Teun Remmers

168 | Chapter 9 Strengths and weaknesss Study strengths are the utilization of GPS devices in order to investigate associations between the objectively assessed context-specific PA patterns (using GIS and GPS), adjusting for meteorological differences and the multilevel structure. However, this study also had some weaknesses. First, in order to reduce complexity of associations, analyses were conducted on a subsample (i.e. non-movers and living at a single address). Due to period-specific wear time validation criteria, the amount of measurement-days in our analyses was further reduced. The latter may be because children experienced the devices as uncomfortable or unfashionable. Although innovations to facilitate application of smaller and more comfortable devices are fast developing, extensive validations of performance both in PA- and location assessment are warranted. Attrition analyses revealed the same patterns as described in Table 1, with a decrease of LPA and MVPA in all segments except before school time. Second, when our definition of time-segments is compared to other studies, especially the time-segment during school may have been improved by additionally defining recess time (19, 53). However, as in our current analyses some associations could not be analysed due to limited data-points (e.g. such as activity at shopping centres), researchers are encouraged to balance specificity of time- segments and available data-points adequately. We found that during school hours, children spent considerable time outside school grounds (e.g. in active transport). This was unexpected, and may reflect activities in-between classes, activities during recess, or trips to externally located physical education facilities. Finally, although we were able to identify active transportation trips based on the GPS signal (i.e. walking and cycling), hip- worn Actigraph GT3X+ accelerometers may still have underestimated the workload of cycling trips (54). External validity Findings of this study may be generalizable to samples with comparable distances from children's residences to their primary- and secondary schools, similar school regimes and similar motives or regulations for active transport. For example, in the Netherlands, there are no organized passive transport programs in place (e.g. school busses) and the environment is generally supportive for active transport (e.g. absence of hills, high availability and quality of cycling paths, bike sheds at schools). This may increase the likelihood of active transport in the home-school commute, regardless of the distance between home and school. Children's or parental motives regarding PA, parental educational levels, and meteorological opportunities (due to hours of daylight) may be different from other international samples (55). In addition, time-constrains of children due to competing activities such as organized sports participation or homework may also be considered in comparing results with other studies.