Diabetes Prevention Combining CGM and Artificial Intelligence Health Education
Overview
- Phase
- N/A
- Intervention
- The continuous glucose monitoring system
- Conditions
- Pre-diabetes
- Sponsor
- University of Southern California
- Enrollment
- 23
- Locations
- 1
- Primary Endpoint
- Change in Mean Glucose (mg/dL) From Baseline
- Status
- Completed
- Last Updated
- 3 months ago
Overview
Brief Summary
The objective of this project is to develop a behavioral intervention that combines wearable continuous glucose monitoring (CGM) with smartphone feedback and educational video clips generated by artificial intelligence (AI) software to improve glycemic control among individuals with pre-diabetes. The goal is to prevent transition to type 2 diabetes.
Detailed Description
Video narratives will be provided by Latino community health workers, known as Promotores de Salud (PdS), who will wear and experience the continuous glucose monitoring (CGM) system and its glycemic variability feedback. Study 1 (G1) is a Phase 0 intervention development study, enrolling a sample of 20 Spanish- and/or English-speaking PdS who test positive for pre-diabetes via a finger prick screening. Participants will wear CGM devices for 20 days, during which they will record daily narratives about their experiences with the CGM feedback and their glucose variability. Structured interviews between staff and participants will explore the benefits and barriers of CGM use. These recorded video clips will serve as the foundation for educational cinematic smartphone videos for future interventions. Artificial intelligence (AI) tools will be used to translate the text, audio, and video clips into various languages for broad dissemination. Blood glucose levels in mg/dL will be recorded continuously over the wear period.
Investigators
David S Black, PhD
Associate Professor of Population and Public Health Sciences
University of Southern California
Eligibility Criteria
Inclusion Criteria
- •Prediabetes by finger prick blood A1C%
- •Centers for Disease Control and Prevention (CDC) prediabetes risk test score of 5 or higher
- •Willingness to wear CGM sensor
- •Latino community health worker
Exclusion Criteria
- •Currently pregnant
- •Less than 18 years of age, which is adult in California
- •Diagnosed with any disorder that interferes with glucose
- •Influential medical disorder/event affecting ability to participate in study
- •Incompatible smartphone device not pairing with Dexcom G6 app
Arms & Interventions
Unmasked CGM feedback
The CGM system is used by the participant according to manufacturer instructions for the condition interval in their normal living environment.
Intervention: The continuous glucose monitoring system
Outcomes
Primary Outcomes
Change in Mean Glucose (mg/dL) From Baseline
Time Frame: Up to 20 days of continuous CGM wear, comprising two sequential 10-day assessment periods (baseline Phase A and subsequent Phase B).
Mean glucose was derived from continuous glucose monitoring (CGM) data obtained from the Dexcom Clarity system. Raw glucose values were processed and analyzed using the R statistical software package iglu to generate the full CGM variability metrics panel. For each participant, mean glucose was calculated separately for each 10-day assessment period. The outcome measure represents the change in mean glucose, defined as the difference between the baseline (Phase A) 10-day assessment period and the subsequent (Phase B) 10-day assessment period.