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

已发表的运动医学研究中基于大型语言模型的写作:揭示其日益增长的影响力

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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 (Arthroscopy: The Journal of Arthroscopic and Related Surgery [Arthroscopy], Orthopaedic Journal of Sports Medicine [OJSM], The American Journal of Sports Medicine [AJSM], British Journal of Sports Medicine [BJSM], and Knee Surgery, Sports Traumatology, Arthroscopy [KSSTA]). After removing tables, figures, and references, full texts were assessed for AI-generated content using ZeroGPT. To establish an AI-generated content threshold, articles published before the release of ChatGPT were also assessed for AI-generated content. A 28.69% threshold was determined from 518 articles published before the release of ChatGPT. Articles published after the release of ChatGPT that exceeded this threshold were analyzed across journals and publication dates using chi-square and regression analyses. RESULTS: Among the 3596 articles published after the release of ChatGPT and included in this study, 3.28% exceeded the established threshold. Moreover, Arthroscopy was flagged as having the highest AI use among all 5 journals (Arthroscopy = 7.17%; OJSM = 4.01%; AJSM = 3.34%; BJSM = 1.42%; KSSTA = 0.93%; P < .001). Finally, temporal analysis identified a significant rise in the use of AI, increasing from 2.38% in January 2023 to 6.25% in December 2024 (r (2) = 0.34; P < .003). 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.

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