Next Article in Journal
Advancing Diabetic Foot Ulcer Care: AI and Generative AI Approaches for Classification, Prediction, Segmentation, and Detection
Previous Article in Journal
Patient Perspectives on Healthcare Utilization During the COVID-19 Pandemic in People with Multiple Sclerosis—A Longitudinal Analysis
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

ChatGPT-4o and 4o1 Preview as Dietary Support Tools in a Real-World Medicated Obesity Program: A Prospective Comparative Analysis

1
Faculty of Arts and Social Sciences, University of Sydney, Sydney, NSW 2050, Australia
2
Dietitians Australia, Phillip, ACT 2606, Australia
3
Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
4
Eucalyptus, Sydney, NSW 2000, Australia
5
Hospital Medicine Division, Department of Medicine, Stanford University, Stanford, CA 94305, USA
*
Author to whom correspondence should be addressed.
Healthcare 2025, 13(6), 647; https://doi.org/10.3390/healthcare13060647
Submission received: 13 February 2025 / Revised: 13 March 2025 / Accepted: 14 March 2025 / Published: 16 March 2025

Abstract

Background/Objectives: Clinicians are becoming increasingly interested in the use of large language models (LLMs) in obesity services. While most experts agree that LLM integration would increase access to obesity care and its efficiency, many remain skeptical of their scientific accuracy and capacity to convey human empathy. Recent studies have shown that ChatGPT-3 models are capable of emulating human dietitian responses to a range of basic dietary questions. Methods: This study compared responses of two ChatGPT-4o models to those from human dietitians across 10 complex questions (5 broad; 5 narrow) derived from patient–clinician interactions within a real-world medicated digital weight loss service. Results: Investigators found that neither ChatGPT-4o nor Chat GPT-4o1 preview were statistically outperformed (p < 0.05) by human dietitians on any of the study’s 10 questions. The same finding was made when scores were aggregated from the ten questions across the following four individual study criteria: scientific correctness, comprehensibility, empathy/relatability, and actionability. Conclusions: These results provide preliminary evidence that advanced LLMs may be able to play a significant supporting role in medicated obesity services. Research in other obesity contexts is needed before any stronger conclusions are made about LLM lifestyle coaching and whether such initiatives increase care access.
Keywords: ChatGPT-4o; dietetics; health coaching; digital weight loss services; weight loss medications ChatGPT-4o; dietetics; health coaching; digital weight loss services; weight loss medications

Share and Cite

MDPI and ACS Style

Talay, L.; Lagesen, L.; Yip, A.; Vickers, M.; Ahuja, N. ChatGPT-4o and 4o1 Preview as Dietary Support Tools in a Real-World Medicated Obesity Program: A Prospective Comparative Analysis. Healthcare 2025, 13, 647. https://doi.org/10.3390/healthcare13060647

AMA Style

Talay L, Lagesen L, Yip A, Vickers M, Ahuja N. ChatGPT-4o and 4o1 Preview as Dietary Support Tools in a Real-World Medicated Obesity Program: A Prospective Comparative Analysis. Healthcare. 2025; 13(6):647. https://doi.org/10.3390/healthcare13060647

Chicago/Turabian Style

Talay, Louis, Leif Lagesen, Adela Yip, Matt Vickers, and Neera Ahuja. 2025. "ChatGPT-4o and 4o1 Preview as Dietary Support Tools in a Real-World Medicated Obesity Program: A Prospective Comparative Analysis" Healthcare 13, no. 6: 647. https://doi.org/10.3390/healthcare13060647

APA Style

Talay, L., Lagesen, L., Yip, A., Vickers, M., & Ahuja, N. (2025). ChatGPT-4o and 4o1 Preview as Dietary Support Tools in a Real-World Medicated Obesity Program: A Prospective Comparative Analysis. Healthcare, 13(6), 647. https://doi.org/10.3390/healthcare13060647

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop