Eileen R Faulds1,2, Margaret Grey3, Heather Tubbs-Cooley1, Robert P Hoffman3, Lisa K Militello1, Alai Tan1, Mary Beth Happ4. 1. The Ohio State University College of Nursing, Columbus, Ohio, 43210. 2. The Ohio State University Wexner Medical Center, Columbus, Ohio, 43210. 3. Yale University School of Nursing, New Haven Connecticut. 4. Nationwide Children's Hospital Division of Endocrinology, Columbus, Ohio.
Abstract
OBJECTIVE: Only 17% of adolescents with type 1 diabetes (T1D) are currently meeting their glycemic targets despite advances in diabetes technologies. Self-management behaviors and challenges specific to use of diabetes technologies are insufficiently studied in adolescents. We aimed to describe the experience of diabetes technology self-management, including facilitators and barriers, among preteens/adolescents with low and high A1C. RESEARCH DESIGN AND METHODS: Youth (10-18 years of age) with T1D who use insulin pump therapy were recruited from the larger quantitative cohort of a mixed methods study for participation in semi-structured qualitative interviews. Maximum variability sampling was used to recruit youth with A1C <7.5% (n = 5) and A1C >9% (n = 5). Participants' personal insulin pump and continuous glucose monitoring data were downloaded and served as a visual reference. Interviews were analyzed using a qualitative descriptive approach. RESULTS: Participants were 50% female with a median age of 14.9 years and 80% used CGM. The sample was predominantly white (90.0%). Analysis produced four major themes, Bad Day, Expect the Unexpected, Nighttime Dependence, and Unpredictability, It's Really a Team and interconnecting subthemes. Youth characterized ''Bad Days'' as those requiring increased diabetes focus and self-management effort. The unpredictability (''Expect the Unexpected'') of glucose outcomes despite attention to self-management behaviors was considerable frustration. CONCLUSIONS: Diabetes devices such as insulin pumps are complex machines that rely heavily on individual proficiency, surveillance, and self-management behaviors to achieve clinical benefit. Our findings highlight the dynamic nature of self-management and the multitude of factors that feed youths' self-management behaviors.
OBJECTIVE: Only 17% of adolescents with type 1 diabetes (T1D) are currently meeting their glycemic targets despite advances in diabetes technologies. Self-management behaviors and challenges specific to use of diabetes technologies are insufficiently studied in adolescents. We aimed to describe the experience of diabetes technology self-management, including facilitators and barriers, among preteens/adolescents with low and high A1C. RESEARCH DESIGN AND METHODS: Youth (10-18 years of age) with T1D who use insulin pump therapy were recruited from the larger quantitative cohort of a mixed methods study for participation in semi-structured qualitative interviews. Maximum variability sampling was used to recruit youth with A1C <7.5% (n = 5) and A1C >9% (n = 5). Participants' personal insulin pump and continuous glucose monitoring data were downloaded and served as a visual reference. Interviews were analyzed using a qualitative descriptive approach. RESULTS: Participants were 50% female with a median age of 14.9 years and 80% used CGM. The sample was predominantly white (90.0%). Analysis produced four major themes, Bad Day, Expect the Unexpected, Nighttime Dependence, and Unpredictability, It's Really a Team and interconnecting subthemes. Youth characterized ''Bad Days'' as those requiring increased diabetes focus and self-management effort. The unpredictability (''Expect the Unexpected'') of glucose outcomes despite attention to self-management behaviors was considerable frustration. CONCLUSIONS: Diabetes devices such as insulin pumps are complex machines that rely heavily on individual proficiency, surveillance, and self-management behaviors to achieve clinical benefit. Our findings highlight the dynamic nature of self-management and the multitude of factors that feed youths' self-management behaviors.
Authors: Bartłomiej Matejko; Małgorzata Grzanka; Beata Kieć-Wilk; Maciej T Małecki; Tomasz Klupa Journal: Ann Agric Environ Med Date: 2013 Impact factor: 1.447
Authors: Melissa J Schoelwer; Jessica L Robic; Thibault Gautier; Chiara Fabris; Kelly Carr; Mary Clancy-Oliveri; Sue A Brown; Stacey M Anderson; Mark D DeBoer; Daniel R Cherñavvsky; Marc D Breton Journal: Diabetes Technol Ther Date: 2020-03-02 Impact factor: 6.118