ArticleCureus2025
Comparative Analysis of ChatGPT and Google Gemini in Generating Patient Educational Resources on Cardiac Health: A Focus on Exercise-Induced Arrhythmia, Sleep Habits, and Dietary Habits.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- An AI-driven evidence ecosystem for cardiometabolic nutrition: bridging the gap from multiomics to patient empowerment.Frontiers in nutrition · 2026Article
- Online platform vs. doctors: a comparative exploration of congenital cataract patient education from virtual to reality.Frontiers in artificial intelligence · 2025Article
- Research progress and implications of the application of large language model in shared decision-making in China's healthcare field.Frontiers in public health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPatient education is crucial in cardiovascular health, aiding in shared decision-making and improving adherence to treatments. Artificial intelligence (AI) tools, including ChatGPT (OpenAI, San Francisco, CA) and Google Gemini (Google LLC, Mountain View, CA), are revolutionizing patient education by providing personalized, round-the-clock access to information, enhancing engagement, and improving health literacy. The paper aimed to compare the responses generated by ChatGPT and Google Gemini for creating patient education guides on exercise-induced arrhythmia, sleep habits and cardiac health, and "dietary habits and cardiac health. METHODOLOGY: A comparative observational study was conducted evaluating three AI-generated guides: "exercise-induced arrhythmia," "sleep habits and cardiac health," and "dietary habits and cardiac health," using ChatGPT and Google Gemini. Responses were evaluated for word count, sentence count, grade level, ease score, and readability using the Flesch-Kincaid calculator and QuillBot (QuillBot, Chicago, IL) plagiarism tool for similarity score. Reliability was assessed with the modified DISCERN score. Statistical analysis was conducted using R version 4.3.2 (The R Core Team, R Foundation for Statistical Computing, Vienna, Austria).
resultsChatGPT-generated responses had an overall higher average word count when compared to Google Gemini; however, the difference was not statistically significant (p = 0.2817). Google Gemini scored higher on ease of understanding, though this difference was also not significant (p = 0.7244). There were no significant differences in sentence count or average words per sentence. ChatGPT tended to produce more complex content for certain topics, whereas Google Gemini's responses were generally easier to read. Similarity scores were higher for ChatGPT across all topics, while reliability scores varied by topic, with Google Gemini performing better for exercise-induced arrhythmia and ChatGPT for sleep habits and cardiac health.
conclusionsThe study found no significant difference in ease score, grade score, and reliability between AI-generated responses for a cardiology disorders brochure. Future research should explore AI techniques across various disorders, ensuring up-to-date and reliable public information.
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Registered trials
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