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

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Standard

DiaFocus : A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes. / Bardram, Jakob E.; Cramer-Petersen, Claus; Maxhuni, Alban; Christensen, Mads V.; Bækgaard, Per; Persson, Dan R.; Lind, Nanna; Christensen, Merete B.; Nørgaard, Kirsten; Khakurel, Jayden; Skinner, Timothy; Kownatka, Dagmar; Jones, Allan.

I: ACM Transactions on Computing for Healthcare, Bind 4, Nr. 2, 13, 2023.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Bardram, JE, Cramer-Petersen, C, Maxhuni, A, Christensen, MV, Bækgaard, P, Persson, DR, Lind, N, Christensen, MB, Nørgaard, K, Khakurel, J, Skinner, T, Kownatka, D & Jones, A 2023, 'DiaFocus: A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes', ACM Transactions on Computing for Healthcare, bind 4, nr. 2, 13. https://doi.org/10.1145/3586579

APA

Bardram, J. E., Cramer-Petersen, C., Maxhuni, A., Christensen, M. V., Bækgaard, P., Persson, D. R., Lind, N., Christensen, M. B., Nørgaard, K., Khakurel, J., Skinner, T., Kownatka, D., & Jones, A. (2023). DiaFocus: A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes. ACM Transactions on Computing for Healthcare, 4(2), [13]. https://doi.org/10.1145/3586579

Vancouver

Bardram JE, Cramer-Petersen C, Maxhuni A, Christensen MV, Bækgaard P, Persson DR o.a. DiaFocus: A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes. ACM Transactions on Computing for Healthcare. 2023;4(2). 13. https://doi.org/10.1145/3586579

Author

Bardram, Jakob E. ; Cramer-Petersen, Claus ; Maxhuni, Alban ; Christensen, Mads V. ; Bækgaard, Per ; Persson, Dan R. ; Lind, Nanna ; Christensen, Merete B. ; Nørgaard, Kirsten ; Khakurel, Jayden ; Skinner, Timothy ; Kownatka, Dagmar ; Jones, Allan. / DiaFocus : A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes. I: ACM Transactions on Computing for Healthcare. 2023 ; Bind 4, Nr. 2.

Bibtex

@article{4b80de0049db40dfbbf4cb3a33777931,
title = "DiaFocus: A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes",
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 article presents DiaFocus, which is a mobile health 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.",
author = "Bardram, {Jakob E.} and Claus Cramer-Petersen and Alban Maxhuni and Christensen, {Mads V.} and Per B{\ae}kgaard and Persson, {Dan R.} and Nanna Lind and Christensen, {Merete B.} and Kirsten N{\o}rgaard and Jayden Khakurel and Timothy Skinner and Dagmar Kownatka and Allan Jones",
year = "2023",
doi = "10.1145/3586579",
language = "English",
volume = "4",
journal = "ACM Transactions on Computing for Healthcare",
issn = "2691-1957",
publisher = "Association for Computing Machinery (ACM)",
number = "2",

}

RIS

TY - JOUR

T1 - DiaFocus

T2 - A Personal Health Technology for Adaptive Assessment in Long-Term Management of Type 2 Diabetes

AU - Bardram, Jakob E.

AU - Cramer-Petersen, Claus

AU - Maxhuni, Alban

AU - Christensen, Mads V.

AU - Bækgaard, Per

AU - Persson, Dan R.

AU - Lind, Nanna

AU - Christensen, Merete B.

AU - Nørgaard, Kirsten

AU - Khakurel, Jayden

AU - Skinner, Timothy

AU - Kownatka, Dagmar

AU - Jones, Allan

PY - 2023

Y1 - 2023

N2 - 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 article presents DiaFocus, which is a mobile health 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.

AB - 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 article presents DiaFocus, which is a mobile health 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.

U2 - 10.1145/3586579

DO - 10.1145/3586579

M3 - Journal article

VL - 4

JO - ACM Transactions on Computing for Healthcare

JF - ACM Transactions on Computing for Healthcare

SN - 2691-1957

IS - 2

M1 - 13

ER -

ID: 358890431