Abstract
Community participation, as indicated by mobility and engagement in socially meaningful activities, is a central component of health based on the International Classification of Health, Functioning, and Disease (WHO, 2001). Global positioning systems (GPS) technology is emerging as a tool for tracking mobility and participation in health and disability-related research. This paper fills a gap in the literature and provides a thorough description of a method that can be used to generate a number of different variables related to the constructs of mobility and participation from GPS data. Here, these variables are generated with the help of ST-DBSCAN, a spatiotemporal data mining algorithm. The variables include the number of unique destinations, activity space area, distance traveled, time in transit, and time at destinations. Data obtained from five individuals with psychiatric disabilities who carried GPS-enabled cell phones for two weeks are presented. Within- and across- individual variability on these constructs was observed. Given the feasibility of gathering data with GPS, larger scale studies of mobility and participation employing this method are warranted.
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