Feasibility of Technology-Assisted Lifestyle Self-Monitoring in Older Adults With Type 2 Diabetes: Mixed Methods...

Type 2 diabetes is a major public health concern in older adults. Healthy lifestyles, such as physical activity and healthy eating, are effective strategies for diabetes self-management. Increasing evidence shows that health technologies can promote healthy lifestyles for diabetes management. However, limited research has evaluated their use among older adults with type 2 diabetes.

This study evaluated the feasibility and preliminary health outcomes of technology-assisted lifestyle monitoring for diabetes management in older adults with type 2 diabetes. The study also examined participants' experiences to identify barriers and facilitators to sustained technology-assisted lifestyle modification.

This 12-week pilot study used a pretest and posttest design. Feasibility was assessed by recruitment, retention, and adherence to device-based self-monitoring, including the percentage of days with tracked steps (PDWTs) and the percentage of days with food logs (PDWFLs). Fitbit fitness trackers paired with smartphone apps were used to track physical activity and food intake in 15 overweight/obese older adults with type 2 diabetes (mean age 70.5, SD 4.8 y). Self-monitoring behaviors were tracked throughout the study. Baseline and 12-week health outcomes (eg, hemoglobin A1c [HbA1c] and physical function) were compared using paired 2-tailed t tests or Wilcoxon signed rank tests, as appropriate; effect sizes were calculated using Cohen d. Associations between self-monitoring data (PDWTs, average daily steps, PDWFL) and health outcomes were examined using Pearson or Spearman correlations. Semistructured interviews were conducted at the study completion, and thematic analysis was used to analyze qualitative data.

The target sample (n=15) was successfully enrolled over 6 months, with 100% retention at 12 weeks. Feasibility was supported by consistent use of wearable devices for self-monitoring of physical activity, although dietary logging adherence varied. HbA1c decreased from baseline to 12 weeks (effect size -0.49, 95% CI -1.15 to -0.04; P=.04), and PDWFL was inversely correlated with HbA1c (r=-0.53; P=.04) at follow-up. The qualitative findings indicated that barriers and facilitators to technology-assisted lifestyle self-monitoring and diabetes management through lifestyle modifications exist across multiple levels, including the individual, interpersonal, organizational or community, and societal levels in older adults with type 2 diabetes. Factors at one level interacted with those at other levels. For example, limited technological proficiency challenged lifestyle tracking, while interpersonal and organizational support helped mitigate barriers.

Technology-assisted self-monitoring of lifestyle behaviors was feasible in this sample of older adults with type 2 diabetes and was associated with favorable signals in glycemic control. While causal inferences cannot be drawn from this single-arm pilot study, observed within-subject changes and behavioral-clinical correlations support further evaluation of technology-assisted lifestyle self-monitoring. The findings also highlight the importance of addressing interconnected factors at multiple levels, tailored to older adults' unique needs and capacities in diabetes self-management.