A Concept Analysis on the Use of Artificial Intelligence in Nursing
Open accessAbstract
Artificial intelligence (AI) has a considerable present and future influence on healthcare. Nurses, representing the largest proportion of healthcare workers, are set to immensely benefit from this technology. However, the overall adoption of new technologies by nurses is quite slow, and the use of AI in nursing is considered to be in its infancy. The current literature on AI in nursing lacks conceptual clarity and consensus, which is affecting clinical practice, research activities, and theory development. Therefore, to set the foundations for nursing AI knowledge development, the purpose of this concept analysis is to clarify the conceptual components of AI in nursing and to determine its conceptual maturity. A concept analysis following Morse's approach was conducted, which examined definitions, characteristics, preconditions, outcomes, and boundaries on the state of AI in nursing. A total of 18 quantitative, qualitative, mixed-methods, and reviews related to AI in nursing were retrieved from the CINAHL and EMBASE databases using a Boolean search. Presently, the concept of AI in nursing is immature. The characteristics and preconditions of the use of AI in nursing are mixed between and within each other. The preconditions and outcomes on the use of AI in nursing are diverse and indiscriminately reported. As for boundaries, they can be more distinguished between robots, sensors, and clinical decision support systems, but these lines can become more blurred in the future. As of 2021, the use of AI in nursing holds much promise for the profession, but conceptual and theoretical issues remain.
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Nurses, as the largest part of all workers involved in health systems, will benefit enormously from AI.
“Nurses, as the largest part of all workers involved in health systems, will benefit enormously from AI (Shang, 2021).”
From Artificial intelligence based prediction models for individuals at risk of multiple diabetic complications: A systematic review of the literature (2022) · cites this paper as Shang, 2021
The Introduction and background says nurses are the largest proportion of healthcare workers and would theoretically benefit the most from AI. The citing sentence presents that projected benefit as certain, whereas the source qualifies it and notes that adoption of AI in nursing remains slow. (LLM, conf=0.86)
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- Authors
- Shang, Z.
- Affiliations
- McGill University (CA)
- Corresponding author
- Shang, Zhida
- ORCID
- Shang, Zhida
- Venue
- Cureus
- Published
- 2021-05-05
- Volume
- 13
- Issue
- 5
- Pages
- e14857-e14857
- ISSN
- 2168-8184 (ISSN-L)
- PMC
- PMC8177028
- OpenAlex
- W3159917108
- Cited by
- 53
- References
- 41
- Citations by year
- 2026: 10 · 2025: 19 · 2024: 11 · 2023: 7 · 2022: 5 · 2021: 1
- FWCI
- 0.49
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Cureus (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence in nursing, conceptual analysis, clinical decision support systems, nursing robots, nursing theory development
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