JMIR Publications

ABSTRACT

Background:

Type 1 diabetes (T1D) requires over 150 distinct self-management behaviors and continuous problem solving to maintain optimal glucose levels and prevent long-term health consequences. In addition to the complex physical, emotional, and cognitive development of adolescence, the ongoing development of executive functioning contributes to a lack of optimal diabetes self-management behaviors in this age group. Diabetes technologies such as continuous glucose monitors (CGMs) may lessen the burden of self-management tasks and CGM data can assist with regular problem-solving. However, the burden to perform self-management tasks can lead to diabetes distress and other poor mental health outcomes that inhibit optimal decision-making. Likewise, adolescent engagement with their CGM data remains low.

Objective:

The overarching objective of the Qualitative Insights to Type 1 Diabetes in Youth (QUALITY) study is to identify potential targets and strategies for future interventions to improve glycemic outcomes in adolescents with T1D using advanced diabetes technologies.

Methods:

Adolescents (12–18-year-olds) with T1D who regularly use CGMs will be recruited from a Midwest pediatric diabetes clinic for participation in a longitudinal, convergent mixed methods study. A purposive sampling strategy will be leveraged to ensure participants with varied glycemic levels and diabetes experiences are included. Enrolled participants (n=40) will complete a baseline survey to report the practice, self-efficacy, and perceptions of diabetes self-management behaviors, including diabetes technology use. Open-ended SMS text message surveys will be sent 4 times per day for 30 days to capture real-time narratives of diabetes self-management behaviors and CGM data use. In addition, participant CGMs will be used to capture real-time glucose levels for the same period. A sample (n~20) will complete a follow-up semi-structured interview focused on self-management behaviors and technology use. Glycemic metrics and baseline survey data will be analyzed using descriptive and inferential statistics. Text responses and interview transcripts will be analyzed following a grounded theory approach.

Results:

Based on previous real-time data collection performed in adolescents with T1D, we expect text message survey completion rates near 80%. Likewise, as participants will continue to use their own devices during the study, we anticipate near complete CGM data to be available. However, recruitment and enrollment may continue until appropriate data completeness and/or thematic saturation is achieved.

Conclusions:

While routine diabetes self-management behaviors and use of diabetes technologies are important for achieving glycemic goals, adolescents tend to struggle to consistently perform the necessary tasks. This innovative real-time mixed methods and longitudinal study will improve our understanding of daily decision making and influences on diabetes self-management and among adolescents with T1D. Findings from this study will provide value in understanding and intervening on facilitators and barriers to optimal adolescent diabetes self-management. Clinical Trial: N/A