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Improving Weight Loss in Healthy Adults With Overweight and Obesity: An Artificial Intelligence-assisted Dietary Prediction and Prevention System With Continuous Glucose Monitoring
Sponsor: National University Health System, Singapore
Summary
This study aims to examine the effectiveness of a novel dietary lapse prediction and prevention self-regulation app called the eating behaviour trigger-response inhibition program (eTRIP), and the addition of continuous glucose monitoring (CGM), on healthy eating and weight loss in people with overweight and obesity.
Key Details
Gender
All
Age Range
21 Years - 65 Years
Study Type
INTERVENTIONAL
Enrollment
300
Start Date
2025-01-22
Completion Date
2026-07
Last Updated
2026-02-09
Healthy Volunteers
No
Interventions
eTRIP
Intervention group 1 involves using the eating behaviour trigger-response inhibition program(eTRIP) smartphone application for 10 weeks, where participants will need to take pictures of their food items as part of their food logging and may also engage with app-based activities to build self-regulatory skills in sticking to their weight loss plans. Additionally, participants will also apply a continuous glucose monitoring (CGM) sensor on their arm and taught how to scan the CGM sensor so that they can monitor their glucose levels for the first 10 days.
FatSecret
Intervention group 2 involves using the FatSecret smartphone application for participants to monitor their calorie intake, without any continuous glucose monitoring.
Locations (1)
National University of Singapore
Singapore, Singapore