Correspondence on “Assessing Immersive Virtual Reality as Learning Tool for Surgical Trainees”

Dear Editor,

The publication on “Assessing Immersive Virtual Reality as Learning Tool for Surgical Trainees”¹ is hereby discussed. The fundamental premise behind this study represents the growing use of virtual reality (VR) technology in medical education, particularly in surgical or surgical training. However, this study remains in the context of a basic comparison of 2-dimensional (2D) video and immersive VR (iVR), with an emphasis on the findings of knowledge, confidence, and first-time hands-on performance, all of which are valid ways for assessing learning outcomes.

However, the notion that VR is “likely” to produce superior results may not be enough to draw policy or practical conclusions. The 1:1:1 randomization of participants to 3 training formats (2D, desktop VR, iVR) is a good approach in terms of research methodology. However, the limited number of participants (43), especially when divided into 3 subgroups (∼14 people per group), reduces statistical reliability and may result in the analysis not detecting real differences (type II error). The use of two blinded assessors is a strength of this study, however it does not state which standard or form was utilized to evaluate performance. This could influence the data’s validity.

The reported “trend” for a significant difference (P = .054) in the iVR group should be viewed with caution, as it did not approach statistical significance (P < .05) and so does not corroborate the genuine effect. Furthermore, the study did not reveal the effect size, which is critical for determining the practical value of VR. Further questions to be considered include: If iVR has no clear influence on practical training outcomes, what characteristics make learners feel more “engaged,” and how does this alter learning behavior in the long run?

Future study should involve bigger sample numbers and long-term follow-up to determine whether immersive learning materials affect knowledge and skill retention. Furthermore, the use of biological or neurological indicators (e.g., eye-tracking, electroencephalogram [EEG], or heart rate variability [HRV]) to systematically measure engagement and cognitive load, as well as cost-effectiveness analyses of VR use in clinical training, should be considered to help inform policy decisions in an era when technology is changing the role of medical education.