ArticleSeminars in ophthalmology2021
Evaluation of the Content, Quality, and Readability of Patient Accessible Online Resources Regarding Cataracts.
Article in Seminars in ophthalmology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
16 citing papers in PubMed.
- Readability, Quality, Understandability, and Actionability of ChatGPT Generated GI Patient Education Versus AGA Patient Center.Digestive diseases and sciences · 2026Article
- Comparing the readability of online patient education materials for LASIK and cataract surgery.International ophthalmology · 2026Article
- Article
- Large language models: unlocking new potential in patient education for thyroid eye disease.Endocrine · 2025Article
- Assessment of Large Language Models in Cataract Care Information Provision: A Quantitative Comparison.Ophthalmology and therapy · 2025Article
- Readability and Appropriateness of Responses Generated by ChatGPT 3.5, ChatGPT 4.0, Gemini, and Microsoft Copilot for FAQs in Refractive Surgery.Turkish journal of ophthalmology · 2024Article
- Assessment of the Quality, Accountability, and Readability of Online Patient Education Materials for Optic Neuritis.Neuro-ophthalmology (Aeolus Press) · 2024Article
- Comparing the Ability of Google and ChatGPT to Accurately Respond to Oculoplastics-Related Patient Questions and Generate Customized Oculoplastics Patient Education Materials.Clinical ophthalmology (Auckland, N.Z.) · 2024Article
- Article
- Analysis of the Readability and Accountability of Online Patient Education Materials Related to Glaucoma Diagnosis and Treatment.Clinical ophthalmology (Auckland, N.Z.) · 2023Article
- Disparities in Vision Health and Eye Care.Ophthalmology · 2022Article
- Article
- Evaluation of the Appropriateness and Readability of ChatGPT-4 Responses to Patient Queries on Uveitis.Ophthalmology scienceArticle
- Article
- Google Trends-Assisted Analysis of the Readability, Accountability, and Accessibility of Online Patient Education Materials for the Treatment of AMD After US FDA Approval of Pegcetacoplan.Journal of vitreoretinal diseasesArticle
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
purposeTo evaluate the content quality, accuracy, and readability of commonly visited websites by cataract patients contemplating cataract surgery.
settingFreely available online information.
designCross-sectional study.
methodsTen websites were evaluated in a cross-sectional study for content analysis using a grading sheet of 40 questions individually scored by three ophthalmologists. JAMA benchmarks were used to assess the quality. An online readability tool,
resultsThere was a significant difference between the content and accuracy of each website according to a Kruskal-Wallis test (H = 22.623,
conclusionCommonly accessed online resources on cataracts and cataract surgery are insufficient to provide patients with a clear and complete understanding of their condition as well as available medical and surgical treatment options.
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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.