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Comparison Between the Health Effects of an AI-driven Model With Those of Human Professional Guidelines for the Treatment of Obesity

2026년 5월 1일 업데이트: Texas Tech University

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.

연구 개요

상세 설명

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).

The AI group participants will be in touch only with a trained study staff member (operator) who will facilitate communication with ChatGPT Premium so that the participants cannot see the operator's screen. The operator will not be a licensed dietitian or healthcare provider and will not provide any independent dietary advice. The operator will receive standardized training prior to study initiation to ensure consistency across participants.

The results of the BIA and finger prick tests will be given to the AI and asked to provide a dietary meal plan based on a standard prompt.

The human group participants will sit in the same room, but instead of the operator, they will have 60-minute consultations with the dietitian. The results of baseline assessments would be provided; however, the dietitian does not have any AI access.

Participants in the combination group will sit in the same room and be consulted for 60 minutes by the same dietitian as the human group. However, in this group, the dietitian has access to ChatGPT premium and can use it.

After 8 weeks, all participants will be asked to attend the clinic for their final visit and glycemic index, lipid profile, HbA1c, and body composition will be measured. In addition, the participants will be asked about their self-report compliance assessment.

연구 유형

중재적

등록 (추정된)

21

단계

  • 해당 없음

연락처 및 위치

이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.

연구 연락처

연구 연락처 백업

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

  • 성인

건강한 자원 봉사자를 받아들입니다

설명

Inclusion Criteria:

  • Participants with age 18 to 60 years,
  • BMI>30
  • Living in Lubbock-TX
  • Willing to participate in the study

Exclusion Criteria:

  • 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

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

  • 주 목적: 치료
  • 할당: 무작위
  • 중재 모델: 병렬 할당
  • 마스킹: 하나의

무기와 개입

참가자 그룹 / 팔
개입 / 치료
실험적: AI-only group using ChatGPT Premium
A human assisted AI (ChatGPT Premium), in which dietary plans are developed and clinical judgment will be made.
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.
실험적: A dietitian-led group (human)
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.
활성 비교기: AI-assisted dietitian group (combination)
An AI-assisted dietitian group (combination), in which the same dietitian is permitted to use ChatGPT Premium as a supportive tool during the consultation
Arm Description: A human assisted AI (ChatGPT Premium), in which dietary plans are developed and clinical judgment will be made.

연구는 무엇을 측정합니까?

주요 결과 측정

결과 측정
기간
Rate of weight change, Fat %, Muscle Mass, and BMI
기간: 8 weeks
8 weeks

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작 (추정된)

2026년 5월 15일

기본 완료 (추정된)

2026년 9월 30일

연구 완료 (추정된)

2026년 12월 31일

연구 등록 날짜

최초 제출

2026년 4월 23일

QC 기준을 충족하는 최초 제출

2026년 4월 23일

처음 게시됨 (실제)

2026년 4월 30일

연구 기록 업데이트

마지막 업데이트 게시됨 (실제)

2026년 5월 7일

QC 기준을 충족하는 마지막 업데이트 제출

2026년 5월 1일

마지막으로 확인됨

2026년 5월 1일

추가 정보

이 연구와 관련된 용어

개별 참가자 데이터(IPD) 계획

개별 참가자 데이터(IPD)를 공유할 계획입니까?

아니요

약물 및 장치 정보, 연구 문서

미국 FDA 규제 의약품 연구

아니

미국 FDA 규제 기기 제품 연구

아니

이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .

Obesity (BMI>30)에 대한 임상 시험

AI-assisted dietitian group (combination)에 대한 임상 시험

구독하다