Accepted for/Published in: JMIR Medical Education
Date Submitted: Oct 23, 2024
Open Peer Review Period: Oct 23, 2024 - Dec 18, 2024
Date Accepted: May 12, 2025
(closed for review but you can still tweet)
Technology Acceptance Model in Medical Education: A systematic review
ABSTRACT
Background:
The growing use of technology means that there is a need for a framework that can evaluate the learners’ and educators’ acceptance of these technologies. In this context, the Technology Acceptance Model (TAM) offers a valuable theoretical framework, providing insights into the determinants influencing the users' acceptance and adoption of technology.
Objective:
This study aims to systematically synthesize the body of research in medical education that employs the TAM.
Methods:
An electronic literature search was conducted using the PRISMA approach in February 2024 on the Embase, Medline, PyscINFO, PubMed, and Web of Science databases, yielding 680 articles. Upon elimination of duplicates and applying the exclusion criteria, a total of 39 articles were retained. To evaluate the quality of the study, the Medical Education Research Study Quality Instrument (MERSQI) score was calculated for each analysis with a qualitative component.
Results:
The review found that the studies using TAM only started in 2010, with the model relatively sparse until 2021. Most of the studies were quantitative, operationalizing the TAM as a survey instrument, but it was also used as a research framework in qualitative data analysis. SEM, descriptive analysis, and correlation analysis are the most common data analysis approaches in the study. E-learning and mobile learning were the predominant learning interventions explored, but there were indications that novel learning technologies such as augmented reality, virtual reality, and 3D printing were being investigated.
Conclusions:
The study's findings reveal an expanding scholarly engagement with the use of TAM in medical education. While the TAM has been mostly used as a survey instrument, it can also be adapted as a research framework to analyze data qualitatively. This systematic review provides a foundation for future research to understand the factors influencing users' acceptance of technology, especially in medical education. Clinical Trial: Not applicable
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