ArticleThe Laryngoscope2025
An Evaluation of Current Trends in AI-Generated Text in Otolaryngology Publications.
Article in The Laryngoscope, 2025. 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.
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Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
objectivesSince the release of ChatGPT-4 in March 2023, large language models (LLMs) application in biomedical manuscript production has been widespread. GPT-modified text detectors, such as GPTzero, lack sensitivity and reliability and do not quantify the amount of AI-generated text. However, recent work has identified certain adjectives more frequently used by LLMs that can help identify and quantify LLM-modified text. The aim of this study is to utilize these adjectives to identify LLM-generated text in otolaryngology publications. STUDY
designMeta-research.
methodsTwenty-five otolaryngology journals were studied between November 2022 and July 2024, encompassing 8751 published works. Articles from countries where ChatGPT-4 is not available were removed, yielding 7702 articles for study inclusion. These publications were analyzed using a Python script to determine the frequency of the top 100 adjectives disproportionately generated by ChatGPT-4.
resultsA significant increase in the frequency of adjectives associated with GPT use was observed from November 2023 to July 2024 across all journals (p < 0.001), with a significant difference before and after the release of ChatGPT in March 2023. Journals with higher impact factors had significantly lower usage of GPT-associated adjectives than those with lower impact factors (p < 0.001). There was no significant difference in GPT-associated adjective use by first authors with a doctoral degree versus those without. Publications by authors from English-speaking countries demonstrated a significantly more frequent use of LLM-associated adjectives (p < 0.001).
conclusionsThis study suggests that ChatGPT use in otolaryngology manuscript production has significantly increased since the release of ChatGPT-4. Future research should be aimed at further characterizing the landscape of AI-generated text in otolaryngology and developing tools that encourage authors' transparency regarding the use of LLMs. LEVEL OF EVIDENCE: NA.
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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.