Evidence map›Paper›PMID 39464759›Full record

ArticleRomanian journal of ophthalmology

Appropriateness and readability of Google Bard and ChatGPT-3.5 generated responses for surgical treatment of glaucoma.

Parul Ichhpujani, Uday Pratap Singh Parmar, Suresh Kumar

Abstract read
In one paragraph

Article in Romanian journal of ophthalmology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
–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

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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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

3 authors.

Parul IchhpujaniDepartment of Ophthalmology, Government Medical College and Hospital, Chandigarh, India.
Uday Pratap Singh ParmarDepartment of Ophthalmology, Government Medical College and Hospital, Chandigarh, India.
Suresh KumarDepartment of Ophthalmology, Government Medical College and Hospital, Chandigarh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: To evaluate the appropriateness and readability of the medical knowledge provided by ChatGPT-3.5 and Google Bard, artificial-intelligence-powered conversational search engines, regarding surgical treatment for glaucoma. Methods: In this retrospective, cross-sectional study, 25 common questions related to the surgical management of glaucoma were asked on ChatGPT-3.5 and Google Bard. Glaucoma specialists graded the responses' appropriateness, and different scores assessed readability. Results: Appropriate answers to the posed questions were obtained in 68% of the responses with Google Bard and 96% with ChatGPT-3.5. On average, the responses generated by Google Bard had a significantly lower proportion of sentences, having more than 30 and 20 syllables (23% and 52% respectively) compared to ChatGPT-3.5 (66% and 82% respectively), as noted by readability. Google Bard had significantly (p<0.0001) lower readability grade scores and significantly higher "Flesch Reading ease score", implying greater ease of readability amongst the answers generated by Google Bard. Discussion: Many patients and their families turn to LLM chatbots for information, necessitating clear and accurate content. Assessments of online glaucoma information have shown variability in quality and readability, with institutional websites generally performing better than private ones. We found that ChatGPT-3.5, while precise, has lower readability than Google Bard, which is more accessible but less precise. For example, the Flesch Reading Ease Score was 57.6 for Google Bard and 22.6 for ChatGPT, indicating Google Bard's content is easier to read. Moreover, the Gunning Fog Index scores suggested that Google Bard's text is more suitable for a broader audience. ChatGPT's knowledge is limited to data up to 2021, whereas Google Bard, trained with real-time data, offers more current information. Further research is needed to evaluate these tools across various medical topics. Conclusion: The answers generated by ChatGPT-3.5™ AI are more accurate than the ones given by Google Bard. However, comprehension of ChatGPT-3.5™ answers may be difficult for the public with glaucoma. This study emphasized the importance of verifying the accuracy and clarity of online information that glaucoma patients rely on to make informed decisions about their ocular health. This is an exciting new area for patient education and health literacy.

Indexed as

ComprehensionGlaucomaCross-Sectional StudiesHealth LiteracyHumansInternetRetrospective StudiesSearch EngineAI = Artificial IntelligenceAMA = American Medical AssociationChatGPTGDD = Glaucoma Drainage DevicesglaucomaGoogle BardGPT-3 = Generative Pre-trained Transformer 3IOP = intraocular pressureLaMBDA = Language Model for Dialogue ApplicationsLarge Language ModelLLM = Large Language ModelSMOG = Simple Measure of Gobbledygook

Identifiers

PMID39464759
PMCPMC11503238

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Registered trials

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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.