ArticleCureus2025
Readability Comparison of AI-Generated Versus UpToDate Educational Content on Stroke Management: A Cross-Sectional Study.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
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
Introduction Stroke is a major cause of global morbidity and mortality. Readability of educational material is critical for rapid clinical decision-making among healthcare professionals. UpToDate (UpToDate, Inc., Waltham, MA) is a widely used, peer-reviewed point-of-care clinical resource, while ChatGPT (OpenAI, San Francisco, CA) is an emerging AI-based educational support tool. However, a formal comparison of their linguistic accessibility has not been performed. Objective To compare the readability and linguistic complexity of educational material on stroke generated by ChatGPT (GPT-4o) versus content retrieved from UpToDate, using validated readability metrics. Design, setting, and participants This cross-sectional study was conducted between May 27 and June 4, 2025. ChatGPT (GPT-4o, accessed May 27, 2025) was prompted to generate educational content on stroke. A corresponding section from UpToDate (accessed May 27, 2025) was extracted. Only prose content was analyzed. Readability parameters assessed included total word count, sentence count, word/sentence ratio (average words per sentence), Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG) Index, difficult word count, and difficult word percentage. Data were analyzed using IBM SPSS v25 (IBM Corp., Armonk, NY) and R v4.3.2 (R Foundation for Statistical Computing, Vienna, Austria). The Mann-Whitney U test was used. P < 0.05 was considered statistically significant. Results UpToDate content was substantially longer (median = 2772 vs. 304 words; p = 0.008) and used more sentences (median = 134 vs. 23; p = 0.032) and difficult words (median = 857 vs. 88; p = 0.008) compared to ChatGPT. The word/sentence ratio (average words per sentence) was also higher (21.7 vs. 13.2; p = 0.008). However, no statistically significant differences were observed for FRE (p = 1.000), FKGL (p = 0.222), SMOG Index (p = 0.151), or difficult word percentage (p = 0.690). Conclusions ChatGPT produces shorter and more concise educational content on stroke while maintaining comparable readability to UpToDate. The lower linguistic density may enhance rapid orientation for trainees; however, the reduced depth indicates ChatGPT should supplement, not replace, established peer-reviewed resources. Future research should explore multiple medical topics, additional AI models, and assess the clinical applicability and accuracy of AI-generated content.
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.