将生成人工智能纳入医疗保健专业本科生模拟教育的策略：范围审查

IF 2.5 3区医学 Q1 NURSING

Clinical Simulation in Nursing Pub Date : 2025-08-25 DOI:10.1016/j.ecns.2025.101795

Jackie Hoi Man Chan , Ken Hok Man Ho , Jacqueline Maria Dias

{"title":"将生成人工智能纳入医疗保健专业本科生模拟教育的策略：范围审查","authors":"Jackie Hoi Man Chan , Ken Hok Man Ho , Jacqueline Maria Dias","doi":"10.1016/j.ecns.2025.101795","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Complex prompting and unreadiness among faculty and students are some of the reported challenges when incorporating generative artificial intelligence (GenAI) into simulation-based education (SBE) in undergraduate healthcare programmes. However, strategies for incorporating GenAI into SBE are unclear. This scoping review identified current evidence on GenAI technology, its role, study outcomes, and strategies to incorporate GenAI into the SBE of undergraduate healthcare programmes.</div></div><div><h3>Methods</h3><div>The Joanna Briggs Institute methodology for scoping reviews was adopted. Eight electronic databases were searched from inception to January 21, 2025. Two authors independently screened and extracted data. The PAGER framework collated, critiqued, and reported the results.</div></div><div><h3>Results</h3><div>Eight studies were included. ChatGPT was the most frequently employed GenAI technology in SBE of undergraduate healthcare programmes, to enhance the students’ cognitive and affective learning. Study outcomes focused on usability. Five core strategies were synthesized: (a) establish guidelines on GenAI use; (b) enhance GenAI literacy; (c) enhance competency in GenAI prompting in simulation; (d) ensure pedagogical alignment; and (e) conduct pilot tests.</div></div><div><h3>Conclusions</h3><div>The findings provide insights into GenAI integration in SBE in undergraduate healthcare programmes. Further studies on the benefits of GenAI when applied to SBE are needed to demonstrate its impact on student learning.</div></div>","PeriodicalId":48753,"journal":{"name":"Clinical Simulation in Nursing","volume":"106 ","pages":"Article 101795"},"PeriodicalIF":2.5000,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Strategies to incorporate generative artificial intelligence in simulation-based education among undergraduate students of healthcare professions: A scoping review\",\"authors\":\"Jackie Hoi Man Chan , Ken Hok Man Ho , Jacqueline Maria Dias\",\"doi\":\"10.1016/j.ecns.2025.101795\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Complex prompting and unreadiness among faculty and students are some of the reported challenges when incorporating generative artificial intelligence (GenAI) into simulation-based education (SBE) in undergraduate healthcare programmes. However, strategies for incorporating GenAI into SBE are unclear. This scoping review identified current evidence on GenAI technology, its role, study outcomes, and strategies to incorporate GenAI into the SBE of undergraduate healthcare programmes.</div></div><div><h3>Methods</h3><div>The Joanna Briggs Institute methodology for scoping reviews was adopted. Eight electronic databases were searched from inception to January 21, 2025. Two authors independently screened and extracted data. The PAGER framework collated, critiqued, and reported the results.</div></div><div><h3>Results</h3><div>Eight studies were included. ChatGPT was the most frequently employed GenAI technology in SBE of undergraduate healthcare programmes, to enhance the students’ cognitive and affective learning. Study outcomes focused on usability. Five core strategies were synthesized: (a) establish guidelines on GenAI use; (b) enhance GenAI literacy; (c) enhance competency in GenAI prompting in simulation; (d) ensure pedagogical alignment; and (e) conduct pilot tests.</div></div><div><h3>Conclusions</h3><div>The findings provide insights into GenAI integration in SBE in undergraduate healthcare programmes. Further studies on the benefits of GenAI when applied to SBE are needed to demonstrate its impact on student learning.</div></div>\",\"PeriodicalId\":48753,\"journal\":{\"name\":\"Clinical Simulation in Nursing\",\"volume\":\"106 \",\"pages\":\"Article 101795\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Simulation in Nursing\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1876139925001124\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Simulation in Nursing","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1876139925001124","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}

引用次数: 0

摘要

据报道，在将生成式人工智能（GenAI）纳入本科医疗保健课程的模拟教育（SBE）时，教师和学生的复杂提示和不准备是一些挑战。然而，将GenAI纳入SBE的策略尚不清楚。本综述确定了GenAI技术的现有证据、其作用、研究结果以及将GenAI纳入本科医疗保健课程SBE的策略。方法采用乔安娜布里格斯研究所的范围审查方法。从成立到2025年1月21日共检索了8个电子数据库。两位作者独立筛选和提取数据。PAGER框架对结果进行整理、评论和报告。结果共纳入8项研究。ChatGPT是本科医疗保健课程SBE中最常用的GenAI技术，以增强学生的认知和情感学习。研究结果集中在可用性上。综合了五项核心战略：(a)制定基因人工智能使用准则；(b)提高基因知识；(c)提高GenAI在模拟中的提示能力；(d)确保教学协调一致；(e)进行试点测试。结论本研究结果对本科医疗保健课程中SBE的GenAI整合提供了见解。需要进一步研究GenAI在应用于SBE时的益处，以证明它对学生学习的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Strategies to incorporate generative artificial intelligence in simulation-based education among undergraduate students of healthcare professions: A scoping review

Background

Complex prompting and unreadiness among faculty and students are some of the reported challenges when incorporating generative artificial intelligence (GenAI) into simulation-based education (SBE) in undergraduate healthcare programmes. However, strategies for incorporating GenAI into SBE are unclear. This scoping review identified current evidence on GenAI technology, its role, study outcomes, and strategies to incorporate GenAI into the SBE of undergraduate healthcare programmes.

Methods

The Joanna Briggs Institute methodology for scoping reviews was adopted. Eight electronic databases were searched from inception to January 21, 2025. Two authors independently screened and extracted data. The PAGER framework collated, critiqued, and reported the results.

Results

Eight studies were included. ChatGPT was the most frequently employed GenAI technology in SBE of undergraduate healthcare programmes, to enhance the students’ cognitive and affective learning. Study outcomes focused on usability. Five core strategies were synthesized: (a) establish guidelines on GenAI use; (b) enhance GenAI literacy; (c) enhance competency in GenAI prompting in simulation; (d) ensure pedagogical alignment; and (e) conduct pilot tests.

Conclusions

The findings provide insights into GenAI integration in SBE in undergraduate healthcare programmes. Further studies on the benefits of GenAI when applied to SBE are needed to demonstrate its impact on student learning.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Clinical Simulation in Nursing NURSING-

CiteScore

5.50

自引率

15.40%

发文量

107

期刊介绍： Clinical Simulation in Nursing is an international, peer reviewed journal published online monthly. Clinical Simulation in Nursing is the official journal of the International Nursing Association for Clinical Simulation & Learning (INACSL) and reflects its mission to advance the science of healthcare simulation. We will review and accept articles from other health provider disciplines, if they are determined to be of interest to our readership. The journal accepts manuscripts meeting one or more of the following criteria: Research articles and literature reviews (e.g. systematic, scoping, umbrella, integrative, etc.) about simulation Innovative teaching/learning strategies using simulation Articles updating guidelines, regulations, and legislative policies that impact simulation Leadership for simulation Simulation operations Clinical and academic uses of simulation.