ArticleScientific data2026
Multimodal dataset on glucose interpretation, treatment decisions and smartwatch visualisation for type 1 diabetes.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Multimodal dataset on glucose interpretation, treatment decisions and smartwatch visualisation for type 1 diabetes.Scientific data · 2026Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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