Effectiveness of virtual reality in nursing education: meta-analysis
Open accessPublished version of a preprint
Abstract
BACKGROUND Virtual reality (VR) is the use of computer technology to create an interactive three-dimensional (3D) world, which gives users a sense of spatial presence. In nursing education, VR has been used to help optimize teaching and learning processes. OBJECTIVE The purpose of this study was to evaluate the effectiveness of VR in nursing education in the areas of knowledge, skills, satisfaction, confidence, and performance time. METHODS We conducted a meta-analysis of the effectiveness of VR in nursing education based on the Cochrane methodology. An electronic literature search using the Cochrane Library, Web of Science, PubMed, Embase, and CINAHL (Cumulative Index to Nursing and Allied Health Literature), up to December 2019 was conducted to identify studies that reported the effectiveness of VR on knowledge, skills, satisfaction, confidence, and performance time. The study selection and data extraction were carried out by two independent reviewers. The methodological quality of the selected studies was determined using the Cochrane criteria for risk-of-bias assessment. RESULTS A total of 12 studies, including 821 participants, were selected for the final analysis. We found that VR was more effective than the control conditions in improving knowledge (standard mean difference [SMD]=0.58, 95% CI 0.41-0.75, P<.001, I2=47%). However, there was no difference between VR and the control conditions in skills (SMD=0.01, 95% CI –0.24 to 0.26, P=.93, I2=37%), satisfaction (SMD=0.01, 95% CI –0.79 to 0.80, P=.99, I2=86%), confidence (SMD=0.00, 95% CI –0.28 to 0.27, P=.99, I2=0%), and performance time (SMD=–0.55, 95% CI –2.04 to 0.94, P=.47, I2=97%). CONCLUSIONS The results of this study suggest that VR can effectively improve knowledge in nursing education, but it was not more effective than other education methods in areas of skills, satisfaction, confidence, and performance time. Further rigorous studies with a larger sample size are warranted to confirm these results.
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Integrating generative AI technologies into foundational medical courses may provide an effective strategy for addressing long-standing challenges in anatomy teaching, such as high cognitive load and fragmented knowledge presentation.
“First, integrating generative AI technologies into foundational medical courses may provide an effective strategy for addressing long-standing challenges in anatomy teaching, such as high cognitive load and fragmented knowledge presentation [6, 7, 38].”
From Effectiveness of a generative AI-powered digital tutor integrated with a knowledge graph in anatomy education for nursing students: a randomized controlled trial (2026) · cites this paper as [38]
The Introduction and Discussion > Knowledge discuss virtual reality in nursing education, and the Results report improved knowledge with VR. Our copy does not address generative AI in foundational medical courses or whether it reduces cognitive load or fragmented presentation in anatomy teaching (searched for those terms and their teaching context). (LLM, conf=0.76)
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- Authors
- Chen, F.-Q., Leng, Y.-F., Ge, J.-F., Wang, D.-W., Li, C., Chen, B., & Sun, Z.-L.
- Affiliations
- Nanjing University of Chinese Medicine (CN)
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2020-09-15
- Volume
- 22
- Issue
- 9
- Pages
- e18290
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC7525398
- OpenAlex
- W3045914130
- Cited by
- 535
- References
- 56
- Citations by year
- 2026: 81 · 2025: 127 · 2024: 130 · 2023: 107 · 2022: 61 · 2021: 28 · 2020: 1
- FWCI
- 6.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Government of Jiangsu Province
- Nanjing University of Chinese Medicine
- Nanjing University
- Qinglan Project of Jiangsu Province of China
- Topics
- Health Sciences › Medicine › Physiology › Simulation-Based Education in Healthcare
- Physical Sciences › Computer Science › Human-Computer Interaction › Virtual Reality Applications and Impacts
- Health Sciences › Medicine › Surgery › Surgical Simulation and Training
- Keywords
- virtual reality, nursing education, simulation-based training, nursing knowledge, clinical skills, student satisfaction, self-confidence, performance time, educational effectiveness
- MeSH terms
- Virtual Reality, Education, Nursing, Female, Humans, Male
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