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Accepted for/Published in: JMIR Nursing

Date Submitted: Sep 11, 2020
Date Accepted: Jan 11, 2021

The final, peer-reviewed published version of this preprint can be found here:

Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review

Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M

Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review

JMIR Nursing 2021;4(1):e23933

DOI: 10.2196/23933

PMID: 34345794

PMCID: 8328269

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Nursing Education in the Age of Artificial Intelligence: A Scoping Review

  • Christine Buchanan; 
  • M. Lyndsay Howitt; 
  • Rita Wilson; 
  • Richard G Booth; 
  • Tracie Risling; 
  • Megan Bamford

ABSTRACT

Background:

It is predicted that artificial intelligence will transform nursing across various domains of nursing practice: administration, clinical care, education, policy, and research. However, little synthesis has been completed exploring how artificial intelligence technologies will influence nursing education specifically.

Objective:

A scoping review was conducted to explore how artificial intelligence-driven digital health technologies are expected to influence nursing education over the next ten years and beyond.

Methods:

This scoping review followed the previously published protocol from April 2020. Using an established scoping review methodology, 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 databases 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 pre-specified inclusion and exclusion criteria. Included literature focused on nursing and digital health technologies that incorporate artificial intelligence. Data was charted using a piloted 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 and nursing students at the undergraduate/entry levels, graduate, and doctoral levels. A variety of artificial intelligence technologies were discussed, including virtual nursing applications and robots. Key categories derived from the literature included: (1) educational requirements for nurses at the entry level, graduate and doctoral levels, (2) educational requirements for nurses in clinical practice, and (3) changes to the delivery of nursing education.

Conclusions:

Nurses need to be better equipped to evaluate and integrate artificial intelligence in practice settings, and imminent changes are needed within nursing education programs to prepare nurses to use these technologies. Additionally, nurse educators need to understand how to use artificial intelligence in their teaching practices at the undergraduate and post-graduate levels.


 Citation

Please cite as:

Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M

Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review

JMIR Nursing 2021;4(1):e23933

DOI: 10.2196/23933

PMID: 34345794

PMCID: 8328269

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