Precision Monitoring: Understanding Momentary Affect, Glucose, and Self-care Behaviors in Adolescents and Young Adults with type 1 diabetes

项目总结/摘要 1型糖尿病（T1 D）青少年和年轻人（AYA）的血红蛋白A1 c值最高， 在整个生命周期中。动态血糖监测（CGM）是一种现代血糖评估方法 提供关于葡萄糖水平的即时信息，以帮助优化范围内时间（[TIR] 70-180 mg/dL）。回顾性回顾动态血糖模式是改善糖尿病的重要组成部分 自我照顾然而，许多CGM用户被大量的CGM数据弄得不知所措，并且很少回顾或 下载CGM此外，CGM数据的解释不应在真空中进行，而应在 应该考虑影响自我护理的背景因素，以改善血糖调节。从而 为了最大限度地发挥CGM在患有T1 D的AYA患者中的临床价值，需要一种新的、基于生态学的方法， 将CGM数据与关于葡萄糖调节的个人内和个人间背景的信息结合起来， 发生。将生态瞬时评估（EMA）与CGM相结合以制定干预措施是及时的 计划，以改善自我护理，康复和心理社会的结果。我们会用严格的方法 情绪和社会体验的即时评级之间的动态关系（使用EMA）， CGM记录的葡萄糖值，这些值将集中显示在仪表板上， 动态血糖的情绪和社会背景（心理社会动态血糖[PAG]）。跟踪 在多成分干预中审查PAG模式，沿着持续的结构化支持， 将帮助患有T1 D的AYA更好地解释和行为响应超出范围的葡萄糖值， 作为一种催化剂，以改善A1 c，TIR和自我护理，以及减少糖尿病困扰。Amit Shapira博士， 提出了一系列的研究，其总体目标是开发、迭代改进和测试PAG T1 D患者的AYA干预。建议的3个具体目标是：1）确定方案咨询组的主要组成部分 使用EMA的仪表板，将协调与CGM相结合的情感和社会背景的显示 使用混合方法记录数据，以增强T1 D高于目标A1 c值的AYA的自我护理; 2） 通过专家反馈和指导，调整和构建仪表板，用于行为干预 从相关的利益相关者;和3）检查是否有一个试点随机对照试验的一个完善的PAG行为干预将 可接受的，可行的，令人满意的参与者，并有可能改善糖尿病和心理社会 与单独使用PAG相比的结果。这些研究的结果将为未来的全面RCT提供信息 R 01应用程序。Shapira博士的职业目标是成为一名独立的糖尿病行为研究人员 专注于优化自我护理，包括使用CGM和其他技术，以改善人们的结果 关于T1 D为期5年的职业发展计划将为她提供必要的糖尿病技能 护理（例如，糖尿病技术），先进的统计方法，以及可用性和定性研究， 开展糖尿病行为独立调查。

PROJECT SUMMARY/ABSTRACT Adolescents and Young Adults (AYA) with type 1 diabetes (T1D) have the highest hemoglobin A1c values of all across the lifespan. Continuous Glucose Monitoring (CGM) is a modern approach to glucose assessment that provides in-the-moment information about glucose levels to help optimize time-in-range ([TIR] 70-180 mg/dL). Retrospective review of ambulatory glucose patterns is an essential component for improving diabetes self-care. However, many CGM users become overwhelmed by the voluminous CGM data and rarely review or download their CGM. Furthermore, interpretation of CGM data should not occur in a vacuum, rather one should consider contextual factors that impact self-care in order to improve glycemic regulation. Thus, to maximize the clinical value of CGM in AYA with T1D, a novel, ecologically grounded approach is needed to contextualize CGM data with information on the intra- and inter-personal context in which glucose regulation occurs. It is timely to pair ecological momentary assessment (EMA) with CGM to develop an intervention program to improve self-care, glycemia, and psychosocial outcomes. We will use rigorous methods to capture dynamic relationships between in-the-moment ratings of emotional and social experiences (using EMA) and CGM-recorded glucose values, which will be collectively displayed on a dashboard, encapsulating the emotional and social context of ambulatory glucose (psychosocial ambulatory glucose [PAG]). Tracking and reviewing of PAG patterns, along with ongoing structured support, within a multicomponent intervention, will help AYA with T1D to better interpret and behaviorally respond to out-of-range glucose values, and may serve as a catalyst to improve A1c, TIR, and self-care, as well as reduce diabetes distress. Amit Shapira, PhD, proposes a series of studies with an overarching goal of developing, iteratively refining, and testing a PAG intervention in AYA with T1D. The proposed 3 specific aims are: 1) to identify salient components of a PAG dashboard using EMA that will coordinate the display of emotional and social context coupled with CGM recorded data to enhance self-care of AYA with T1D above target A1c values using mixed methods; 2) to adapt and build upon the dashboard for use in a behavioral intervention through expert feedback and guidance from pertinent stakeholders; and 3) to examine if a pilot RCT of a refined PAG behavioral intervention will be acceptable, feasible, and satisfactory to participants and have potential to improve diabetes and psychosocial outcomes compared with PAG-alone. Results from these studies will inform a fully powered RCT for a future R01 application. Dr. Shapira’s career objective is to become an independent diabetes behavioral researcher focused on optimizing self-care, including use of CGM and other technologies, to improve outcomes for people with T1D. The 5-year, mentored career development program will provide her with necessary skills in diabetes care (e.g., diabetes technologies), advanced statistical methods, and usability and qualitative research to launch her independence in diabetes behavioral investigation.