ArticleRevista latino-americana de enfermagem2024
Using the Chat Generative Pre-trained Transformer in academic writing in health: a scoping review.
Article in Revista latino-americana de enfermagem, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- The Influencing Factors of Medical Postgraduates' Usage Intention Toward Artificial Intelligence-Generated Content Tools in Academic Research: Qualitative Analysis.Journal of medical Internet research · 2026Article
- The landscape of artificial intelligence tools and platforms for evidence synthesis: a scoping review.Systematic reviews · 2026Article
- Generative artificial intelligence in ophthalmology research writing: A comprehensive review of applications, detection tools, and ethical considerations.Taiwan journal of ophthalmologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveto map the scientific literature regarding the use of the Chat Generative Pre-trained Transformer, ChatGPT, in academic writing in health.
methodthis was a scoping review, following the JBI methodology. Conventional databases and gray literature were included. The selection of studies was applied after removing duplicates and individual and paired evaluation. Data were extracted based on an elaborate script, and presented in a descriptive, tabular and graphical format.
resultsthe analysis of the 49 selected articles revealed that ChatGPT is a versatile tool, contributing to scientific production, description of medical procedures and preparation of summaries aligned with the standards of scientific journals. Its application has been shown to improve the clarity of writing and benefits areas such as innovation and automation. Risks were also observed, such as the possibility of lack of originality and ethical issues. Future perspectives highlight the need for adequate regulation, agile adaptation and the search for an ethical balance in incorporating ChatGPT into academic writing.
conclusionChatGPT presents transformative potential in academic writing in health. However, its adoption requires rigorous human supervision, solid regulation, and transparent guidelines to ensure its responsible and beneficial use by the scientific community.
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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.