Development of a measurement approach to assess time children participate in organized sport, active travel, outdoor active play, and curriculum-based physical activity

Abstract

BackgroundChildren participate in four main types of physical activity: organized sport, active travel, outdoor active play, and curriculum-based physical activity. The objective of this study was to develop a valid approach that can be used to concurrently measure time spent in each of these types of physical activity.MethodsTwo samples (sample 1: n = 50; sample 2: n = 83) of children aged 10–13 wore an accelerometer and a GPS watch continuously over 7 days. They also completed a log where they recorded the start and end times of organized sport sessions. Sample 1 also completed an outdoor time log where they recorded the times they went outdoors and a description of the outdoor activity. Sample 2 also completed a curriculum log where they recorded times they participated in physical activity (e.g., physical education) during class time.ResultsWe describe the development of a measurement approach that can be used to concurrently assess the time children spend participating in specific types of physical activity. The approach uses a combination of data from accelerometers, GPS, and activity logs and relies on merging and then processing these data using several manual (e.g., data checks and cleaning) and automated (e.g., algorithms) procedures. In the new measurement approach time spent in organized sport is estimated using the activity log. Time spent in active travel is estimated using an existing algorithm that uses GPS data. Time spent in outdoor active play is estimated using an algorithm (with a sensitivity and specificity of 85%) that was developed using data collected in sample 1 and which uses all of the data sources. Time spent in curriculum-based physical activity is estimated using an algorithm (with a sensitivity of 78% and specificity of 92%) that was developed using data collected in sample 2 and which uses accelerometer data collected during class time. There was evidence of excellent intra- and inter-rater reliability of the estimates for all of these types of physical activity when the manual steps were duplicated.ConclusionsThis novel measurement approach can be used to estimate the time that children participate in different types of physical activity.Electronic supplementary materialThe online version of this article (10.1186/s12889-018-5268-1) contains supplementary material, which is available to authorized users.

Pedestrian traffic safety and outdoor active play among 10–13 year olds living in a mid-sized city

“…The method for assessing outdoor active play over 7 consecutive days was developed by our laboratory as part of the larger study from which the data for this paper were drawn ( Borghese and Janssen, 2018 ). As explained below, this method uses data from several sources and includes a combination of manual checks and automated steps.…”

Duration and intensity of different types of physical activity among children aged 10–13 years

“…A description of the measurement approach used to assess time spent in these different types of physical activity, including measurement devices used, steps used to clean and merge the data collected by these devices, algorithms, and decisions rules used when processing the data, and the validity and reliability of these methods are available elsewhere (Borghese and Janssen 2018). A brief description is provided below.…”

“…Merged accelerometer and GPS data were then combined with geographic information system (GIS) data in ArcMap 10.5 (ESRI, Redlands, CA) to identify whether each epoch occurred while the participant was indoors (i.e., within a building footprint) or outdoors. We then applied an algorithm to correct some of the error in the precision of location estimates which resulted from poor signal quality (Borghese and Janssen 2018).…”

“…Trips with the same start and end destination (e.g., walking around the neighbourhood, going for a run) were excluded because they were considered travel for leisure rather than active travel to a specific destination. Identification of outdoor active play was done using a previously established prediction algorithm that classified epochs as either being part of outdoor active play or not using a combination of accelerometer, GPS, GIS, and self-report data (Borghese and Janssen 2018). Epochs that occurred while sleeping, indoors, or during school curriculum time, organized sport, or active travel were excluded prior to applying the outdoor active play algorithm.…”

“…Epochs that occurred while sleeping, indoors, or during school curriculum time, organized sport, or active travel were excluded prior to applying the outdoor active play algorithm. Identification of curriculum-based physical activity was done using a previously established prediction algorithm that classified epochs that occur during school curriculum time as being either part of curriculum-based physical activity or not (Borghese and Janssen 2018). Epochs flagged as being part of each type of physical activity were summed and the average minutes/day was calculated.…”