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

项目摘要/摘要 患有1型糖尿病(T1D)的青少年和青壮年(Aya)的血红蛋白A1c值最高 在整个生命周期内。连续血糖监测(CGM)是一种现代的血糖评估方法 提供有关血糖水平的即时信息，以帮助优化范围内时间([TIR]70-180 Mg/dL)。动态血糖模式的回顾是改善糖尿病的重要组成部分 自我照顾。然而，许多CGM用户被海量的CGM数据淹没了，很少查看或 下载他们的CGM。此外，对CGM数据的解释不应在真空中进行，而应在真空中进行 应考虑影响自我护理的环境因素，以改善血糖调节。因此，要 在患有T1D的AYA中最大限度地发挥CGM的临床价值，需要一种新的、生态基础的方法来 将CGM数据与葡萄糖调节所处的个人内和个人之间的环境信息联系起来 发生。将生态瞬时评估(EMA)与CGM配对以开发干预措施是及时的 改善自我护理、血糖和心理社会结果的计划。我们将用严谨的方法 情绪和社会体验的即时评分(使用EMA)和 CGM记录的血糖值，将集中显示在仪表板上，封装了 动态血糖的情绪和社会背景(心理社会动态血糖[PAG])。跟踪 以及在多组件干预中审查PAG模式以及持续的结构化支持， 将帮助患有T1D的Aya更好地解释和行为反应超出范围的血糖值，并可能 作为一种催化剂，改善A1c、TIR和自我护理，以及减少糖尿病痛苦。阿米特·夏皮拉，博士 提出了一系列研究，主要目标是开发、迭代地改进和测试PAG T1D对AYA的干预。建议的3个具体目标是：1)确定PAG的显著组成部分 使用EMA的仪表板将配合CGM协调情感和社交背景的显示 使用混合方法记录T1D高于目标A1C值的Aya的自我护理；2) 调整和构建仪表板，以便通过专家反馈和指导在行为干预中使用 来自相关利益相关者的；以及3)检查改进的PAG行为干预的试点RCT是否将 参与者可以接受、可行和满意，并有可能改善糖尿病和心理社会 结果与单独PAG相比。这些研究的结果将为未来的全功率随机对照试验提供信息 R01应用程序。夏皮拉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 使用T1D。为期5年的有指导的职业发展计划将为她提供糖尿病方面的必要技能 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 启动她在糖尿病行为调查中的独立性。

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.