A meta-analysis of e-health applications acceptance

Abstract

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.

Healthcare at Your Fingertips: The Acceptance and Adoption of Mobile Medical Treatment Services among Chinese Users

“…Similar to previous studies that applied the TAM in the context of general mHealth applications [21,49,67,68], the current results emphasized that the users' perceived usefulness and perceived ease of use together significantly influenced their attitude toward using MMT services, which further affected their intention to use such services in the future. However, in contrast to the findings of some previous studies [21,[68][69][70], the present work found that users' perceived ease of use of MMT services did not have a significant influence on their perceived usefulness. This might be because users who have already experimented with MMT services do not regard ease of use as a major consideration when weighing possible benefits and risks brought by such services.…”

“…Theoretically, this study validated the robustness of the TAM in predicting users' acceptance and adoption intention of MMT services. Compared with previous studies that focused on general eHealth and mHealth services [17,70], the current findings more precisely reflect the acceptance behavior for online medical treatment in the field of mHealth. Furthermore, the findings identified the significant influences of additional factors, such as technology anxiety, trust, privacy concerns, personalization, and interactivity, which highlight the necessity of extending the TAM by emphasizing these unique variables and features in the context of mHealth.…”

Digitalization and Physician Learning

“…54 The primary health care focus has been on electronic health records 55 and specific eHealth applications. 56 Other applications are relatively neglected. 54 , 57 …”

Fear of Covid-19 and Intentions towards Adopting E-Health Services: Exploring the Technology Acceptance Model in the Scenario of Pandemic

“…Therefore, it is strongly suggested to gather information from Covid-19 patients and physicians to investigate the effect of the e-health system on patient care and relationships between doctors and patients. As mentioned by Chauhan and Jaiswal (2017) sufferers and the local population developed diverse views and practices regarding the use and benefits of e-health systems. Second, the model was validated using data obtained in Pakistan, which could be considered a research constraint (Zhang, Rasheed, & Luqman, 2019).…”