DiaFocus: A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes

Jakob E. Bardram, Claus Cramer-Petersen, Alban Maxhuni, Mads V.S. Christensen, Per Bækgaard, Dan R. Persson, Nanna Lind, Merete B. Christensen, Kirsten Nørgaard, Jayden Khakurel, Timothy C. Skinner, Dagmar Kownatka, Allan Jones

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Abstract

Type 2 diabetes (T2D) is a large disease burden worldwide and represents an increasing and complex challenge for all societies. For the individual, (T2D) is a complex, multi-dimensional, and long-term challenge to manage, and it is challenging to establish and maintain good communication between the patient and healthcare professionals. This paper presents DiaFocus, which is a mobile health (mHealth) sensing application for long-term ambulatory management of T2D. DiaFocus supports an adaptive collection of physiological, behavioral, and contextual data in combination with ecological assessments of psycho-social factors. This data is used for improving patient-clinician communication during consultations. DiaFocus is built using a generic data collection framework for mobile and wearable sensing and is highly extensible and customizable. We deployed DiaFocus in a 6-week feasibility study involving 12 patients with T2D. The patients found the DiaFocus approach and system useful and usable for diabetes management. Most patients would use such a system, if available as part of their treatment. Analysis of the collected data shows that mobile sensing is feasible for longitudinal ambulatory assessment of T2D, and helped identify the most appropriate target users being early diagnosed and technically literate T2D patients.
Original languageEnglish
Article number13
JournalACM Transactions on Computing for Healthcare
Volume4
Issue number2
Number of pages43
ISSN2637-8051
DOIs
Publication statusPublished - 2023

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