A New Taxonomy for Technology-Enabled Diabetes Self-Management Interventions: Results of an Umbrella Review

Author:

Greenwood Deborah A.1ORCID,Litchman Michelle L.2ORCID,Isaacs Diana3,Blanchette Julia E.2ORCID,Dickinson Jane K.4ORCID,Hughes Allyson5ORCID,Colicchio Vanessa D.2ORCID,Ye Jiancheng6ORCID,Yehl Kirsten7ORCID,Todd Andrew8ORCID,Peeples Malinda M.9ORCID

Affiliation:

1. School of Nursing, UT Health San Antonio, TX, USA

2. University of Utah, College of Nursing, Salt Lake City, UT, USA

3. Cleveland Clinic Diabetes Center, Cleveland, OH, USA

4. Teachers College Columbia University, New York, NY, USA

5. T1D Exchange, Boston, MA, USA

6. Northwestern University Feinberg School of Medicine, Chicago, IL, USA

7. Association of Diabetes Care & Education Specialists, Chicago, IL, USA

8. University of Central Florida, College of Nursing, University Tower, Orlando, FL, USA

9. Welldoc, Columbia, MD, USA

Abstract

Background: A 2017 umbrella review defined the technology-enabled self-management (TES) feedback loop associated with a significant reduction in A1C. The purpose of this 2021 review was to develop a taxonomy of intervention attributes in technology-enabled interventions; review recent, high-quality systematic reviews and meta-analyses to determine if the TES framework was described and if elements contribute to improved diabetes outcomes; and to identify gaps in the literature. Methods: We identified key technology attributes needed to describe the active ingredients of TES interventions. We searched multiple databases for English language reviews published between April 2017 and April 2020, focused on PwD (population) receiving diabetes care and education (intervention) using technology-enabled self-management (comparator) in a randomized controlled trial, that impact glycemic, behavioral/psychosocial, and other diabetes self-management outcomes. AMSTAR-2 guidelines were used to assess 50 studies for methodological quality including risk of bias. Results: The TES Taxonomy was developed to standardize the description of technology-enabled interventions; and ensure research uses the taxonomy for replication and evaluation. Of the 26 included reviews, most evaluated smartphones, mobile applications, texting, internet, and telehealth. Twenty-one meta-analyses with the TES feedback loop significantly lowered A1C. Conclusions: Technology-enabled diabetes self-management interventions continue to be associated with improved clinical outcomes. The ongoing rapid adoption and engagement of technology makes it important to focus on uniform measures for behavioral/psychosocial outcomes to highlight healthy coping. Using the TES Taxonomy as a standard approach to describe technology-enabled interventions will support understanding of the impact technology has on diabetes outcomes.

Funder

Association of Diabetes Care and Education Specialists

Publisher

SAGE Publications

Subject

Biomedical Engineering,Bioengineering,Endocrinology, Diabetes and Metabolism,Internal Medicine

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