Abstract
PurposeThe 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/approachA 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.FindingsThe 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/implicationsThis 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 implicationsThis 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/valueThe research is original and is based on the existing literature and its interpretation.
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