"Nothing is linear": Characterizing the determinants and dynamics of CGM use in older adults with type 1 diabetes. (February 2023)

• Record Type: Journal Article
• Authors: Kahkoska, Anna R.; Smith, Cambray; Thambuluru, Sirisha; Weinstein, Joshua; Batsis, John A.; Pratley, Richard; Weinstock, Ruth S.; Young, Laura A.; Hassmiller Lich, Kristen
• Is Part Of: Diabetes research and clinical practice. Volume 196(2023)
• Publication Date: 2023-02
• Subjects: Type 1 diabetes -- Older adults -- Continuous glucose monitoring -- Systems science -- Participatory system dynamics; T1D Type 1 diabetes -- CGM Continuous glucose monitoring -- GMB Group model building -- CLD Causal loop diagramming; Diabetes -- Periodicals; Diabetes Mellitus -- Periodicals; 616.462
• DOI: 10.1016/j.diabres.2022.110204
• Languages: English
• ISSNs: 0168-8227

Abstract

Highlights: CGM can improve glycemic management and increase quality of life for older adults living with type 1 diabetes, yet there are known age-specific barriers to technology use in this age group. This study used a participatory approach to system dynamics modeling called group model building to engage older adults with type 1 diabetes (including CGM users and non-users) and their caregivers. To our knowledge, few studies to date have extended participatory systems science methods to engage older adult patients. We present the first system model of the factors that influence CGM uptake and use over time, including the hypothesized ways in which they interact to reinforce versus inhibit CGM use through feedback loops. The system model offers insight into the dynamic barriers or problematic patterns that may inhibit effective CGM use in older adults (i.e., negative, balancing loops), as well as where there are high-leverage points for interventions to promote sustained CGM use (i.e., positive, reinforcing loops). Modeling the system structure illuminates opportunities to tailor education and support for older adults, using interventions that leverage key feedback loops at critical moments in the CGM learning curve to promote and sustained effective use. Abstract: Aims: Continuous glucose monitoring (CGM) can reduce hypoglycemia in older adults with type 1 diabetes (T1D). We aimed to characterize factors that influence effective use in this age group. Methods: Older adults with type T1D (age ≥ 65) and their caregivers participated in one of a series of parallel group model building workshops, a participatory approach to system dynamics involving drawing and scripted group activities. Data were synthesized in a qualitative model of the hypothesized system of factors producing distinct patterns of CGM use in older adults. The model was validated through virtual follow-up interviews. Results: Data were collected from 33 participants (four patient-caregiver dyads, mean age 73.8 ± 4.4 years [range 66–85 years]; 16 % non-CGM users, 79 % pump users). The system model delineates drivers of CGM uptake, drivers of ongoing CGM use, and feedback loops that either reinforce or counteract future CGM use. Participants emphasized the importance of different sets of feedback loops at different points in the duration of CGM use. Conclusions: The holistic system model underscores that factors and feedback loops driving effective CGM use in older adults are both individualized and dynamic (e.g., changing over time), suggesting opportunities for staged and tailored age-specific education and support.