Abstract
Introduction:
Mobile health applications (apps) have been associated with improved glycemic outcomes in people with diabetes, but the behavioral factors leading to these outcomes remain poorly understood. The aim of this study was to quantify the impact of a diabetes app (mySugr®) on glycemic and non-glycemic outcomes and to explore the relationship between behavior and glycemic control by investigating app usage patterns.
Methods:
Glycemic (blood glucose [BG]) and non-glycemic (body mass index [BMI] and “tags” indicating hypoglycemia and hyperglycemia feelings) outcomes of mySugr users with type 1 (T1DM) or type 2 (T2DM) diabetes mellitus were collected in the app over 90 days and assessed through population analysis, including stratification by frequency of app usage. Linear modeling was employed to identify characteristics of app users that may predict glycemic outcomes.
Results:
Data from 80,044 mySugr users were analyzed. Improved glycemic control was observed (change in mean BG = −12.5 mg/dL; P < 0.001), correlating with app usage and was greatest in users with >16 app sessions/day. In users with T2DM, a 2.4% reduction from baseline was observed in mean BMI (−0.76 kg/m2; P < 0.001; n = 6910). Users with T1DM or T2DM reported reductions of 16% and 27% in hypoglycemia and hyperglycemia feelings, respectively (143,600 tags). Linear models showed a significant fit (P < 0.001) for both T1DM (n = 17,465) and T2DM (n = 39,069) users and explained a large degree of the variability in glycemic outcomes (R2 = 0.355 for T1DM and R2 = 0.444 for T2DM). Baseline glycemic control was the strongest predictor of glycemic outcomes, followed by number of BG logs and app engagement.
Conclusions:
Using a digital diabetes app can improve glycemic and non-glycemic outcomes in people with diabetes. This work also establishes a methodology to correlate user behavior with glycemic control.
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Supplementary Material
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