Evidence map›Paper›PMID 39229462›Full record

ArticleDigital health

Evaluation of the quality and readability of ChatGPT responses to frequently asked questions about myopia in traditional Chinese language.

Li-Chun Chang, Chi-Chin Sun, Ting-Han Chen, Der-Chong Tsai, Hui-Ling Lin, Li-Ling Liao

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Article in Digital health. 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

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

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

6 authors.

Li-Chun ChangSchool of Nursing, Chang Gung University of Science and Technology, Gueishan.
Chi-Chin SunDepartment of Ophthalmology, Chang Gung Memorial Hospital, Keelung.
Ting-Han ChenChang Gung University of Science and Technology, Taoyuan City.
Der-Chong TsaiFaculty of Medicine, National Yang Ming Chiao Tung University, School of Medicine, Taipei.
Hui-Ling LinSchool of Nursing, Chang Gung University of Science and Technology, Gueishan.
Li-Ling LiaoDepartment of Public Health, College of Health Science, Kaohsiung Medical University, Kaohsiung City.ORCID https://orcid.org/0000-0003-0867-2699

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: ChatGPT can serve as an adjunct informational tool for ophthalmologists and their patients. However, the reliability and readability of its responses to myopia-related queries in the Chinese language remain underexplored. Purpose: This study aimed to evaluate the ability of ChatGPT to address frequently asked questions (FAQs) about myopia by parents and caregivers. Method: Myopia-related FAQs were input three times into fresh ChatGPT sessions, and the responses were evaluated by 10 ophthalmologists using a Likert scale for appropriateness, usability, and clarity. The Chinese Readability Index Explorer (CRIE) was used to evaluate the readability of each response. Inter-rater reliability among the reviewers was examined using Cohen's kappa coefficient, and Spearman's rank correlation analysis and one-way analysis of variance were used to investigate the relationship between CRIE scores and each criterion. Results: Forty-five percent of the responses of ChatGPT in Chinese language were appropriate and usable and only 35% met all the set criteria. The CRIE scores for 20 ChatGPT responses ranged from 7.29 to 12.09, indicating that the readability level was equivalent to a middle-to-high school level. Responses about the treatment efficacy and side effects were deficient for all three criteria. Conclusions: The performance of ChatGPT in addressing pediatric myopia-related questions is currently suboptimal. As parents increasingly utilize digital resources to obtain health information, it has become crucial for eye care professionals to familiarize themselves with artificial intelligence-driven information on pediatric myopia.

Indexed as

ChatGPThealth educationmyopiaophthalmologistsquality

Identifiers

PMID39229462
PMCPMC11369861

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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.