%0 Journal Article
%@ 2291-9279
%I JMIR Publications
%V 13
%N 
%P e68272
%T Enhancing Immersion in Virtual Reality–Based Advanced Life Support Training: Randomized Controlled Trial
%A Kitapcioglu,Dilek
%A Aksoy,Mehmet Emin
%A Ozkan,Arun Ekin
%A Usseli,Tuba
%A Cabuk Colak,Dilan
%A Torun,Tugrul
%+ Center of Advanced Simulation and Education, Acibadem Mehmet Ali Aydinlar University, Kayisdagi cad No 32 Atasehir, Istanbul, 34752, Turkey, 90 05052685158, emin.aksoy@acibadem.edu.tr
%K artificial intelligence
%K voice recognition
%K serious gaming
%K immersion
%K virtual reality
%D 2025
%7 14.2.2025
%9 Original Paper
%J JMIR Serious Games
%G English
%X Background: Serious game–based training modules are pivotal for simulation-based health care training. With advancements in artificial intelligence (AI) and natural language processing, voice command interfaces offer an intuitive alternative to traditional virtual reality (VR) controllers in VR applications. Objective: This study aims to compare AI-supported voice command interfaces and traditional VR controllers in terms of user performance, exam scores, presence, and confidence in advanced cardiac life support (ACLS) training. Methods: A total of 62 volunteer students from Acibadem Mehmet Ali Aydinlar University Vocational School for Anesthesiology, aged 20-22 years, participated in the study. All the participants completed a pretest consisting of 10 multiple-choice questions about ACLS. Following the pretest, participants were randomly divided into 2 groups: the voice command group (n=31) and the VR controller group (n=31). The voice command group members completed the VR-based ACLS serious game in training mode twice, using an AI-supported voice command as the game interface. The VR controller group members also completed the VR-based ACLS serious game in training mode twice, but they used VR controllers as the game interface. The participants completed a survey to assess their level of presence and confidence during gameplay. Following the survey, participants completed the exam module of the VR-based serious gaming module. At the final stage of the study, participants completed a posttest, which had the same content as the pretest. VR-based exam scores of the voice command and VR controller groups were compared using a 2-tailed, independent-samples t test, and linear regression analysis was conducted to examine the effect of presence and confidence rating. Results: Both groups showed an improvement in performance from pretest to posttest, with no significant difference in the magnitude of improvement between the 2 groups (P=.83). When comparing presence ratings, there was no significant difference between the voice command group (mean 5.18, SD 0.83) and VR controller group (mean 5.42, SD 0.75; P=.25). However, when comparing VR-based exam scores, the VR controller group (mean 80.47, SD 13.12) significantly outperformed the voice command group (mean 66.70, SD 21.65; P=.005), despite both groups having similar time allocations for the exam (voice command group: mean 18.59, SD 5.28 minutes and VR controller group: mean 17.3, SD 4.83 minutes). Confidence levels were similar between the groups (voice command group: mean 3.79, SD 0.77 and VR controller group: mean 3.60, SD 0.72), but the voice command group displayed a significant overconfidence bias (voice command group: mean 0.09, SD 0.24 and VR controller group: mean –0.09, SD 0.18; P=.002). Conclusions: VR-based ACLS training demonstrated effectiveness; however, the use of voice commands did not result in improved performance. Further research should explore ways to optimize AI’s role in education through VR. Trial Registration: ClinicalTrials.gov NCT06458452; https://clinicaltrials.gov/ct2/show/NCT06458452 
%R 10.2196/68272
%U https://games.jmir.org/2025/1/e68272
%U https://doi.org/10.2196/68272