Validity and reliability of the Chinese version of digital health readiness questionnaire among hypertension patients in rural areas of China

• Published in: Digital health 2024-01, Vol.10, p.20552076231216604-20552076231216604
• Main Authors: Xu, Linqi, Yu, Tianzhuo, Leng, Xin, Yu, Tianyue, Scherrenberg, Martijn, Falter, Maarten, Kaihara, Toshiki, Kizilkilic, Sevda Ece, Van Erum, Hanne, Kindermans, Hanne, Dendale, Paul, Tong, Qian, Li, Feng
• Format: Article
• Language: English
• Subjects: Health education; Health literacy; Hypertension; Questionnaires; Rural areas
• ISSN: 2055-2076; 2055-2076
• DOI: 10.1177/20552076231216604

Introduction Digital health has the potential to support health care in rural areas by overcoming the problems of distance and poor infrastructure, however, rural areas have extremely low use of digital health because of the lack of interaction with technology. There is no existing tool to measure digital health literacy in rural China. This study aims to test and validate the digital health readiness questionnaire for assessing digital readiness among patients in rural China. Methods Due to the different Internet environments in China compared to Belgium, a cultural adaptation is needed to optimize the use of Digital Health Readiness Questionnaire in China. Then, a prospective single-center survey study was conducted in rural China among patients with hypertension. Confirmatory factor analysis was computed to test the measurement models. Results A total of 330 full questionnaires were selected and included in the analysis. The model-fit measures were used to assess the model's overall goodness of fit (Chi-square/degrees of freedom = 5.060, comparative fit index = 0.889, Tucker–Lewis index (TLI) = 0.869, root mean square error of approximation (RMSEA) = 0.111, standardized root mean square residual (SRMR) = 0.0880). TLI is a little bit lower than the borderline (more than 0.9) and RMSEA is higher than it (less than 0.08 means good model fit). We deleted two items 2 and 4 and the result shows a better goodness of fit (Chi-square/degrees of freedom = 4.897, comparative fit index = 0.914, TLI = 0.895, RMSEA = 0.109, SRMR = 0.0765) Conclusion To increase applicability and generalizability in rural areas, it should be considered to use the calculation of only the parts Digital skills, Digital literacy and Digital health literacy which are equally applicable in a Belgian population as in a rural Chinese population.