{"title":"Generative artificial intelligence in nursing: A scoping review","authors":"Ga Eun Park , Hyeryeon Kim , U Ri Go","doi":"10.1016/j.colegn.2024.10.004","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Generative artificial intelligence (AI) is rapidly transforming multiple sectors, with significant potential to revolutionise nursing through advancements in education, practice, and research. However, the application of generative AI in nursing remains underexplored, highlighting the need for a comprehensive review of its current impact and future implications.</div></div><div><h3>Aim</h3><div>To investigate the current state and implications of generative AI in nursing education, practice, and research.</div></div><div><h3>Methods</h3><div>This scoping review was conducted following the methodological frameworks of Arksey and O’Malley, refined by Levac and colleagues. The databases searched for articles published between January 2020 and April 2024 included PubMed, Embase, CINAHL, PsycINFO, Cochrane Library, and IEEE Xplore.</div></div><div><h3>Findings</h3><div>A total of 4858 articles were identified, with 23 included in this review. Most of the selected studies were published in 2024 (n = 19/23), primarily conducted in the United States (n = 8/23), and largely consisted of quantitative descriptive studies (n = 14/22). ChatGPT was the most frequently used tool, appearing in 95.7% of the studies (n = 22/23). The articles addressed various nursing domains, including nursing education (n = 12/23), practice (n = 10/23), and research (n = 1/23). Both the benefits and concerns associated with this technology were identified.</div></div><div><h3>Discussion</h3><div>Generative AI shows great promise for transforming nursing education, practice, and research; however, its integration is still in the early stages.</div></div><div><h3>Conclusion</h3><div>To fully leverage the benefits of generative AI, nursing professionals must address the challenges associated with AI and lead its ethical adoption. Rigorous research and proactive leadership are crucial to realising the potential of generative AI in nursing.</div></div>","PeriodicalId":55241,"journal":{"name":"Collegian","volume":"31 6","pages":"Pages 428-436"},"PeriodicalIF":1.6000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Collegian","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1322769624000696","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Generative artificial intelligence (AI) is rapidly transforming multiple sectors, with significant potential to revolutionise nursing through advancements in education, practice, and research. However, the application of generative AI in nursing remains underexplored, highlighting the need for a comprehensive review of its current impact and future implications.
Aim
To investigate the current state and implications of generative AI in nursing education, practice, and research.
Methods
This scoping review was conducted following the methodological frameworks of Arksey and O’Malley, refined by Levac and colleagues. The databases searched for articles published between January 2020 and April 2024 included PubMed, Embase, CINAHL, PsycINFO, Cochrane Library, and IEEE Xplore.
Findings
A total of 4858 articles were identified, with 23 included in this review. Most of the selected studies were published in 2024 (n = 19/23), primarily conducted in the United States (n = 8/23), and largely consisted of quantitative descriptive studies (n = 14/22). ChatGPT was the most frequently used tool, appearing in 95.7% of the studies (n = 22/23). The articles addressed various nursing domains, including nursing education (n = 12/23), practice (n = 10/23), and research (n = 1/23). Both the benefits and concerns associated with this technology were identified.
Discussion
Generative AI shows great promise for transforming nursing education, practice, and research; however, its integration is still in the early stages.
Conclusion
To fully leverage the benefits of generative AI, nursing professionals must address the challenges associated with AI and lead its ethical adoption. Rigorous research and proactive leadership are crucial to realising the potential of generative AI in nursing.
期刊介绍：
Collegian: The Australian Journal of Nursing Practice, Scholarship and Research is the official journal of Australian College of Nursing (ACN).
The journal aims to reflect the broad interests of nurses and the nursing profession, and to challenge nurses on emerging areas of interest. It publishes research articles and scholarly discussion of nursing practice, policy and professional issues.
Papers published in the journal are peer reviewed by a double blind process using reviewers who meet high standards of academic and clinical expertise. Invited papers that contribute to nursing knowledge and debate are published at the discretion of the Editor.
The journal, online only from 2016, is available to members of ACN and also by separate subscription.
ACN believes that each and every nurse in Australia should have the opportunity to grow their career through quality education, and further our profession through representation. ACN is the voice of influence, providing the nursing expertise and experience required when government and key stakeholders are deciding the future of health.
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