ChatGPT and human dietitian responses to diet-related questions on an online Q&A platform: A comparative study - Seul Ki Choi; Yunseo Moon; Hyunggu Jung (Digital Health)
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.