Evidence map›Paper›PMID 40482056›Full record

ReviewNursing open2025

ChatGPT Applications in Nursing: Current Status and Future Perspectives.

Wenli Peng, Xinhua Cheng, Jili Deng, Xian Zhang

Abstract readReview
In one paragraph

Review in Nursing open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Safety and accuracy of AI in triaging patients in the emergency department.International journal of emergency medicine · 2025
    Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Wenli PengChongqing College of Humanities, Science & Technology, Chongqing, China.ORCID https://orcid.org/0009-0006-3209-922X
Xinhua ChengChongqing College of Humanities, Science & Technology, Chongqing, China.
Jili DengChongqing College of Humanities, Science & Technology, Chongqing, China.
Xian ZhangChongqing College of Humanities, Science & Technology, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimWith the rapid advancement of generative artificial intelligence technologies, natural language processing tools represented by ChatGPT have been increasingly used. This narrative review explored the application, challenges, and future directions of ChatGPT in nursing.

designNarrative review.

methodsThe searches were conducted in PubMed, Web of Science and Google Scholar. The empirical studies of ChatGPT in nursing were selected and explored.

resultsChatGPT has been integrated into clinical nursing support, nurse education and patient service optimisation, demonstrating potential in improving efficiency and patient outcomes. However, technical limitations, ethical-legal issues and implementation barriers pose challenges to its widespread adoption. In future, technology iteration, standard development and multimodal convergence are needed to promote the construction of trusted artificial intelligence nursing systems. PATIENT OR PUBLIC CONTRIBUTION: This narrative review is based on a secondary analysis of existing literature and does not directly involve patient or public contributions.

Indexed as

Artificial IntelligenceNatural Language ProcessingNursingGenerative Artificial IntelligenceHumansChatGPTclinical nursingnurse educationpatient service

Identifiers

PMID40482056
PMCPMC12145163

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.