Comparison Between the Health Effects of an AI-driven Model With Those of Human Professional Guidelines for the Treatment of Obesity
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 21
研究概览
简要总结
Many non-communicable diseases are diet-related and have a significant impact on public health. It is stated that global dietary shifts are needed to change disease patterns, highlighting the importance of nutrition in addressing public health issues, such as obesity. The field of nutrition has been dependent on clinical and observational studies; however, the emergence of Artificial Intelligence (AI) is transforming these approaches.
ChatGPT may be used to provide dietary recommendations due to its high speed, extensive access to a variety of meal data, and low complexity. However, initial evaluations have shown that ChatGPT may be inaccurate in terms of safety and reliability, and traditional nutrition approaches are highly reliant on experts' knowledge and the validity of nutritional guidelines. It has been suggested that AI in nutrition may be beneficial; however, further investigations are needed. Our proposal aims to fill the represented critical evidence gaps.
The study aims to compare the health effects of an AI-driven model with those of human professional guidelines for the treatment of obesity. Furthermore, investigators seek better strategies to utilize AI, if appropriate, for weight loss and other health benefits.
详细描述
An 8-week parallel-randomized clinical trial will be conducted. Participants will be recruited through printed flyers posted at approved locations, including Texas Tech University campus buildings and community centers in Lubbock, Texas. In addition to physical flyers, recruitment may include unpaid postings on social media platforms. No paid or targeted advertisements will be used. Flyers will include a QR code directing interested individuals an online survey. Based on their completed survey, they will be screened according to inclusion and exclusion criteria. If they meet the criteria, they will be invited for the baseline visit. Eligible participants will be asked to come fast for 8 hours to the Nutrition and Metabolic Health Initiative (NMHI). Upon arrival, the written consent form will be provided, and they will be enrolled in the study. They will be randomly allocated into one of the three groups in a 1:1:1 ratio. The REDCap will be used for electronic data capture for randomization and data management.
The experimental groups will include:
- An AI-only group using ChatGPT Premium.
- A dietitian-led group (human), in which dietary plans are developed by a licensed dietitian using standard professional resources and clinical judgment, without the use of generative AI tools.
- An AI-assisted dietitian group (combination), in which the same dietitian is permitted to use ChatGPT Premium as a supportive tool during the consultation.
This design reflects real-world clinical practice, where dietitians commonly use professional judgment and non-AI resources.
After allocation, blood pressure will be measured. Resting metabolic rate, fasting blood glucose, lipid profile, and HbA1 will be recorded. Participants will be blinded to their group assignment; however, the study will be unable to blind the personnel due to the nature of the study. Additionally, the participants will be asked to complete the short form of the International Physical Activity Questionnaire (IPAQ).
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Treatment
- 盲法
- Single (Participant)
入排标准
- 年龄范围
- 18 Years 至 60 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Participants with age 18 to 60 years,
- •Living in Lubbock-TX
- •Willing to participate in the study
排除标准
- •Pregnant women
- •Breastfeeding women
- •Recent diagnosis of a severe/acute medical condition within 6 months
- •Any other chronic diseases except obesity (e.g., diabetes, chronic kidney diseases, psychiatric conditions, cancer, acute pancreatitis)
- •Taking any anti-obesity medications