Appl Clin Inform 2020; 11(01): 070-078
DOI: 10.1055/s-0039-1701002
Research Article
Georg Thieme Verlag KG Stuttgart · New York

Self-Management Behaviors of Patients with Type 1 Diabetes: Comparing Two Sources of Patient-Generated Data

George Karway
1  College of Health Solutions, Arizona State University, Scottsdale, Arizona, United States
,
Maria Adela Grando
1  College of Health Solutions, Arizona State University, Scottsdale, Arizona, United States
,
Kevin Grimm
2  Department of Psychology, Arizona State University, Scottsdale, Arizona, United States
,
Danielle Groat
1  College of Health Solutions, Arizona State University, Scottsdale, Arizona, United States
3  Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, United States
,
Curtiss Cook
4  Department of Endocrinology, Mayo Clinic, Scottsdale, Arizona, United States
,
Bithika Thompson
4  Department of Endocrinology, Mayo Clinic, 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

14 June 2019

09 December 2019

Publication Date:
22 January 2020 (online)

Abstract

Objectives This article aims to evaluate adult type 1 diabetes mellitus (T1DM) self-management behaviors (SMBs) related to exercise and alcohol on a survey versus a smartphone app to compare self-reported and self-tracked SMBs, and examine inter- and intrapatient variability.

Methods Adults with T1DM on insulin pump therapy were surveyed about their alcohol, meal, and exercise SMBs. For 4 weeks, participants self-tracked their alcohol, meal, and exercise events, and their SMBs corresponding with these events via an investigator-developed app. Descriptive statistics and generalized linear mixed-effect models were used to analyze the data

Results Thirty-five participants self-tracked over 5,000 interactions using the app. Variability in how participants perceived the effects of exercise and alcohol on their blood glucose was observed. The congruity between SMBs self-reported on the survey and those self-tracked with the app was measured as mean (SD). The lowest congruity was for alcohol and exercise with 61.9% (22.7) and 66.4% (20.2), respectively. Congruity was higher for meals with 80.9% (21.0). There was significant daily intra- and interpatient variability in SMBs related to preprandial bolusing: recommended bolus, p < 0.05; own bolus choice, p < 0.01; and recommended basal adjustment, p < 0.01.

Conclusion This study highlights the variability in intra- and interpatient SMBs obtained through the use of a survey and app. The outcomes of this study indicate that clinicians could use both one-time and every-day assessment tools to assess SMBs related to meals. For alcohol and exercise, further research is needed to understand the best assessment method for SMBs. Given this degree of patient variability, there is a need for an educational intervention that goes beyond the traditional “one-size-fits-all” approach of diabetes management to target individualized treatment barriers.

Protection of Human and Animal Subjects

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