Evidence map›Paper›PMID 40211643›Full record

ArticleUlusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES2025

Assessing the quality of ChatGPT's responses to commonly asked questions about trigger finger treatment.

Mehmet Can Gezer, Mehmet Armangil

Abstract read
In one paragraph

Article in Ulusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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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

2 authors.

Mehmet Can GezerDepartment of Orthopedics and Traumatology, Mamak State Hospital, Ankara-Türkiye.
Mehmet ArmangilDepartment of Orthopedics and Traumatology, Hand Surgery Unit, Ankara University Faculty of Medicine, Ankara-Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aims to evaluate the accuracy and reliability of Generative Pre-trained Transformer (ChatGPT; OpenAI, San Francisco, California) in answering patient-related questions about trigger finger. This evaluation has the potential to enhance patient education prior to treatment and provides insight into the role of artificial intelligence (AI)-based systems in the patient educa-tion process.

methodsThe ten most frequently asked questions regarding trigger finger were compiled from patient education websites and a literature review, then posed to ChatGPT. Two orthopedic specialists evaluated the responses using the Journal of the American Medical Association (JAMA) Benchmark criteria and the DISCERN instrument (A Tool for Judging the Quality of Written Consumer Health Information on Treatment Choices). Additionally, the readability of the responses was assessed using the Flesch-Kincaid Grade Level.

resultsThe DISCERN scores for ChatGPT's responses to trigger finger questions ranged from 35 to 47, with an average of 42, indicating "moderate" quality. While 60% of the responses were satisfactory, 40% contained deficiencies. According to the JAMA Benchmark criteria, the absence of scientific references was a significant drawback. The average readability level corresponded to the university level, making the information difficult to understand for patients with low health literacy. Improvements are needed to enhance the accessibility and comprehensibility of the content for a broader patient population.

conclusionTo the best of our knowledge, this is the first study to investigate the use of ChatGPT in the context of trigger finger. While ChatGPT shows reasonable effectiveness in providing general information on trigger finger, expert oversight is necessary before it can be relied upon as a primary source for patient education.

Indexed as

Patient Education as TopicTrigger Finger DisorderArtificial IntelligenceComprehensionGenerative Artificial IntelligenceHumansReproducibility of ResultsSurveys and Questionnaires

Identifiers

PMID40211643
PMCPMC12000978

What OpenQuestion holds

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LicenceCC BY-NC
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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.