Evaluating Whether Nonimmersion Virtual Reality Simulation Training Improves Nursing Competency in Isolation Wards: Randomized Controlled Trial

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Abstract

Background: During infectious disease outbreaks such as the COVID-19 pandemic, nurses are crucial in patient care and public health safety; however, they face challenges such as inadequate training and high stress in isolation wards. Virtual reality (VR) technology offers innovative training solutions to enhance nurses' clinical skills and preparedness. However, extensive studies on its effectiveness in isolation ward environments are still limited. Objective: This study aims to develop a nonimmersive VR (NIVR) simulation training program for isolation wards and further validate its feasibility and training effectiveness in aiding nurses in adapting to isolation ward settings. Methods: This study was a prospective, parallel, open-label, randomized controlled trial. A total of 90 nurses from 3 hospitals in China were randomly assigned to either the control or intervention group, with 45 (50%) individuals in each group. Both groups received training on isolation ward layout and nursing procedures. The control group underwent a 4-hour conventional training session consisting of 2 hours of face-to-face lectures and 2 hours of ward visits. The intervention group received a 4-hour NIVR simulation training session. Subsequently, both groups completed approximately 4 hours of emergency drills and assessments. Results: After the intervention, there were no significant differences in theoretical test or performance assessment scores between the 2 groups (t88=-0.30, P=.75; Cohen d=-0.06; z score=0.00, P>.99), using a 2-tailed t test. However, the intervention group completed 6 tasks faster than the control group (t88=5.10, P

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Zhang, D., Fu, M., Zhang, J., Li, Y., Chen, L., Chen, Y. J., … Zhang, Y. P. (2025). Evaluating Whether Nonimmersion Virtual Reality Simulation Training Improves Nursing Competency in Isolation Wards: Randomized Controlled Trial. Journal of Medical Internet Research, 27. https://doi.org/10.2196/63131

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