Is ChatGPT an Effective Tool for Providing Dietary Advice?
ChatGPT
dietary advice
guidelines
non-communicable diseases (NCDs)
Journal
Nutrients
ISSN: 2072-6643
Titre abrégé: Nutrients
Pays: Switzerland
ID NLM: 101521595
Informations de publication
Date de publication:
06 Feb 2024
06 Feb 2024
Historique:
received:
08
01
2024
revised:
30
01
2024
accepted:
03
02
2024
medline:
24
2
2024
pubmed:
24
2
2024
entrez:
24
2
2024
Statut:
epublish
Résumé
The chatbot Chat Generative Pretrained Transformer (ChatGPT) is becoming increasingly popular among patients for searching health-related information. Prior studies have raised concerns regarding accuracy in offering nutritional advice. We investigated in November 2023 ChatGPT's potential as a tool for providing nutritional guidance in relation to different non-communicable diseases (NCDs). First, the dietary advice given by ChatGPT (version 3.5) for various NCDs was compared with guidelines; then, the chatbot's capacity to manage a complex case with several diseases was investigated. A panel of nutrition experts assessed ChatGPT's responses. Overall, ChatGPT offered clear advice, with appropriateness of responses ranging from 55.5% (sarcopenia) to 73.3% (NAFLD). Only two recommendations (one for obesity, one for non-alcoholic-fatty-liver disease) contradicted guidelines. A single suggestion for T2DM was found to be "unsupported", while many recommendations for various NCDs were deemed to be "not fully matched" to the guidelines despite not directly contradicting them. However, when the chatbot handled overlapping conditions, limitations emerged, resulting in some contradictory or inappropriate advice. In conclusion, although ChatGPT exhibited a reasonable accuracy in providing general dietary advice for NCDs, its efficacy decreased in complex situations necessitating customized strategies; therefore, the chatbot is currently unable to replace a healthcare professional's consultation.
Identifiants
pubmed: 38398794
pii: nu16040469
doi: 10.3390/nu16040469
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM