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AI Writing Vocabulary in Ophthalmology: Faster Non-Native Adoption, Unchanged Outcomes
Alessandro Berni1, Daniel Shu Wei Ting2, Greta Caputo3
1Department of Neurosciences, Psychology, Drug Research, and Child Health, Eye Clinic, University of Florence, AOU Careggi, Florence, Italy.; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore..
After ChatGPT, non-native English-speaking ophthalmology authors adopted AI writing styles faster than native English speakers. This shift in vocabulary did not correlate with increased publication rates or journal placement, indicating a population-level trend rather than individual quality.
Area of Science:
- Ophthalmology
- Bibliometrics
- Artificial Intelligence
Background:
- The rapid advancement of large language models (LLMs) like ChatGPT has influenced academic writing across disciplines.
- Understanding the impact of LLMs on scientific literature, particularly in specialized fields like ophthalmology, is crucial for evaluating research integrity and trends.
Purpose of the Study:
- To quantify the changes in LLM-associated writing vocabulary in ophthalmology publications following the advent of ChatGPT.
- To investigate whether these vocabulary changes differ based on the first author's country language group (native vs. non-native English-speaking).
- To determine if there were any shifts in publishing outcomes associated with these vocabulary changes.
Main Methods:
- A retrospective, cross-sectional bibliometric study analyzing a 10-year publication census (2015-2024) from high-impact ophthalmology journals.
- Comparison of PubMed abstracts pre-ChatGPT (2018-2019) and post-ChatGPT (2023-2024) to count LLM-associated words.
- Interrupted time-series analysis to assess changes in publication share and top-quartile journal placement for authors affiliated with native-English-speaking versus non-native-English-speaking countries.
Main Results:
- The rate of LLM-associated words per million increased 2.1-fold post-ChatGPT (320 to 668).
- This increase was significantly steeper among non-native English-affiliated authors (interaction IRR, 0.61; P < .001), a finding robust to adjustments.
- No significant post-ChatGPT changes were observed in the proportion of publications or top-quartile journal placements for non-native English-affiliated authors.
Conclusions:
- Non-native English-affiliated authors in ophthalmology adopted AI-associated writing vocabulary more rapidly after ChatGPT's release.
- This adoption of AI-associated vocabulary did not lead to a corresponding increase in publication frequency or placement in high-impact journals.
- The observed vocabulary changes reflect a population-level stylistic shift influenced by AI tools, not necessarily an indicator of individual article quality or confirmed AI usage.
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