2024/08/20 by Vu, My H., Black, David S, Vidmar, Alaina +1
#Medicine and Health Sciences #Science and Technology Studies #Social and Behavioral Sciences #Translational Medical Research #behavioral intervention #biofeedback #continuous glucose monitoring #diabetes prevention #digital health #problem solving
paper · doi:10.17605/osf.io/u3a7q
The role of a standalone continuous glucose monitoring (CGM) system to operate as a feedback stimulus to maintain glucose levels within a target range is not well understood in terms of determinant behavioral principles. In this case series trial, we examined CGM sensor interstitial glucose levels in two adults without diabetes. Participants received only verbal introductory instructions on CGM functionality and the definition of sensor glucose. We generated within-subject heat maps and learning curves to analyze percent time-out of range (%TOR) by day across a minimum of 16 days. During this period, participants received glucose feedback on their personal smartphone through a graphical display, with time on the x-axis and glucose levels in mg/dL on the y-axis. A shaded gray area highlighted periods when glucose levels exceeded the upper normoglycemic range (>140 mg/dL), and auditory alerts sounded at this high excursion. Graphical analyses were used to evaluate whether CGM feedback could reinforce daily glucose control over time without additional intervention. In Case A, where the female participant consistently reviewed CGM feedback, a notable decrease in average daily %TOR was observed from the first to the second sensor phase (9.2% to 1.9%) along with a reduction in the median daily number of such excursions: 1.5 to 0.0). Conversely, no %TOR improvement was observed in Case B, where the male participant, citing competing vocational demands, reviewed CGM feedback very infrequently (14.2% to 19.1%; median daily number of excursions: 2.0 to 3.0). This investigation suggests that, in individuals without diabetes, standalone CGM feedback can facilitate glucose control by contingency-shaped learning, but this requires engagement with the feedback provided by the device. Consequently, time spent viewing feedback data appears to be a critical variable for consideration in future trials assessing the effects of CGM on glucose control in individuals without diabetes.