Continuous Glucose Monitoring for Prediabetes
(G2 Trial)

Recruiting in Palo Alto (17 mi)

Overseen byDavid S Black, PhD MPH

Age: 18+

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Recruiting

Sponsor: David S Black, PhD

No Placebo Group

Trial Summary

What is the purpose of this trial?The objective of this project is to deliver a behavior health education video series that combines wearable continuous glucose monitoring (CGM) with smartphone feedback and video clips generated by artificial intelligence (AI) software to improve glycemic control among individuals with prediabetes. The goal is to prevent transition to type 2 diabetes and advanced metabolic complications.

Eligibility Criteria

This trial is for individuals with prediabetes, as indicated by a finger prick A1c% test. Participants must be willing to wear a continuous glucose monitoring (CGM) sensor and have a compatible smartphone device. Pregnant individuals or those with disorders affecting blood glucose levels or significant medical conditions that could impact participation are excluded.

Inclusion Criteria

Pre-diabetes determined by finger prick A1c%

Community health worker

I am willing to wear a continuous glucose monitor (CGM) sensor.

Exclusion Criteria

Influential medical disorder or event affecting ability to participate in the study

Incompatible smartphone device not pairing with the Dexcom CGM system

Currently pregnant

+1 more

Trial Timeline

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Masked CGM Phase

Participants wear continuous glucose monitoring devices with data masked for 10 days

10 days

1 visit (in-person) for device setup

Unmasked CGM Phase

Participants wear continuous glucose monitoring devices with data unmasked and receive daily health education videos

10 days

Daily virtual interactions via smartphone

Follow-up

Participants are monitored for safety and effectiveness after the CGM phases

2 weeks

Participant Groups

The study tests the effectiveness of health education videos combined with wearable CGM feedback in improving glycemic control among prediabetic individuals. The aim is to use AI-generated video content to help prevent the onset of type 2 diabetes and related metabolic complications.