ArticleCureus2024
A Cross-Sectional Study Comparing Patient Information Guides Generated by ChatGPT and Google Gemini for Common Radiological Procedures.
Article in Cureus, 2024. 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionArtificial intelligence (AI) plays a significant role in creating brochures on radiological procedures for patient education. Thus, this study aimed to evaluate the responses generated by ChatGPT (San Francisco, CA: OpenAI) and Google Gemini (Mountain View, CA: Google LLC) on abdominal ultrasound, abdominal CT scan, and abdominal MRI. METHODOLOGY: A cross-sectional original research was conducted over one week in June 2024 to evaluate the quality of patient information brochures produced by ChatGPT 3.5 and Google Gemini 1.5 Pro. The study assessed variables including word count, sentence count, average words per sentence, average syllables per sentence, grade level, and ease score using the Flesch-Kincaid calculator. Similarity percentage was evaluated using Quillbot (Chicago, IL: Quillbot Inc.), and reliability was measured using the modified DISCERN score. Statistical analysis was conducted using R version 4.3.2 (Vienna, Austria: R Foundation for Statistical Computing).
resultsThere is no significant difference between sentence count (p=0.8884), average words per sentence (p=0.1984), average syllables per sentence (p=0.3868), ease (p=0.1812), similarity percentage (p=0.8110), and reliability score (p=0.6495). However, there is a statistically significant difference, with ChatGPT having a higher word count (p=0.0409) and grade level (p=0.0482) than Google Gemini. P-values <0.05 were considered significant.
conclusionsBoth ChatGPT and Google Gemini demonstrate the ability to generate content that maintains consistency assessed through readability and reliability scores. Nevertheless, the noticeable disparities in word count and grade level underscore a crucial area for improvement in customizing content to accommodate varying levels of patient literacy.
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.