Purpose - The increasing importance of electronic health (e-health) has raised the significance of exploring the factors influencing the users' acceptance of e-health applications. There has been an extensive usage of the technology acceptance model (TAM) in e-health applications acceptance research. However, not all TAM relationships are borne out in all the studies. There is a variation in predicted effects in several studies with different user type and application type. The purpose of this paper is to bridge a research gap by providing a holistic view of the e-health applications acceptance research by integrating the findings of existing relevant literature. Design/methodology/approach - A statistical meta-analysis of the effect size of causal relationships between common TAM constructs was conducted on 111 peer-reviewed academic studies published in various journals. Findings - The results confirm the validity and robustness of the TAM in e-health applications acceptance research. Further, a moderator analysis based on user type and e-health application type demonstrated that the effect size of causal relationships between TAM constructs majorly depends on the user type, but not on e-health application type. Research limitations/implications - This research provides a ready reference of the existing studies on e-health applications acceptance to the researchers. Further, if researchers or practitioners want to learn more about the particular user or application type, they may find the results valuable. Practical implications - This research suggests that the general public can be used as the surrogates for patients in e-health applications acceptance research. The implementation strategy found successful for medical staff may not work for general public and patients. This research also suggests ways to enhance acceptance of e-health applications among different user groups. Originality/value - The research is original and is based on the existing literature and its interpretation.