Do AI Chatbots Tell the Truth About Dentin Hypersensitivity? A Comparative Evaluation of Quality, Accuracy, and Readability

Aim:Dentin hypersensitivity (DH) is a common dental complaint, and many patients now seek information from AI chatbots. Yet, the accuracy, reliability, and readability of chatbot-generated DH content remain uncertain.Materials and Methods:A consensus-based DH question set was presented to three AI chatbots (ChatGPT-4o, DeepSeek, Copilot) in independent, standardized sessions. Three blinded periodontologists evaluated the responses using CLEAR, mGQS, accuracy scores, DISCERN, and readability metrics (FRE, FKGL). Non-parametric tests compared inter-model differences.Results:Significant differences were found in FKGL (p=0.025), DISCERN (p=0.004), and response length (p

Authors

Institutions

Publication Details

Journal
Cumhuriyet Dental Journal
Published
2026-03-27
DOI
https://doi.org/10.7126/cumudj.1848545
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Do AI Chatbots Tell the Truth About Dentin Hypersensitivity? A Comparative Evaluation of Quality, Accuracy, and Readability

Seval Ceylan Şen, Özlem Saraç Atagün, Rumeysa Nur Kayacı, Zeynep Hazan Yildiz et al.
Cumhuriyet Dental Journal
Artificial Intelligence in Healthcare and Education
article

Do AI Chatbots Tell the Truth About Dentin Hypersensitivity? A Comparative Evaluation of Quality, Accuracy, and Readability

Seval Ceylan Şen, Özlem Saraç Atagün, Rumeysa Nur Kayacı, Zeynep Hazan Yildiz, Gülbahar Ustaoğlu
article en

Abstract

Aim:Dentin hypersensitivity (DH) is a common dental complaint, and many patients now seek information from AI chatbots. Yet, the accuracy, reliability, and readability of chatbot-generated DH content remain uncertain.Materials and Methods:A consensus-based DH question set was presented to three AI chatbots (ChatGPT-4o, DeepSeek, Copilot) in independent, standardized sessions. Three blinded periodontologists evaluated the responses using CLEAR, mGQS, accuracy scores, DISCERN, and readability metrics (FRE, FKGL). Non-parametric tests compared inter-model differences.Results:Significant differences were found in FKGL (p=0.025), DISCERN (p=0.004), and response length (p

Cumhuriyet Dental JournalVol. 29(1)
Sağlık Bilimleri Üniversitesi (TR), University of Health Sciences (SO)
Quality Education
Openalex Percentile: Top 6%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.