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Artificial intelligence in nursing education: A scoping review
Igal Lifshits1, Dennis Rosenberg2
1Varna Free University, Bulgaria.
Aim:
To explore recent empirical studies on implementation of artificial intelligence in nursing education in hospital settings through the prism of the Strengths, Weaknesses, Opportunities and Threats (SWOT) model.
Background:
In the last decade, artificial intelligence has markedly influenced healthcare and nursing domains, particularly in improving care and educational processes for nursing staff. Despite its ongoing integration in nursing education, an understanding of its impact remained limited.
Design:
Scoping review.
Methods:
A systematic search using PubMed and ScienceDirect databases, following PRISMA guidelines, identified relevant studies. The main inclusion criteria were empirical studies from 2018 onwards and a focus on nursing students/registered nurses in hospital settings. The exclusion criteria were non-empirical documentation such as abstracts, editorials and opinion-related articles, as well as studies in surgical, pediatric, gynecological and mental health nursing.
Results:
In total, 15 articles were selected from a pool of 6517 documents. The aspects mentioned in the employed literature highlighted the positive impact of artificial intelligence on educational experiences, knowledge acquisition and mental safety. Challenges of the artificial intelligence implementation in the nursing education field, such as technical issues, language barriers and limited realistic experience were also identified.
Conclusions:
The findings of the review suggest that artificial intelligence provides significant benefits for nursing education. However, continuous evaluation managing weaknesses and maximizing the educational potential of artificial intelligence in the nursing field is crucial.
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