Using linked accelerometer and GPS data for characterizing children's schoolyard physical activity: An overview of hot spot analytic decisions with reporting guidelines

Abstract

Hot spot analysis of linked accelerometer and Global Positioning System data is often used to identify areas of high/low activity in the schoolyard. We illustrate the potential impact of a suite of methodological decisions (i) accelerometer metric; (ii) monitor epoch; (iii) number of recess periods/days and level of aggregation; (iv) sample size; (v) distance band; (vi) spatial versus spatiotemporal weighting scheme; and (vii) time band. Accelerometer metrics resulted in different clustering patterns. Longer epochs resulted in a less detailed picture of schoolyard behavior. Level of data aggregation impacted cluster patterns due to inter-period and inter-day differences, but clusters were consistent with increasing sample size. Use of spatiotemporal weight matrices resulted in better separation of hot and cold spots and revealed potentially important temporal clustering patterns. Increasing distance or time band resulted in reallocation of small clusters to larger clusters. Hot spot analysis decisions should be clearly reported in future studies.