ArticleOphthalmology science
Evaluation of the Appropriateness and Readability of ChatGPT-4 Responses to Patient Queries on Uveitis.
Article in Ophthalmology science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluating Large Language Models in Ophthalmology: Systematic Review.Journal of medical Internet research · 2025Pooled it
- ChatGPT's role in alleviating anxiety in total knee arthroplasty consent process: a randomized controlled trial pilot study.International journal of surgery (London, England) · 2025Trial
- Investigating the Readability and Quality of AI Systems to Trending Questions About Food Poisoning.Journal of food science · 2026Article
- How Far Have Large Language Models Advanced in Ophthalmology? A Systematic Review of Their Development, Evaluation, and Readiness for Clinical Use.Research square · 2026Article
- Assessing ChatGPT's Performance in Delineating Uveitis: An analysis of responses to real-world case presentations.medRxiv : the preprint server for health sciences · 2026Article
- Utility of ChatGPT-4o in Creating Patient Handouts in Ophthalmology: A Comparison With American Academy of Ophthalmology Educational Materials.Translational vision science & technology · 2026Article
- Can large language models provide quality, reliable and readable information about sudden infant death syndrome?BMC pediatrics · 2026Article
- Evaluation of the artificial intelligence chatbots in frequently asked questions about retinitis pigmentosa: a comparative analysis between ChatGPT-4 and Gemini-2.0.International journal of retina and vitreous · 2025Article
- Large language models: unlocking new potential in patient education for thyroid eye disease.Endocrine · 2025Article
- Evaluating ChatGPT's Utility in Biologic Therapy for Systemic Lupus Erythematosus: Comparative Study of ChatGPT and Google Web Search.JMIR formative research · 2025Article
- ChatGPT-Generated Responses Across Orthopaedic Sports Medicine Surgery Vary in Accuracy, Quality, and Readability: A Systematic Review.Arthroscopy, sports medicine, and rehabilitation · 2025Review
- Evaluating Large Language Models in Ptosis-Related inquiries: A Cross-Lingual Study.Translational vision science & technology · 2025Article
- Assessing the Quality and Reliability of ChatGPT's Responses to Radiotherapy-Related Patient Queries: Comparative Study With GPT-3.5 and GPT-4.JMIR cancer · 2025Article
- Reply.The journal of allergy and clinical immunology. Global · 2025Article
- Advances in the application of artificial intelligence in ophthalmic education and clinical training.Frontiers in medicine · 2025Review
Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To compare the utility of ChatGPT-4 as an online uveitis patient education resource with existing patient education websites. Design: Evaluation of technology. Participants: Not applicable. Methods: The term "uveitis" was entered into the Google search engine, and the first 8 nonsponsored websites were selected to be enrolled in the study. Information regarding uveitis for patients was extracted from Healthline, Mayo Clinic, WebMD, National Eye Institute, Ocular Uveitis and Immunology Foundation, American Academy of Ophthalmology, Cleveland Clinic, and National Health Service websites. ChatGPT-4 was then prompted to generate responses about uveitis in both standard and simplified formats. To generate the simplified response, the following request was added to the prompt: 'Please provide a response suitable for the average American adult, at a sixth-grade comprehension level.' Three dual fellowship-trained specialists, all masked to the sources, graded the appropriateness of the contents (extracted from the existing websites) and responses (generated responses by ChatGPT-4) in terms of personal preference, comprehensiveness, and accuracy. Additionally, 5 readability indices, including Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning Fog Index, Coleman-Liau Index, and Simple Measure of Gobbledygook index were calculated using an online calculator, Readable.com, to assess the ease of comprehension of each answer. Main Outcome Measures: Personal preference, accuracy, comprehensiveness, and readability of contents and responses about uveitis. Results: A total of 497 contents and responses, including 71 contents from existing websites, 213 standard responses, and 213 simplified responses from ChatGPT-4 were recorded and graded. Standard ChatGPT-4 responses were preferred and perceived to be more comprehensive by dually trained (uveitis and retina) specialist ophthalmologists while maintaining similar accuracy level compared with existing websites. Moreover, simplified ChatGPT-4 responses matched almost all existing websites in terms of personal preference, accuracy, and comprehensiveness. Notably, almost all readability indices suggested that standard ChatGPT-4 responses demand a higher educational level for comprehension, whereas simplified responses required lower level of education compared with the existing websites. Conclusions: This study shows that ChatGPT can provide patients with an avenue to access comprehensive and accurate information about uveitis, tailored to their educational level. Financial Disclosures: The author(s) have no proprietary or commercial interest in any materials discussed in this article.
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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.