Date created: | Last Updated:

Category: Hypothesis

Description: Aim 1: To understand within-person dynamic relationships between BG metrics, function, and emotional well-being. Multi-level time-series analyses using CGM, EMA, and accelerometer data will examine the strength, directionality, and timing of these relationships on a short-term and daily basis. These analyses will be foundational to determine how BG, function, and emotional well-being are associated in real time, and which measures of BG have the most meaningful and robust relationships with function and emotional well-being. Hypothesis 1.1: Blood glucose variables have within-person effects on subsequent function and well-being. Hypothesis 1.2: Negative affect and stress have within-person effects on subsequent blood glucose, hyperglycemia and glycemic variability. Hypothesis 1.3: The effects are observed over both shorter (3 hours) and longer (day-to-day) time frames. Aim 2: To examine moderators of short-term and daily relationships between BG metrics, function, and emotional well-being. Demographics (e.g. age, sex, race, ethnicity), clinical and psychosocial characteristics (e.g. duration of T1D, CGM use global measures of self-management and emotional distress,), and average BG levels (HbA1c) will be examined as potential moderators. These analyses will inform the individualization of treatment recommendations to optimize both clinical and patient-reported outcomes. Hypothesis 2.1: Person-level moderators (age, sex, race, global DD, global DS, HbA1c, duration of T1D, treatment regimen, CGM use) moderate within-person relationships between blood glucose, emotional well-being, and function. Aim 3: To understand how short-term dynamics between BG, function, and emotional well-being are predictive of global function, well-being, and quality of life. We will examine the extent to which different BG metrics and their within-person relationships with momentary emotional well-being and function contribute to patient-reported outcomes. These analyses will pave the way for innovative, individualized just-in-time adaptive interventions to address the short-term dynamics that most adversely affect global quality of life. Hypothesis 3.1: Individual differences in blood glucose measures predict global function, well-being, and quality of life. Hypothesis 3.2: Individual differences in the effects of blood glucose measures on momentary function and emotions predict global function, well-being, and quality of life.