Older Age And Health Status Are Associated With Smartwatch Use Over 12 Months In The Electronic Framingham Heart Study

Introduction: Long-term use is critical for successful clinical or research applications of digital devices, but digital health studies are challenged by significant early discontinuation of use. Hypothesis: We sought to identify factors associated with long-term use of a smartwatch among participants enrolled in the electronic Framingham Heart Study (eFHS). We hypothesized that sociodemographic and health variables are associated with watch use. Methods: Participants were provided with a study smartwatch and were asked to wear the watch daily. We examined watch use over 12 months. Weekly watch use was defined as a binary response (yes=watch wear for ≥1 days for ≥ 5 hours per day, vs. no). We considered 19 different predictors including sociodemographic, health behaviors, and family relationship. We selected an individual predictor for watch use ( P <0.05) using generalized linear mixed models (GLMM) adjusted for age, sex, and weeks of watch use. We further built a model with all predictors selected from initial testing adjusted for age, sex, and weeks. We report odds ratios (OR) and 95% confidence interval (95%CI). Results: Among 1243 participants (mean age 53 years, 59% women), watch use was highest in the age-group ≥65 years, and decreased linearly over time in all participants (Figure). In GLMM adjusted for age, sex, and weeks, we found that self-reported health status (excellent vs good, fair or poor) (OR=2.7; 95%CI, 1.6-4.8), BMI (OR=0.9; 95%CI, 0.9-1.0) per 1 kg/m 2 increase, and depressive symptoms (OR=0.5; 95%CI, 0.3-0.8) were associated with watch use. In the model with all selected predictors, age-group > 65 (OR=4.0; 95%CI, 1.4 -11.6), excellent health (OR=2.3; 95%CI, 1.3-4.1), and depressive symptoms (OR=0.5; 95%CI, 0.3-0.9) remained significant. Conclusions: Older age, lack of depressive symptoms, and self-reported excellent health were associated with greater use of the smartwatch over the 12-month follow-up. Consideration of these factors in planning future digital studies may improve participation.