Evidence map›Paper›PMID 40941466›Full record

ArticleHealthcare (Basel, Switzerland)2025

Evaluating the Competence of AI Chatbots in Answering Patient-Oriented Frequently Asked Questions on Orthognathic Surgery.

Ezgi Yüceer-Çetiner, Dilara Kazan, Mobin Nesiri, Selçuk Basa

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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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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

3 citing papers 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

4 authors.

Ezgi Yüceer-ÇetinerDepartment of Oral and Maxillofacial Surgery, School of Dental Medicine, Bahçeşehir University, Istanbul 34357, Turkey.ORCID 0000-0003-4393-9440
Dilara KazanDepartment of Oral and Maxillofacial Surgery, School of Dental Medicine, Bahçeşehir University, Istanbul 34357, Turkey.ORCID 0000-0002-7471-8758
Mobin NesiriDepartment of Oral and Dental Health, Vocational School of Health Services, Bahçeşehir University, Istanbul 34353, Turkey.ORCID 0009-0000-8517-8999
Selçuk BasaDepartment of Oral and Maxillofacial Surgery, School of Dental Medicine, Bahçeşehir University, Istanbul 34357, Turkey.ORCID 0000-0002-9135-1011

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to evaluate the performance of three widely used artificial intelligence (AI) chatbots-ChatGPT-4, Gemini 2.5 Pro, and Claude Sonnet 4-in answering patient-oriented frequently asked questions (FAQs) related to orthognathic surgery. Given the increasing reliance on AI tools in healthcare, it is essential to evaluate their performance to provide accurate, empathetic, readable, and clinically appropriate information.

methodsTwenty FAQs in Turkish about orthognathic surgery were presented to each chatbot. The responses were evaluated by three oral and maxillofacial surgeons using a modified Global Quality Score (GQS), binary clinical appropriateness judgment, and a five-point empathy rating scale. The evaluation process was conducted in a double-blind manner. The Ateşman Readability Formula was applied to each response using an automated Python-based script. Comparative statistical analyses-including ANOVA, Kruskal-Wallis, and post hoc tests-were used to determine significant differences in performance among chatbots.

resultsGemini outperformed both GPT-4 and Claude in GQS, empathy, and clinical appropriateness (

conclusionsAI chatbots vary significantly in their ability to support surgical patient education. While GPT-4 offers superior readability, Gemini provides the most balanced and clinically reliable responses. These findings underscore the importance of context-specific chatbot selection and continuous clinical oversight to ensure safe and ethical AI-driven communication.

Indexed as

artificial intelligenceclinical safetyhealth communicationorthognathic surgerypatient education

Identifiers

PMID40941466
PMCPMC12428093

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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.