The effectiveness of augmented reality/mixed reality in medical education: a meta-analysis

Augmented reality (AR) and mixed reality (MR) are increasingly being applied in the field of medical education. However, the effectiveness and acceptance of AR/MR in different teaching scenarios remain unclear. This meta-analysis aimed to examine the effectiveness of AR/MR in improving medical students' knowledge and skills training.

PubMed, Embase, Cochrane Library, PsycINFO, Education Source, Education Resources Information Center, CINAHL, Web of Science Core Collection, China National Knowledge Infrastructure, WanFang, WeiPu, and Chinese BioMedical Literature databases were searched. The search encompassed literature from the database establishment to December 2023. Studies examining the use of AR/MR in medical education and reporting outcomes related to knowledge learning or skill training were included. The data were analyzed using Stata version 15.1 software.

Twenty-nine publications were included in this meta-analysis. Compared to traditional teaching methods, AR/MR-assisted teaching showed greater effectiveness in medical skills training, as indicated by the higher skill scores (WMD = 12.31, 95% CI: 4.12 to 20.50), reduced failure rate (RD = -0.08, 95% CI: -0.12 to -0.04), and shortened performance time (SMD = -0.20, 95% CI: -0.36 to -0.04). However, AR/MR did not significantly improve knowledge acquisition (WMD = 2.92, 95% CI: -1.73 to 7.57). The questionnaire survey revealed the advantages of AR/MR in terms of perceived usefulness (PU) (WMD = 0.27, 95% CI: 0.00 to 0.53), perceived ease of use (PEOU) (WMD = 0.35, 95% CI: 0.13 to 0.57), and enjoyment (WMD = 0.67, 95% CI: 0.20 to 1.13).

This meta-analysis highlights the effectiveness and user acceptance of AR/MR in medical education, particularly in skill training, although no significant improvement was observed in knowledge learning. The findings provide a foundational evidence base for the further expansion of AR/MR applications in medical education. However, it should be noted that these estimates may be influenced by heterogeneity and publication bias.