ArticleDigital health
ChatGPT and human dietitian responses to diet-related questions on an online Q&A platform: A comparative study.
Article in Digital health. 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.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: ChatGPT's potential as a diet information tool is emerging. However, little is known about the extent to which the information provided by ChatGPT aligns with that provided by dietitians. Objective: This study aimed to assess ChatGPT's capacity to provide responses to diet-related questions, compared to responses by dietitians. Methods: A total of 928 diet-related questions and corresponding responses from dietitians were collected from Naver Knowledge-iN, a Korean online Q&A platform, between January 18, 2023, and January 17, 2024. ChatGPT-4o was used to generate responses to the same questions. Five text similarity indices-Dice Coefficient, Jaccard Index, Overlap Coefficient, Cosine Similarity, and Term Frequency-Inverse Document Frequency-were used to assess the similarity between ChatGPT's and dietitians' responses. Questions with the top 5% response similarity were reviewed to identify characteristics of the questions for which ChatGPT generated responses similar to those of dietitians. Responses with the bottom 5% similarity were reviewed to identify reasons for the low similarity. Results: The average similarity coefficient between ChatGPT and dietitian responses was 0.42. Questions with high response similarity tended to include detailed information, such as specific food items or portions (76.1%), the questioner's context (69.6%), or personal characteristics (17.4%). Low response similarity was mainly due to ChatGPT providing significantly longer responses than dietitians. Conclusions: ChatGPT demonstrated content similarity to dietitian responses, but they were not identical. The development of prompt engineering techniques to enhance ChatGPT's ability to provide more expert-like and personalized information could benefit users seeking dietary information.
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Registered trials
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