JMIR Publications

ABSTRACT

Background:

Individuals with type 1 diabetes (T1D) represent a population with important vulnerabilities and short-term dynamic interactions among physiological, behavioral, psychological, and cognitive processes. Ecological Momentary Assessment (EMA), a methodological approach used to study intra-individual variation over time, has only recently been used to deliver cognitive assessments in daily life and many methodological questions remain. The Glycemic Variability and Fluctuations in Cognitive Status in Adults with Type 1 Diabetes Study (GluCog) utilizes EMA to deliver cognitive and self-report measures while simultaneously collecting passive interstitial glucose in adults with T1D.

Objective:

Our aim is to report the results of an EMA optimization pilot (N=20) and how these data were used to refine the study design of the GluCog Study. The optimization pilot was designed to determine whether low frequency EMA (3/day) over more days or high frequency EMA (6/day) for fewer days would 1) result in better EMA completion rate and 2) capture more episodes of hypoglycemia. A secondary aim was to reduce the number of cognitive EMA tasks from 6 to 3.

Methods:

Baseline cognitive tasks and psychological questionnaires were completed by all participants, followed by EMA delivery of brief cognitive and self-report measures for 15 days while wearing a blinded continuous glucose monitor (CGM) to measure interstitial glucose. CGM was coded for the presence of hypoglycemia (<70 mg/dL) within 60 minutes of each EMA. Participants were randomized to Group A (N=10; starting with 3/day EMA for 10 days, and then switching to 6/day for an additional 5 days) or Group B (N = 10; starting with 6/day EMA for 5 days, and then switching to 3/day for an additional 10 days).

Results:

Two participants were excluded from Group A due to completing less than 50% of EMA. A paired samples t-test found no significant difference in completion rate between the two schedules (t(17) = 1.16, P = .26, dz = .27), with both schedules producing over 80% EMA completion. However, more hypoglycemia episodes were captured during the 3 EMA/day schedule.

Conclusions:

Results from this EMA optimization pilot guided key design decisions regarding EMA frequency and study duration for the main GluCog study. The present report responds to the urgent need for systematic and detailed information on EMA study designs, particularly those employing cognitive assessment coupled with physiological measures. Given the complexity of EMA studies, choosing the right instruments and assessment schedules is an important aspect of study design and subsequent data interpretation. Empirically determining these parameters in the target population will ensure adequate sampling of the phenomena of interest.