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| ID | Type | Description | Link |
|---|---|---|---|
| 3P50MD017344-03S3 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institute on Minority Health and Health Disparities (NIMHD) | NIH |
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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 (T2D).
The primary objective of this new project is to enhance glycemic control in individuals with prediabetes and deter the progression to Type 2 Diabetes (T2D) within the Los Angeles (LA) County community. Our proposal involves conducting a Phase 0 intervention development study. This study will enlist a final sample of N=50 adults who speak English and/or Spanish, have non-clinical prediabetes, and test positive for prediabetes via a finger-prick A1c% screening. Participants will wear CGM devices for 20 days, with glucose data masked for the first 10 days and unmasked for the next 10 days. During the unmasked phase, participants will receive daily health education videos on their smartphones. The study will compare the duration of glucose excursions between the masked and unmasked phases to assess the impact of CGM feedback and health education on glucose regulation.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Single Group: CGM with Masked Phase A and Unmasked Phase B | 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. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 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. |
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| Measure | Description | Time Frame |
|---|---|---|
| Glucose levels | Mean glucose in mg/dL | Maximum of 20 days of continuous wear |
| Measure | Description | Time Frame |
|---|---|---|
| Time out of range > 140 mg/dL (TOR) | Time out of range > 140 mg/dL (TOR) | Maximum of 20 days of continuous wear |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| David S Black, PhD MPH | Contact | 3234428223 | davidbla@usc.edu | |
| Ruth Flores | Contact | rflores8@usc.edu |
| Name | Affiliation | Role |
|---|---|---|
| David S Black, PhD MPH | University of Southern California Keck School of Medicine | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Southern California Center for Latino Health (SCCLH) | Recruiting | Los Angeles | California | 90031 | United States |
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| Label | URL |
|---|---|
| Dexcom G CGM system specifications | View source |
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IPD sharing is set up with affiliate USC-Children's Hospital Los Angeles (CHLA) P50 Center universities and hospitals under a registered data use agreement (DUA). Data and protocol documentation will be posted on the Open Science Framework
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.
Publicly available link or by request to PI or directly obtained as supplemental material from the website of the journal publication.
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| ID | Term |
|---|---|
| D011236 | Prediabetic State |
| D006266 | Health Education |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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Phase A / Phase B (AB) sequential condition design with CGM automated continuous glucose recording with glucose level masked and unmasked phases.
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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.
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| D004700 | Endocrine System Diseases |
| D000099060 | Adherence Interventions |
| D055118 | Medication Adherence |
| D010349 | Patient Compliance |
| D010342 | Patient Acceptance of Health Care |
| D000074822 | Treatment Adherence and Compliance |
| D015438 | Health Behavior |
| D001519 | Behavior |