Evidence map›Paper›PMID 41339722›Full record

ArticleScientific reports2025

Evaluation of ChatGPT-4o and DeepSeek as tools for orthodontic health literacy in public dental education.

Zhaoxiang Wen, Jiaxin Huang, Keer Yu, Yaqi Li, Zhenhui Wang, Xiaozhu Liao, Biao Li, Zhendong Tao, Hong He

Abstract read
In one paragraph

Article in Scientific reports, 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

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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Zhaoxiang WenState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Jiaxin HuangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Keer YuState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Yaqi LiState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Zhenhui WangState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Xiaozhu LiaoState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Biao LiState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Zhendong TaoState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.
Hong HeState Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China. drhehong@whu.edu.cn.

Funding

National Natural Science Foundation of China 82271011
6 · The paper itself

Abstract

This study aims to compare and evaluate the accuracy, consistency, and response behavior of ChatGPT-4o and DeepSeek in orthodontic health literacy tasks. A total of 50 multiple-choice, text-based questions covering five orthodontic domains were developed using the Delphi method by a panel of five experienced orthodontic professionals. Each question was asked to both models three times daily (morning, noon, evening) over three days, in both English and Chinese versions. Accuracy, consistency, and response time were analyzed using SPSS and R software. The overall accuracy of ChatGPT-4o (90.4%) was slightly higher than that of DeepSeek (88.0%), though the difference was not statistically significant in either English (p = 1.000) or Chinese (p = 0.263). Across individual question groups, no significant differences in accuracy were found between models (p > 0.05). The time of day and testing day had no effect on model performance (p > 0.05 for all comparisons). Both models demonstrated similar consistency in their responses (p = 1.000 for English; p = 0.412 for Chinese). However, ChatGPT-4o showed significantly faster response times than DeepSeek in both languages (p < 0.01). Both ChatGPT-4o and DeepSeek demonstrate comparable accuracy and consistency in orthodontic health literacy tasks. However, ChatGPT-4o's significantly faster response time makes it more suitable for clinical applications requiring efficient information delivery.

Indexed as

Education, DentalHealth LiteracyOrthodonticsFemaleGenerative Artificial IntelligenceHumansMaleSurveys and QuestionnairesArtificial intelligence (AI)ChatGPTDeepSeekDelphi methodHealth literacyOrthodontics

Identifiers

PMID41339722
PMCPMC12774924

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.