Self-efficacy and Physical Activity in Overweight and Obese Adults Participating in a Worksite Weight Loss Intervention: Multistate Modeling of Wearable Device Data.

BACKGROUND: Physical activity is associated with a reduced risk of numerous types of cancer and plays an important role in maintaining a healthy weight. Wearable physical activity trackers may supplement behavioral intervention and enable researchers to study how determinants like self-efficacy predict physical activity patterns over time.
METHODS: We used multistate models to evaluate how self-efficacy predicted physical activity states among overweight and obese individuals participating in a 26-week weight loss program (N = 96). We specified five states to capture physical activity patterns: (i) active (i.e., meeting recommendations for 2 weeks), (ii) insufficiently active, (iii) nonvalid wear, (iv) favorable transition (i.e., improvement in physical activity over 2 weeks), and (v) unfavorable transition. We calculated HRs of transition probabilities by self-efficacy, body mass index, age, and time.
RESULTS: The average prevalence of individuals in the active, insufficiently active, and nonvalid wear states was 13%, 44%, and 16%, respectively. Low self-efficacy negatively predicted entering an active state [HR, 0.51; 95% confidence interval (CI), 0.29-0.88]. Obesity negatively predicted making a favorable transition out of an insufficiently active state (HR, 0.61; 95% CI, 0.40-0.91). Older participants were less likely to transition to the nonvalid wear state (HR, 0.53; 95% CI, 0.30-0.93). Device nonwear increased in the second half of the intervention (HR, 1.73; 95% CI, 1.07-2.81).
CONCLUSIONS: Self-efficacy is an important predictor for clinically relevant physical activity change in overweight and obese individuals. Multistate modeling is useful for analyzing longitudinal physical activity data. IMPACT: Multistate modeling can be used for statistical inference of covariates and allow for explicit modeling of nonvalid wear.See all articles in this CEBP Focus section, "Modernizing Population Science." ©2019 American Association for Cancer Research.