ReviewCureus2021
A Concept Analysis on the Use of Artificial Intelligence in Nursing.
Review in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 5 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 5 syntheses or guidelines pooled it, 52 citations in OpenAlex.
- Artificial Intelligence Technologies in Nursing Clinical Decision-Making: An Umbrella Review.Journal of advanced nursing · 2026Pooled it
- Artificial Intelligence Technologies Supporting Nurses' Clinical Decision-Making: A Systematic Review.Journal of clinical nursing · 2026Pooled it
- Examining the Role of AI in Changing the Role of Nurses in Patient Care: Systematic Review.JMIR nursing · 2025Pooled it
- AI literacy and competency in nursing education: preparing students and faculty members for an AI-enabled future-a systematic review and meta-analysis.Frontiers in medicine · 2025Pooled it
- Artificial intelligence based prediction models for individuals at risk of multiple diabetic complications: A systematic review of the literature.Journal of nursing management · 2022Pooled it
- Review
- Artificial Intelligence-Supported Virtual Nursing at Home: A Systematic Review.Florence Nightingale journal of nursing · 2026Article
- Use of Conventional Artificial Intelligence Methods in the Identification of Frailty: A Scoping Review.Journal of the American Geriatrics Society · 2026Article
- Personal Health Data in Healthcare: Important Factors Considered by Health Students-A Qualitative Study.Healthcare (Basel, Switzerland) · 2026Article
- Community Health Nurses' Knowledge and Perceptions of AI in Canada: National Cross-Sectional Survey.JMIR nursing · 2026Article
- Artificial Intelligence Attitudes and Time Management Among Undergraduate Nursing Students: A Cross-Sectional Study.Journal of nursing management · 2026Article
- Factors that influence the implementation of AI-driven lifestyle monitoring in long-term care for older adults.The Gerontologist · 2025Article
- Nurses' attitudes towards artificial intelligence: relationship between cognitive flexibility and emotion regulation.BMC psychology · 2025Article
- Review
- Exploring the deep learning of artificial intelligence in nursing: a concept analysis with Walker and Avant's approach.BMC nursing · 2024Article
- The Cooperation Between Nurses and a New Digital Colleague "AI-Driven Lifestyle Monitoring" in Long-Term Care for Older Adults: Viewpoint.JMIR nursing · 2024Article
- Article
- Use of Artificial Intelligence in the Identification and Management of Frailty: A Scoping Review Protocol.BMJ open · 2023Article
- Harnessing Large Language Models in Nursing Care Planning: Opportunities, Challenges, and Ethical Considerations.Cureus · 2023Article
- Data Science Implementation Trends in Nursing Practice: A Review of the 2021 Literature.Applied clinical informatics · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.