Evidence map›Paper›PMID 41000422›Full record

ArticleOrthopaedic journal of sports medicine2025

Large Language Model-Based Writing in Published Sports Medicine Research: Uncovering a Growing Influence.

Joseph E Nassar, Michael J Farias, Manjot Singh, Peter V Dinh, Maxwell Sahhar, Mohammad Daher, Ryan Fallon, Stephen E Marcaccio, Alan H Daniels, Brett D Owens

Abstract read
In one paragraph

Article in Orthopaedic journal of sports medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Evolution of Artificial Intelligence Adoption inOrthopaedic journal of sports medicine · 2026
    Article
  2. Article
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

10 authors.

Joseph E NassarDepartment of Orthopaedics, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.ORCID https://orcid.org/0000-0002-2475-4996
Michael J FariasDepartment of Orthopaedics, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.ORCID https://orcid.org/0000-0002-9705-1351
Manjot SinghDepartment of Orthopaedics, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.ORCID https://orcid.org/0000-0003-4524-6226
Peter V DinhDepartment of Orthopaedics, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.ORCID https://orcid.org/0009-0001-2015-4643
Maxwell SahharDepartment of Orthopaedics, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Mohammad DaherDepartment of Orthopaedics, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.ORCID https://orcid.org/0000-0002-9256-9952
Ryan FallonDepartment of Orthopaedics, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.ORCID https://orcid.org/0009-0005-5302-9725
Stephen E MarcaccioDepartment of Orthopaedics, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Alan H DanielsDepartment of Orthopaedics, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Brett D OwensDepartment of Orthopaedics, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In the past few years, there has been an increase in the use of artificial intelligence (AI)-based large language models, including ChatGPT, in scientific research. This has shown promise in its ability to draft high-quality articles; however, there has been concerns regarding its ethical use in generating original research. Purpose/Hypothesis: The purpose of this study was to quantify the percentage of AI use in articles that were published in major sports medicine journals before and after the release of ChatGPT. It was hypothesized that AI use has changed and increased over time. Study Design: Cross-sectional study. Methods: All articles that were published from 2023 to 2024 in the 5 sports medicine journals with the highest impact factors were identified ( Results: Among the 3596 articles published after the release of ChatGPT and included in this study, 3.28% exceeded the established threshold. Moreover, Conclusion: AI use in sports medicine research remains low but is steadily rising. Editorial policies allowing AI usage may, in turn, perpetuate its use in published sports medicine articles.

Indexed as

artificial intelligencemanuscript writingresearch integritysports medicine

Identifiers

PMID41000422
PMCPMC12457763

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.