ArticleCureus2026
Artificial Intelligence-Generated Versus Professional Society Patient Education Materials in Gastroenterology, Surgery, Ophthalmology, and Anesthesiology: A Comparative Analysis of Readability and Health Literacy Metrics.
Article in Cureus, 2026. 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
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
No grant is acknowledged in the PubMed record.
Abstract
aimProfessional society patient education materials frequently exceed recommended literacy levels, limiting equitable health information access. This study aimed to compare the readability, information quality, understandability, and actionability of artificial intelligence (AI)-generated patient education materials versus professional society materials across gastroenterology, surgery, ophthalmology, and anesthesiology. SUBJECTS AND
methodsWe conducted a cross-sectional comparative analysis of 100 paired topics (25 per specialty), comparing professional society materials with the responses generated by ChatGPT (OpenAI, San Francisco, California, United States) under standardized conditions. Readability was assessed using the Flesch-Kincaid grade level, information quality with DISCERN, and understandability and actionability with the Patient Education Materials Assessment Tool (PEMAT). Paired two-sided t-tests assessed within-specialty differences.
resultsIn surgery, AI-generated materials had lower reading levels and higher quality, understandability, and actionability (all p<0.001). In anesthesiology, AI materials were more readable (p<0.001) with no differences in other measures. In ophthalmology, AI improved readability (p<0.001), while professional society materials had higher quality and understandability (p<0.01) with no difference in actionability. In gastroenterology, AI materials had higher reading levels (p<0.001) with no differences in quality or usability.
conclusionThe performance of AI-generated patient education materials varied by specialty and appeared to depend on the structure and complexity of clinical content. AI improved readability in several domains, but these gains were not uniform across specialties, particularly in areas requiring more complex or longitudinal explanations.
Indexed as
Identifiers
What OpenQuestion holds
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.