Deborah A Greenwood1, Michelle L Litchman2, Diana Isaacs3, Julia E Blanchette2, Jane K Dickinson4, Allyson Hughes5, Vanessa D Colicchio2, Jiancheng Ye6, Kirsten Yehl7, Andrew Todd8, Malinda M Peeples9. 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.
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.
Entities:
Keywords:
A1C; diabetes care and education; diabetes self-management education and support; taxonomy; technology-enabled self-management; umbrella review
Authors: Michelle L Litchman; Heather R Walker; Ashley H Ng; Sarah E Wawrzynski; Sean M Oser; Deborah A Greenwood; Perry M Gee; Mellanye Lackey; Tamara K Oser Journal: J Diabetes Sci Technol Date: 2019-03-10
Authors: Lyndsay A Nelson; Robert A Greevy; Andrew Spieker; Kenneth A Wallston; Tom A Elasy; Sunil Kripalani; Chad Gentry; Erin M Bergner; Lauren M LeStourgeon; Sarah E Williamson; Lindsay S Mayberry Journal: Diabetes Care Date: 2020-11-05 Impact factor: 19.112