奇纳
心理信息
执照
课程
虚拟现实
护理部
资源(消歧)
可用性
梅德林
护士教育
包裹体(矿物)
医学
心理学
医学教育
计算机科学
教育学
心理干预
计算机网络
社会心理学
人机交互
人工智能
政治学
法学
标识
DOI:10.1080/01612840.2023.2243330
摘要
The integrative review's objective is to determine the effectiveness of incorporating virtual reality (VR) simulation teaching methods in pre-licensure psychiatric nursing curricula. While the demand for skilled nurses has increased, the COVID-19 pandemic exacerbated nursing educational resource shortages and reduced the number of qualified applicants accepted into nursing schools. Psychiatric assessment and communication skills are difficult to obtain. VR simulation may present an effective solution to enhancing nursing students' psychiatric education. The integrative review was the study design. Tailored search terms were applied to the following databases: PubMed, PsycINFO, ERIC, and CINAHL Plus with Full Text. The databases were searched by title and abstract during the period January 1, 2011, through October 14, 2021. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied to search strategies and results. The selected articles were evaluated using the Johns Hopkins research evidence appraisal tool. Eleven studies met the inclusion criteria for the integrative review. Study results were categorized into two main themes: (a) pedagogical approach and (b) usability. Three sub-themes emerged: (a) knowledge, (b) attitudes, and (c) skills. VR was found to be effective in increasing nursing students' knowledge; improving communication and decision-making skills; and impacting attitudes toward patients living with mental illness. VR was found to be the same as or superior to traditional and other simulation methods in teaching psychiatric nursing education to pre-licensure students. While convenient, virtual reality use involves managing technical difficulties and considering safety. VR simulation is an effective pedagogical approach for psychiatric nursing curricula and offers a potentially cost-effective alternative to traditional learning and other simulation methods.
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