ArticleSkin health and disease2025
Assessing the readability of dermatological patient information leaflets generated by ChatGPT-4 and its associated plugins.
Article in Skin health and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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Who cites it
2 citing papers in PubMed.
- Readability of dermatology patient education materials: a comparative analysis of Turkish Dermatology Association brochures and texts generated by ChatGPT and Gemini.Turkish journal of medical sciences · 2026Article
- Evaluating the usefulness of ChatGPT and Gemini in generating educational content for patients with vitiligo: a comparative cross-sectional study.Proceedings (Baylor University. Medical Center)Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: In the UK, 43% of adults struggle to understand health information presented in standard formats. As a result, Health Education England recommends that patient information leaflets (PILs) be written at a readability level appropriate for an 11-year-old. Objectives: To evaluate the ability of ChatGPT-4 and its three dermatology-specific plugins to generate PILs that meet readability recommendations and compare their readability with existing British Association of Dermatologists (BAD) PILs. Methods: ChatGPT-4 and its three plugins were used to generate PILs for 10 preselected dermatological conditions. The readability of these PILs was assessed using three readability formulas Simple Measure of Gobbledygook (SMOG), Flesch Reading Ease Test (FRET) and Flesch-Kincaid Grade Level Test (FKGLT) and compared against the readability of BAD PILs. A one-way ANOVA was conducted to identify any significant differences. Results: The readability scores of PILs generated by ChatGPT-4 and its plugins did not meet the recommended target range. However, some of these PILs demonstrated more favourable mean readability scores compared with those from the BAD, with certain plugins, such as Chat with a Dermatologist, showing significant differences in mean SMOG ( Conclusions: ChatGPT-4 can produce dermatological PILs free from misleading information, occasionally surpassing BAD PILs in terms of readability. However, these PILs still fall short of being easily understood by the general public, and the content requires rigorous verification by healthcare professionals to ensure reliability and quality.
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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.