To estimate time with diabetes distress using ecological momentary assessment (EMA) in people with type 1 diabetes and analyze its associations with glycemic management based on continuous glucose monitoring (CGM).


We used EMA to assess diabetes distress in a sample of recently hospitalized adults with type 1 diabetes once a day for 17 consecutive days in an ambulatory setting. Additionally, participants were asked daily about hypoglycemia distress (<70 mg/dL [3.9 mmol/L]), hyperglycemia distress (>180 mg/dL [10 mmol/L]), and variability distress (glucose fluctuations). Per person, the percentage of days with elevated distress was calculated (time with distress). Multilevel regression was used to analyze daily associations of distress ratings with CGM-derived parameters. EMA-derived associations between diabetes distress and glycemic outcomes were compared with questionnaire-derived associations.


Data of 178 participants were analyzed. Participants spent a mean (SD) of days in a state of diabetes distress, 54.6 ± 26.0% in hyperglycemia distress, 45.2 ± 27.5% in variability distress, and 23.0 ± 19.3% in hypoglycemia distress. In multilevel analyses, higher daily ratings of diabetes distress were significantly associated with hyperglycemia (β = 0.41). Results showed high between-person variability as explanation of variance of the models ranged between 22.2 and 98.8%. EMA-derived diabetes distress showed a significant association with mean glucose (r = 0.25), while questionnaire-based diabetes distress did not (r = 0.10). Prospectively, time with diabetes distress was associated with HbA1c at the 3-month follow-up (r = 0.27), while questionnaire-based distress showed no association (r = 0.11).


Time with distress as assessed with EMA showed a comparative advantage over distress as determined by questionnaire-based assessment of diabetes distress regarding associations with glycemic management.

Clinical trial reg. no. NCT03811132, clinicaltrials.gov

This article contains supplementary material online at https://doi.org/10.2337/figshare.19669101.

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