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