item-total correlation coefficients ranged between 0.86 and 0.91. Item 8 and 4 had the lowest and highest mean score among all. The correlation coefficients between SC-eHEALS and ICECAP and overall health condition were mild to moderate. The discrimination of SC-eHEALS ranged between 2.63 and 5.42. ICCs indicated that the order of categories’ thresholds for all the items were good. In total, 70% of the information provided by the SC-eHEALS was below the average level of the latent trait. DIF was found for Item 6 when considering the responses of different age groups.

Conclusions:

SC-eHEALS was demonstrated to have good psychometric properties and can therefore be used to evaluate people’s eHealth literacy in China.