Predictors of users’ preferences for online health services

The purpose of this study is to explain predictors that discriminate users’ preferences for online health services, focusing on a downtown area in a developing country.

Drawing on rational choice theory (RCT), the authors test a model that links the frequency of online health service usage to access-activators and access-inhibitors. Multivariate analysis of variance (MANOVA) and the discriminant analysis model were used to analyze data from a sample of 215 internet users.

Results confirm the significance of responsiveness, user’s attitude, accessibility and perceived ease of use, indicating their discriminating role in the usage of online health services.

The study demonstrates the relevance of RCT in measuring perceived online health service quality in an emerging context. Future research should consider the influence of electronic health (eHealth) literacy, norms and trustworthiness to increase the generalizability of the findings.

The findings of this study can help enhance the eHealth service quality by encouraging service providers to improve the interactivity and ease of use of their platforms, thus delivering value to both consumers and firms and improving the well-being of the society at large.

Few existing studies draw attention to access-activators and access-inhibitors to predict users’ preferences for online health services. This study shows the applicability of RCT in preparing the instrumental dimensions of online health service quality.