Acceptance of Virtual Reality in Trainees Using a Technology Acceptance Model: Survey Study

Background: Virtual reality (VR) technologies have demonstrated therapeutic usefulness across a variety of health care settings. However, graduate medical education (GME) trainee perspectives on VR acceptability and usability are limited. The behavioral intentions of GME trainees with regard to VR as an anxiolytic tool have not been characterized through a theoretical framework of technology adoption.

Objective: The primary aim of this study was to apply a hybrid Technology Acceptance Model (TAM) and a United Theory of Acceptance and Use of Technology (UTAUT) model to evaluate factors that predict the behavioral intentions of GME trainees to use VR for patient anxiolysis. The secondary aim was to assess the reliability of the TAM-UTAUT.

Methods: Participants were surveyed in June 2023. GME trainees participated in a VR experience used to reduce perioperative anxiety. Participants then completed a survey evaluating demographics, perceptions, attitudes, environmental factors, and behavioral intentions that influence the adoption of new technologies.

Results: In total, 202 of 1540 GME trainees participated. Only 198 participants were included in the final analysis (12.9% participation rate). Perceptions of usefulness, ease of use, and enjoyment; social influence; and facilitating conditions predicted intention to use VR. Age, past use, price willing to pay, and curiosity were less strong predictors of intention to use. All confirmatory factor analysis models demonstrated a good fit. All domain measurements demonstrated acceptable reliability.

Conclusions: This TAM-UTAUT demonstrated validity and reliability for predicting the behavioral intentions of GME trainees to use VR as a therapeutic anxiolytic in clinical practice. Social influence and facilitating conditions are modifiable factors that present opportunities to advance VR adoption, such as fostering exposure to new technologies and offering relevant training and social encouragement. Future investigations should study the model's reliability within specialties in different geographic locations.