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.
