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

The study successfully enrolled the target sample with 100% retention at 12 weeks.

• 15 overweight/obese older adults with type 2 diabetes were enrolled (mean age 70.5, SD 4.8 years)
• Target sample of n=15 was successfully enrolled over 6 months
• 100% retention was achieved at the 12-week endpoint
• Study used a pretest and posttest (single-arm) design with no control group

Adherence to physical activity tracking via wearable devices was consistent, while dietary logging adherence varied.

• Feasibility was assessed by recruitment, retention, and adherence measured via percentage of days with tracked steps (PDWTs) and percentage of days with food logs (PDWFLs)
• Fitbit fitness trackers paired with smartphone apps were used to track both physical activity and food intake
• Consistent use of wearable devices for self-monitoring of physical activity was observed throughout the 12-week period
• Dietary logging adherence was described as variable across participants

HbA1c significantly decreased from baseline to 12 weeks with a medium effect size.

• HbA1c decreased from baseline to 12 weeks with an effect size of -0.49 (95% CI -1.15 to -0.04)
• The change in HbA1c was statistically significant (P=.04)
• Comparisons were made using paired 2-tailed t tests or Wilcoxon signed rank tests as appropriate
• Effect sizes were calculated using Cohen d

Greater dietary logging adherence was inversely correlated with HbA1c levels at 12-week follow-up.

• Percentage of days with food logs (PDWFL) was inversely correlated with HbA1c at follow-up (r=-0.53; P=.04)
• This indicates that participants who logged food more frequently tended to have lower HbA1c values at 12 weeks
• Associations between self-monitoring data and health outcomes were examined using Pearson or Spearman correlations

Barriers and facilitators to technology-assisted lifestyle self-monitoring existed across multiple socioecological levels and interacted with one another.

• Qualitative data were collected via semistructured interviews conducted at study completion and analyzed using thematic analysis
• Barriers and facilitators were identified at the individual, interpersonal, organizational or community, and societal levels
• Limited technological proficiency was identified as an individual-level barrier to lifestyle tracking
• Interpersonal and organizational support helped mitigate individual-level barriers
• Factors at one level interacted with those at other levels

The study used a mixed methods design combining quantitative health outcome measurement with qualitative interviews to evaluate feasibility and participant experiences.

• This was a 12-week pilot study using a pretest and posttest design
• Quantitative measures included HbA1c, physical function, self-monitoring adherence (PDWTs, PDWFLs), and average daily steps
• Qualitative component consisted of semistructured interviews at study completion analyzed via thematic analysis
• The study explicitly notes that causal inferences cannot be drawn from this single-arm pilot study