Continuous Glucose Monitoring in Prediabetes With Health Education Videos Among Community Health Workers

NCT06883812 | Completed DMC FDA Device

• 2 other identifiers: UP-23-01001(a)3P50MD017344-03S3
• Study Type: interventional
• Target: 30
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Prediabetes

Keywords

Prediabetes; Glucose control; Feedback; Health education; Artificial intelligence; Behavioral analysis

Outcome Measures

Primary Outcomes (1)

• Glucose levels

  Mean glucose in mg/dL

  Maximum of 20 days of continuous wear

Secondary Outcomes (1)

• Time out of range > 140 mg/dL (TOR)

  Maximum of 20 days of continuous wear

Study Arms (1)

Single Group

OTHER

Participants wear a CGM on the back of the arm. During Phase A, glucose values are not visible to participants. During Phase B, glucose values are visible via the phone app.

Device: CGM

Interventions

CGM DEVICE

The CGM sensor is worn on the back of the arm and glucose levels are recorded continuously but levels are not shown on the participant's phone app in phase A.

Single Group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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
• Community health worker

You may not qualify if:

• 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

Sponsors & Collaborators

• David S Black, PhD: lead
• National Institute on Minority Health and Health Disparities (NIMHD): collaborator

Study Sites (1)

Southern California Center for Latino Health SCCLH

Los Angeles, California, 90031, United States

Location

Related Links

• Dexcom G CGM system specifications

MeSH Terms

Conditions

Prediabetic State; Health Education

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Adherence Interventions; Medication Adherence; Patient Compliance; Patient Acceptance of Health Care; Treatment Adherence and Compliance; Health Behavior; Behavior

Study Officials

• David S Black, PhD MPH

  University of Southern California Keck School of Medicine

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Masking Details: Participants are blinded to glucose values during Phase A. The CGM system generates automated records of glucose and does not require observation from an outcomes assessor. The investigator does not engage with participants and becomes aware of unmasking after trial is completed.
• Purpose: PREVENTION
• Intervention Model: SEQUENTIAL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Tenured Associate Professor of Population and Public Health Sciences

Model Details: An AB sequential condition design with CGM automated continuous glucose recording with glucose level masked and unmasked phases.

Study Record Dates

• First Submitted: March 12, 2025
• First Posted: March 19, 2025
• Study Start: March 5, 2025
• Primary Completion: November 3, 2025
• Study Completion: November 3, 2025
• Last Updated: March 30, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ANALYTIC CODE
• Time Frame: No longer than one year after the completion of the trial. Researchers can obtain de-identified data and statistical codes after publication of the study outcomes by email request and as supplemental material in future journal publications.
• Access Criteria: Publicly available link or by request to PI or directly obtained as supplemental material from the website of the journal publication.

Locations

US (1)