Evidence map›Paper›PMID 40861713›Full record

ArticleCureus2025

A Cross-Sectional Study to Evaluate the Effectiveness of Patient Information Guides Produced by ChatGPT Versus Google Gemini for Three Pediatric Illnesses.

Kavya Thayappa, Renee Manake, Sai Brigisha Kyasa, Aishwarya Babu

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kavya ThayappaPediatrics, MVJ Medical College and Research Hospital, Bengaluru, IND.
Renee ManakeInternal Medicine, Makerere University College of Health Sciences, School of Medicine, Kampala, UGA.
Sai Brigisha KyasaPediatrics, Kamineni Institute of Medical Sciences, Nalgonda, IND.
Aishwarya BabuInternal Medicine, Tbilisi State Medical University, Tbilisi, GEO.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesEducating pediatric patients and their caregivers about the disease is crucial for improving treatment adherence, recognizing complications early, and alleviating anxiety. AI tools such as ChatGPT and Google Gemini offer personalized education, benefiting patients and providers, and are increasingly utilized in healthcare. This study aims to compare patient education guides created by ChatGPT and Google Gemini for acute otitis media, pneumonia, and pharyngitis.

methodsPatient information guides on pediatric diseases generated by ChatGPT and Google Gemini were evaluated by comparing various variables (words, sentences, average words per sentence, average syllables per word, grade level, and ease score) and further assessed for ease using the Flesch-Kincaid calculator, similarity using Quillbot, and reliability using the Modified Discern score. Statistical analysis was done using R v4.3.2.

resultsBoth tools' responses were statistically compared. No significant difference was found in word count (ChatGPT: 477.3; Google Gemini: 394.0; p=0.0765) or sentences (ChatGPT: 35.33; Google Gemini: 46.33; p=0.184). Google Gemini scored slightly higher in ease (ChatGPT: 37.79; Google Gemini: 57.10) and grade level (ChatGPT: 11.40; Google Gemini: 7.43), but these were not statistically significant (p>0.05), indicating no clear superiority. CONCLUSIONS FOR PRACTICE: In a comparison of patient education guides created by both tools for acute otitis media, pneumonia, and pharyngitis, there was no statistically significant difference to determine the superiority of one AI tool over the other. Further studies should comprehensively evaluate various AI tools across a broader range of diseases. It is also important to assess whether AI tools can provide real-time, verifiable content based on the latest medical advancements.

Indexed as

artificial intelligencechatgpteducational toolgoogle geminipatient education brochurepediatric diseases

Identifiers

PMID40861713
PMCPMC12377924

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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.