Statistical analyses
sedentary behaviors
EVENTS
Descriptive analyses were conducted to summarize participants' baseline characteristics by condition. Fisher's exact tests compared the groups on reported medical events. Wilcoxon rank sum tests compared the groups on days of activity tracking and Facebook engagement. To evaluate intervention effects relative to the self‐help group, we used an intention‐to‐treat approach including data from all participants. We conducted repeated measures analyses using generalized estimating equation (GEE) analyses to compare the effects of the intervention and self‐help groups on total PA min/week over the course of the 12‐month study. Based on examination of spaghetti plots showing the trajectory of accelerometer‐measured and self‐reported activity over time from baseline to 6 to 12 months, it appeared that the general activity trends over time were often non‐linear. Therefore, time was treated as categorical to allow the longitudinal model to accommodate non‐linear trends over time. The longitudinal analyses modeled accelerometer‐measured and self‐reported PA outcomes (total, MVPA, light, steps, sedentary behaviors) by group, time as a 3‐level category (i.e., baseline as reference, month 6, and month 12), and the interaction between group and time. These models estimated activity changes over time from baseline to 12 months and 6 to 12 months within groups, as well as differences in changes over time from baseline to 12 months and 6 to 12 months between groups. As prespecified in the study protocol, adjusted models included education, time since diagnosis, age, and wear time (accelerometer‐measured outcomes only) as covariates.