Engagement with an AI- and CGM-Integrated Digital Health Platform Is Associated with Clinically Significant Weight...

Area of Science:

• Obesity research
• Digital health interventions
• Metabolic disease management

Background:

• Obesity is a widespread health issue in the U.S., strongly linked to cardiometabolic diseases.
• The Signos app integrates artificial intelligence (AI) with continuous glucose monitoring (CGM) to provide personalized behavioral recommendations.
• This study investigates the association between user engagement with the Signos app and weight loss outcomes.

Purpose of the Study:

• To determine if user engagement with the Signos app is associated with weight loss in adults with obesity.
• To compare weight loss during periods of high and low engagement with the Signos system.
• To evaluate the relationship between engagement levels and total body weight loss over a 180-day period.

Main Methods:

• Adults (≥18 years) with a BMI ≥ 30 kg/m² and without diabetes were included.
• Engagement was measured by total meaningful actions per day (TMAPD).
• Longitudinal and cross-sectional analyses compared weight change based on TMAPD levels.

Main Results:

• Weight loss was significantly greater during engaged periods (1.17%/week) compared to non-engaged periods (0.44%/week).
• Higher engagement (TMAPD ≥ 1.02) was associated with greater 180-day total body weight loss (5.90%) versus lower engagement (4.38%).
• Weight loss outcomes were consistent regardless of early or late engagement with the platform.

Conclusions:

• Increased engagement with the Signos System is linked to greater weight loss in adults with obesity and without diabetes.
• AI-guided, CGM-informed behavioral interventions show potential for supporting clinically meaningful weight reduction.
• The findings support the utility of digital health platforms in managing obesity.