Effectiveness of Virtual Reality in Nursing Education: Meta-Analysis.

Journal of medical Internet research(2020)

引用 156|浏览1
暂无评分
摘要
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.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要