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How Easily Can AI Chatbots Spread Misinformation in Audiology and Otolaryngology?
Article in OTO open. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Reference Accuracy in Large Language Model Chatbots: A Metric for Inherent Misinformation?Medical science monitor : international medical journal of experimental and clinical research · 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
Objective: Chatbots powered by large language models (LLMs) have recently emerged as prominent sources of information. However, their ability to propagate misinformation as well as information, particularly in specialized fields like audiology and otolaryngology, remains underexplored. This study aimed to evaluate the accuracy of 6 popular chatbots-ChatGPT, Gemini, Claude, DeepSeek, Grok, and Mistral-in response to questions framed around a range of unproven methods in audiological and otolaryngological care. Study Design: Cross-sectional study. Setting: A set of 50 questions was developed based on common conversations between patients and clinicians. We then posed these questions to the chatbots. Methods: We tested each chatbot 10 times to account for variable responses, producing a total of 3000 responses. The responses were compared with correct answers based on the general opinion of 11 professionals. The consistency of the responses was evaluated by Cohen's Kappa. Results: Most chatbot responses to the majority of questions were deemed accurate. Grok consistently performed best, where its answers aligned perfectly with the opinions of the experts. Deepseek exhibited the lowest accuracy, scoring 95.8%. Mistral exhibited the lowest consistency, scoring 0.96. Conclusions: Although all the chatbots generally avoided endorsing unproven methods, some responses deviated from the expert consensus and could therefore be said to contribute to the spread of misinformation. The best performer among the group was Grok, which provided consistently accurate responses, showing it has the potential for clinical and educational use within audiology and otolaryngology.
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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.