ArticleThe Angle orthodontist2025
Can AI chatbots accurately provide information on orthodontic risks?
Article in The Angle orthodontist, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Patient-Facing AI Chatbot Treatment-Direction Advice in Orthodontic Health Communication: A Scenario-Based Comparison with Expert Consensus.Healthcare (Basel, Switzerland) · 2026Article
- Patient Facing AI Chatbots in Digital Orthodontic Education: A Comparative Evaluation of Understandability, Actionability, Quality, and Safety of Dietary Advice.Healthcare (Basel, Switzerland) · 2026Article
- Prompt sensitivity of large language models in orthodontic patient counseling: a scenario-based experimental study.BMC oral health · 2026Article
- Evaluating large language models for orthodontic consultation in patients with periodontitis: a study of reliability, quality, and readability.BMC oral health · 2026Article
- Generative Artificial Intelligence-driven orthodontic education practices.BMC medical education · 2026Review
- Exploring LLM-based chatbot effectiveness in answering questions related to the risks and benefits of orthognathic treatment: a cross-sectional study.European journal of orthodontics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: To evaluate and compare the validity and reliability of different artificial intelligence (AI) chatbots in answering queries about potential orthodontic risks. Materials and Methods: Answers to 20 frequently asked questions about the potential risks of orthodontics were derived from daily consultations with experienced orthodontists and AI chatbots (ChatGPT 4o, Claude 3.5 Sonnet, and Gemini 1.5 Pro). The questions were repeated three times and submitted to the AI chatbots to assess the reliability of their answers. The answers from AI chatbots were scored using a modified Global Quality Scale (GQS). Low- and high-threshold validity tests were used to determine validity, and Cronbach's alpha was used to evaluate the consistency of the three responses to each of the 20 questions. Results: In the low-threshold validity test, Gemini exhibited the highest overall performance. In the high-threshold validity test, Gemini also showed the highest overall effectiveness, but there was no significant difference observed among the three chatbots. All three chatbots demonstrated satisfactory levels of reliability, with Gemini having the highest consistency. Conclusions: AI chatbots have some potential in providing orthodontic risk information, but they must be used cautiously and further optimized to improve their effectiveness in clinical practice.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.