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Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review
BACKGROUND: It is predicted that artificial intelligence (AI) will transform nursing across all domains of nursing practice, including administration, clinical care, education, policy, and research. Increasingly, researchers are exploring the potential influences of AI health technologies (AIHTs) on...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328269/ https://www.ncbi.nlm.nih.gov/pubmed/34345794 http://dx.doi.org/10.2196/23933 |
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author | Buchanan, Christine Howitt, M Lyndsay Wilson, Rita Booth, Richard G Risling, Tracie Bamford, Megan |
author_facet | Buchanan, Christine Howitt, M Lyndsay Wilson, Rita Booth, Richard G Risling, Tracie Bamford, Megan |
author_sort | Buchanan, Christine |
collection | PubMed |
description | BACKGROUND: It is predicted that artificial intelligence (AI) will transform nursing across all domains of nursing practice, including administration, clinical care, education, policy, and research. Increasingly, researchers are exploring the potential influences of AI health technologies (AIHTs) on nursing in general and on nursing education more specifically. However, little emphasis has been placed on synthesizing this body of literature. OBJECTIVE: A scoping review was conducted to summarize the current and predicted influences of AIHTs on nursing education over the next 10 years and beyond. METHODS: This scoping review followed a previously published protocol from April 2020. Using an established scoping review methodology, the databases of MEDLINE, Cumulative Index to Nursing and Allied Health Literature, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Centre, Scopus, Web of Science, and Proquest were searched. In addition to the use of these electronic databases, a targeted website search was performed to access relevant grey literature. Abstracts and full-text studies were independently screened by two reviewers using prespecified inclusion and exclusion criteria. Included literature focused on nursing education and digital health technologies that incorporate AI. Data were charted using a structured form and narratively summarized into categories. RESULTS: A total of 27 articles were identified (20 expository papers, six studies with quantitative or prototyping methods, and one qualitative study). The population included nurses, nurse educators, and nursing students at the entry-to-practice, undergraduate, graduate, and doctoral levels. A variety of AIHTs were discussed, including virtual avatar apps, smart homes, predictive analytics, virtual or augmented reality, and robots. The two key categories derived from the literature were (1) influences of AI on nursing education in academic institutions and (2) influences of AI on nursing education in clinical practice. CONCLUSIONS: Curricular reform is urgently needed within nursing education programs in academic institutions and clinical practice settings to prepare nurses and nursing students to practice safely and efficiently in the age of AI. Additionally, nurse educators need to adopt new and evolving pedagogies that incorporate AI to better support students at all levels of education. Finally, nursing students and practicing nurses must be equipped with the requisite knowledge and skills to effectively assess AIHTs and safely integrate those deemed appropriate to support person-centered compassionate nursing care in practice settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/17490 |
format | Online Article Text |
id | pubmed-8328269 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-83282692021-08-02 Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review Buchanan, Christine Howitt, M Lyndsay Wilson, Rita Booth, Richard G Risling, Tracie Bamford, Megan JMIR Nurs Review BACKGROUND: It is predicted that artificial intelligence (AI) will transform nursing across all domains of nursing practice, including administration, clinical care, education, policy, and research. Increasingly, researchers are exploring the potential influences of AI health technologies (AIHTs) on nursing in general and on nursing education more specifically. However, little emphasis has been placed on synthesizing this body of literature. OBJECTIVE: A scoping review was conducted to summarize the current and predicted influences of AIHTs on nursing education over the next 10 years and beyond. METHODS: This scoping review followed a previously published protocol from April 2020. Using an established scoping review methodology, the databases of MEDLINE, Cumulative Index to Nursing and Allied Health Literature, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Centre, Scopus, Web of Science, and Proquest were searched. In addition to the use of these electronic databases, a targeted website search was performed to access relevant grey literature. Abstracts and full-text studies were independently screened by two reviewers using prespecified inclusion and exclusion criteria. Included literature focused on nursing education and digital health technologies that incorporate AI. Data were charted using a structured form and narratively summarized into categories. RESULTS: A total of 27 articles were identified (20 expository papers, six studies with quantitative or prototyping methods, and one qualitative study). The population included nurses, nurse educators, and nursing students at the entry-to-practice, undergraduate, graduate, and doctoral levels. A variety of AIHTs were discussed, including virtual avatar apps, smart homes, predictive analytics, virtual or augmented reality, and robots. The two key categories derived from the literature were (1) influences of AI on nursing education in academic institutions and (2) influences of AI on nursing education in clinical practice. CONCLUSIONS: Curricular reform is urgently needed within nursing education programs in academic institutions and clinical practice settings to prepare nurses and nursing students to practice safely and efficiently in the age of AI. Additionally, nurse educators need to adopt new and evolving pedagogies that incorporate AI to better support students at all levels of education. Finally, nursing students and practicing nurses must be equipped with the requisite knowledge and skills to effectively assess AIHTs and safely integrate those deemed appropriate to support person-centered compassionate nursing care in practice settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/17490 JMIR Publications 2021-01-28 /pmc/articles/PMC8328269/ /pubmed/34345794 http://dx.doi.org/10.2196/23933 Text en ©Christine Buchanan, M Lyndsay Howitt, Rita Wilson, Richard G Booth, Tracie Risling, Megan Bamford. Originally published in JMIR Nursing Informatics (https://nursing.jmir.org), 28.01.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Review Buchanan, Christine Howitt, M Lyndsay Wilson, Rita Booth, Richard G Risling, Tracie Bamford, Megan Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review |
title | Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review |
title_full | Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review |
title_fullStr | Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review |
title_full_unstemmed | Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review |
title_short | Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review |
title_sort | predicted influences of artificial intelligence on nursing education: scoping review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8328269/ https://www.ncbi.nlm.nih.gov/pubmed/34345794 http://dx.doi.org/10.2196/23933 |
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