Download PDF
Appl Clin Inform 2018; 09(02): 440-449
DOI: 10.1055/s-0038-1660438
Research Article
Schattauer GmbH Stuttgart

Design and Testing of a Smartphone Application for Real-Time Self-Tracking Diabetes Self-Management Behaviors

Danielle Groat
1   Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, United States
2   Department of Biomedical Informatics, Arizona State University, Scottsdale, Arizona, United States
,
Hiral Soni
2   Department of Biomedical Informatics, Arizona State University, Scottsdale, Arizona, United States
,
Maria Adela Grando
2   Department of Biomedical Informatics, Arizona State University, Scottsdale, Arizona, United States
,
Bithika Thompson
3   Division of Endocrinology, Mayo Clinic Arizona, Scottsdale, Arizona, United States
,
David Kaufman
2   Department of Biomedical Informatics, Arizona State University, Scottsdale, Arizona, United States
,
Curtiss B. Cook
2   Department of Biomedical Informatics, Arizona State University, Scottsdale, Arizona, United States
3   Division of Endocrinology, Mayo Clinic Arizona, Scottsdale, Arizona, United States
› Author Affiliations Funding This research was supported by the 2018 Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery and the Arizona State University Research Acceleration Grant.
Further Information

Publication History

07 February 2018

24 April 2018

Publication Date:
20 June 2018 (online)

Also available at
   Permissions and Reprints

Abstract

Background Type 1 diabetes (T1D) care requires multiple daily self-management behaviors (SMBs). Preliminary studies on SMBs rely mainly on self-reported survey and interview data. There is little information on adult T1D SMBs, along with corresponding compensation techniques (CTs), gathered in real-time.

Objective The article aims to use a patient-centered approach to design iDECIDE, a smartphone application that gathers daily diabetes SMBs and CTs related to meal and alcohol intake and exercise in real-time, and contrast patients' actual behaviors against those self-reported with the app.

Methods Two usability studies were used to improve iDECIDE's functionality. These were followed by a 30-day pilot test of the redesigned app. A survey designed to capture diabetes SMBs and CTs was administered prior to the 30-day pilot test. Survey results were compared against iDECIDE logs.

Results Usability studies revealed that participants desired advanced features for self-tracking meals and alcohol intake. Thirteen participants recorded over 1,200 CTs for carbohydrates during the 30-day study. Participants also recorded 76 alcohol and 166 exercise CTs. Comparisons of survey responses and iDECIDE logs showed mean% (standard deviation) concordance of 77% (25) for SMBs related to meals, where concordance of 100% indicates a perfect match. There was low concordance of 35% (35) and 46% (41) for alcohol and exercise events, respectively.

Conclusion The high variability found in SMBs and CTs highlights the need for real-time diabetes self-tracking mechanisms to better understand SMBs and CTs. Future work will use the developed app to collect SMBs and CTs and identify patient-specific diabetes adherence barriers that could be addressed with individualized education interventions.

Keywords

patient self-care - smartphone - usability testing - survey - diabetes

Protection of Human and Animal Subjects

This study was reviewed by the Arizona State University and Mayo Clinic Institutional Review Boards.


Supplementary Material