Diabetes Prevention Combining CGM and Artificial Intelligence Health Education
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 23
- 试验地点
- 1
- 主要终点
- Change in Mean Glucose (mg/dL) From Baseline
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Prevention
- 盲法
- None
盲法说明
The CGM system feedback is unmasked. The CGM is automatically recorded and does not require an outcomes assessor.
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •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
排除标准
- •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
研究组 & 干预措施
Unmasked CGM feedback
The CGM system is used by the participant according to manufacturer instructions for the condition interval in their normal living environment.
干预措施: The continuous glucose monitoring system (Device)
结局指标
主要结局
Change in Mean Glucose (mg/dL) From Baseline
时间窗: 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.
次要结局
未报告次要终点
研究者
David S Black, PhD
Associate Professor of Population and Public Health Sciences
University of Southern California