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

Area of Science:

• Medical Education Technology
• Digital Health Interventions
• Patient Anxiety Management

Background:

• Virtual reality (VR) shows therapeutic potential in healthcare, but trainee perspectives on its use are underexplored.
• Behavioral intentions of graduate medical education (GME) trainees regarding VR for anxiety remain uncharacterized by technology adoption frameworks.
• Limited data exists on GME trainee acceptance and usability of VR as a clinical tool.

Purpose of the Study:

• To apply a hybrid Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) model to GME trainees.
• To identify factors predicting GME trainees' behavioral intentions to use VR for patient anxiolysis.
• To assess the reliability of the combined TAM-UTAUT model in this context.

Main Methods:

• Surveyed 202 GME trainees after a VR experience designed to reduce perioperative anxiety.
• Collected data on demographics, perceptions, attitudes, environmental factors, and behavioral intentions.
• Utilized confirmatory factor analysis to evaluate the TAM-UTAUT model and its reliability.

Main Results:

• Perceptions of usefulness, ease of use, enjoyment, social influence, and facilitating conditions predicted VR adoption intention.
• Age, prior VR use, price sensitivity, and curiosity were weaker predictors.
• The TAM-UTAUT model demonstrated good fit and acceptable reliability for all measurements.

Conclusions:

• The TAM-UTAUT model is valid and reliable for predicting GME trainee intentions to use VR for patient anxiety.
• Modifiable factors like social influence and facilitating conditions can promote VR adoption through training and exposure.
• Future research should explore model reliability across different medical specialties and geographic locations.