Abstract
Over the past several years, activity monitors have become very popular in the general population, and due to their low cost and ease of use, are starting to be seen as clinical tools for the assessment of interventions. This presents researchers with the opportunity to better understand how activity, or lack thereof, is related to the recovery of patients. However, even in individuals without disabilities, there is a high degree of variability in activity monitor data which must be better understood in order to produce clinically meaningful interpretation of such data.What sources of variability contribute the most to the daily scatter in activity data as measured by StepWatches in youth with Cerebral Palsy (CP)? In particular, do non-clinical factors such as weather and location contribute to this variability significantly?This was a retrospective study making use of data from our activity monitoring protocol of youths with CP who obtain single event multi-level surgeries. Before and after these surgeries, 57 such youths aged 4.2–21.3 years were issued StepWatches to monitor daily activity for 8 day periods over 24 months duration. Weather data and walk scores for the patients’ home locations were collected from online databases. Steps per hour were predicted from clinical and environmental data using bootstrapped regression to determine the stability of regression coefficients and the percent variability explained by each variable.Time since surgery, age, season, GMFCS level, and surgical burden were significant variables in the model. Of them, GMFCS level was most important and explained nearly 16% of the variability in the data. Temperature, precipitation, and walk score had small effects on step count variance.Understanding sources of variability in step-counts is important if such a measure is to be used as a clinical measure of recovery, and may be important in the consideration of future surgical planning.
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