ReviewJB & JS open access
Trends in Artificial Intelligence Usage in Orthopaedic Surgery Residency Applications.
Review in JB & JS open access. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The public adoption of artificial intelligence (AI) tools such as ChatGPT has expanded rapidly in recent years, including growing use among healthcare professionals. The purpose of this study was to assess the use of AI and plagiarism in orthopaedic surgery residency applications across the 2022 to 2023, 2023 to 2024, and 2024 to 2025 application cycles. Methods: Deidentified letters of recommendation (LORs) and personal statements (PSs) from interviewed applicants across 3 consecutive application cycles at a single institution were analyzed. Blinded reviewers input the documents into an online platform designed to detect AI-generated language and plagiarism. Result: There was a statistically significant increase in the AI usage in LORs during the 2024 to 2025 application cycle (17.8%) compared with the 2023 to 2024 (5.0%) and 2022 to 2023 (5.6%) cycles (p < 0.001). Correspondingly, the originality scores of LORs significantly decreased in 2024 to 2025 (92.4%) compared with 2023 to 2024 (97.3%) and 2022 to 2023 (97.7%) (p < 0.001). By contrast, the AI usage in personal statements significantly decreased in 2024 to 2025 (43.5%) compared with 2023 to 2024 (60.3%) and 2022 to 2023 (65.2%) (p = 0.031). There was no significant difference in plagiarism scores across the 3 cycles for either LORs (p = 0.28) or PSs (p = 0.39). Conclusions: The 2024 to 2025 application cycle showed a marked increase in AI usage in letters of recommendation, while the usage of AI in personal statements declined. These trends reflect evolving patterns in how applicants and letter writers are integrating AI tools into the application process. Level of Evidence: Level III; Retrospective Cohort Study. See Instructions for Authors for a complete description of levels of evidence.
Identifiers
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.