Evidence map›Paper›PMID 39622702›Full record

ArticleJMIR medical education2024

Using ChatGPT in Nursing: Scoping Review of Current Opinions.

You Zhou, Si-Jia Li, Xing-Yi Tang, Yi-Chen He, Hao-Ming Ma, Ao-Qi Wang, Run-Yuan Pei, Mei-Hua Piao

Abstract readScoping Review
In one paragraph

Article in JMIR medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Trial
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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

8 authors.

You Zhou *School of Nursing, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 33 Badachu Road, Shijingshan District, Beijing, 100433, China, 86 13522112889.ORCID 0000-0002-1352-0211
Si-Jia Li *School of Nursing, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 33 Badachu Road, Shijingshan District, Beijing, 100433, China, 86 13522112889.ORCID 0009-0001-0740-5858
Xing-Yi TangSchool of Nursing, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 33 Badachu Road, Shijingshan District, Beijing, 100433, China, 86 13522112889.ORCID 0009-0007-6992-4710
Yi-Chen HeSchool of Nursing, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 33 Badachu Road, Shijingshan District, Beijing, 100433, China, 86 13522112889.ORCID 0009-0006-8009-6453
Hao-Ming MaSchool of Nursing, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 33 Badachu Road, Shijingshan District, Beijing, 100433, China, 86 13522112889.ORCID 0000-0002-0271-8409
Ao-Qi WangSchool of Nursing, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 33 Badachu Road, Shijingshan District, Beijing, 100433, China, 86 13522112889.ORCID 0009-0000-8859-2423
Run-Yuan PeiSchool of Nursing, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 33 Badachu Road, Shijingshan District, Beijing, 100433, China, 86 13522112889.ORCID 0009-0007-8190-2477
Mei-Hua PiaoSchool of Nursing, Chinese Academy of Medical Sciences, Peking Union Medical College, No. 33 Badachu Road, Shijingshan District, Beijing, 100433, China, 86 13522112889.ORCID 0000-0002-2436-6870

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Since the release of ChatGPT in November 2022, this emerging technology has garnered a lot of attention in various fields, and nursing is no exception. However, to date, no study has comprehensively summarized the status and opinions of using ChatGPT across different nursing fields. Objective: We aim to synthesize the status and opinions of using ChatGPT according to different nursing fields, as well as assess ChatGPT's strengths, weaknesses, and the potential impacts it may cause. Methods: This scoping review was conducted following the framework of Arksey and O'Malley and guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). A comprehensive literature research was conducted in 4 web-based databases (PubMed, Embase, Web of Science, and CINHAL) to identify studies reporting the opinions of using ChatGPT in nursing fields from 2022 to September 3, 2023. The references of the included studies were screened manually to further identify relevant studies. Two authors conducted studies screening, eligibility assessments, and data extraction independently. Results: A total of 30 studies were included. The United States (7 studies), Canada (5 studies), and China (4 studies) were countries with the most publications. In terms of fields of concern, studies mainly focused on "ChatGPT and nursing education" (20 studies), "ChatGPT and nursing practice" (10 studies), and "ChatGPT and nursing research, writing, and examination" (6 studies). Six studies addressed the use of ChatGPT in multiple nursing fields. Conclusions: As an emerging artificial intelligence technology, ChatGPT has great potential to revolutionize nursing education, nursing practice, and nursing research. However, researchers, institutions, and administrations still need to critically examine its accuracy, safety, and privacy, as well as academic misconduct and potential ethical issues that it may lead to before applying ChatGPT to practice.

Indexed as

Artificial IntelligenceEducation, NursingNursingHumansartificial intelligenceChatGPTgenerative AIlarge language modelnursingnursing educationscoping review

Identifiers

PMID39622702
PMCPMC11611787

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.