Evidence map›Paper›PMID 39146013›Full record

ArticleJournal of medical Internet research2024

ChatGPT and Google Assistant as a Source of Patient Education for Patients With Amblyopia: Content Analysis.

Gloria Wu, David A Lee, Weichen Zhao, Adrial Wong, Rohan Jhangiani, Sri Kurniawan

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

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

5 citing papers in PubMed, 1 synthesis or guideline 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

6 authors.

Gloria WuUniversity of California, San Francisco School of Medicine, San Francisco, CA, United States.ORCID 0000-0002-0050-2401
David A LeeMcGovern Medical School, University of Texas Health Science Center at Houston, Houston, CA, United States.ORCID 0009-0009-4124-4339
Weichen ZhaoCollege of Biological Sciences, University of California, Davis, Davis, CA, United States.ORCID 0000-0002-6992-950X
Adrial WongCollege of Biological Sciences, University of California, Davis, Davis, CA, United States.ORCID 0009-0005-6566-5315
Rohan JhangianiDepartment of Computational Media, University of California, Santa Cruz, Santa Cruz, CA, United States.ORCID 0009-0002-2541-5619
Sri KurniawanDepartment of Computational Media, University of California, Santa Cruz, Santa Cruz, CA, United States.ORCID 0000-0003-0372-5800

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe queried ChatGPT (OpenAI) and Google Assistant about amblyopia and compared their answers with the keywords found on the American Association for Pediatric Ophthalmology and Strabismus (AAPOS) website, specifically the section on amblyopia. Out of the 26 keywords chosen from the website, ChatGPT included 11 (42%) in its responses, while Google included 8 (31%).

objectiveOur study investigated the adherence of ChatGPT-3.5 and Google Assistant to the guidelines of the AAPOS for patient education on amblyopia.

methodsChatGPT-3.5 was used. The four questions taken from the AAPOS website, specifically its glossary section for amblyopia, are as follows: (1) What is amblyopia? (2) What causes amblyopia? (3) How is amblyopia treated? (4) What happens if amblyopia is untreated? Approved and selected by ophthalmologists (GW and DL), the keywords from AAPOS were words or phrases that deemed significant for the education of patients with amblyopia. The "Flesch-Kincaid Grade Level" formula, approved by the US Department of Education, was used to evaluate the reading comprehension level for the responses from ChatGPT, Google Assistant, and AAPOS.

resultsIn their responses, ChatGPT did not mention the term "ophthalmologist," whereas Google Assistant and AAPOS both mentioned the term once and twice, respectively. ChatGPT did, however, use the term "eye doctors" once. According to the Flesch-Kincaid test, the average reading level of AAPOS was 11.4 (SD 2.1; the lowest level) while that of Google was 13.1 (SD 4.8; the highest required reading level), also showing the greatest variation in grade level in its responses. ChatGPT's answers, on average, scored 12.4 (SD 1.1) grade level. They were all similar in terms of difficulty level in reading. For the keywords, out of the 4 responses, ChatGPT used 42% (11/26) of the keywords, whereas Google Assistant used 31% (8/26).

conclusionsChatGPT trains on texts and phrases and generates new sentences, while Google Assistant automatically copies website links. As ophthalmologists, we should consider including "see an ophthalmologist" on our websites and journals. While ChatGPT is here to stay, we, as physicians, need to monitor its answers.

Indexed as

AmblyopiaInternetPatient Education as TopicHumansOphthalmologyamblyopiaAmerican Association for Pediatric Ophthalmology and StrabismusChatGPTeducationGoogleGoogle Assistanthealth literacymonitoringophthalmologistophthalmologypatient educationpediatric

Identifiers

PMID39146013
PMCPMC11362700

What OpenQuestion holds

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LicenceCC BY
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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.