Abstract People with Type 1 Diabetes Mellitus (T1DM) must frequently check their blood glucose and make over 180 health-critical decisions daily alongside everyday life decisions. These individuals heavily rely on glucose monitoring devices to monitor their glucose levels, yet the user interfaces do not support accurate interpretation and treatment decision-making. The constant need to check glucose levels several times a day also contributes to negative emotional impacts, including diabetes distress and burnout, where individuals eventually disengage from self-care. This dataset comprises three complementary components: (1) transcripts capturing how 27 individuals with T1DM interpret and make treatment decisions presented on their familiar monitoring interfaces, (2) questionnaire responses from 86 individuals with T1DM detailing their treatment actions across various glucose scenarios and (3) 11 smartwatch interfaces designed to support ambient, at-a-glance glucose awareness. Together, this dataset provides an in-depth investigation of interpretation errors, decision-making processes, and design opportunities. The dataset can support clinicians in understanding patient reasoning and provides researchers with a foundation for developing glucose interfaces that support better long-term diabetes self-management.
Kongdee et al. (Mon,) studied this question.