The effect of playground and nature-based interventions on physical activity and self-esteem in UK school children

School playtime provides opportunities for children to engage in physical activity (PA). Playground playtime interventions designed to increase PA have produced differing results. However, nature can also promote PA, through the provision of large open spaces for activity. The purpose of this study is to determine which playtime interventions are most effective at increasing moderate-to-vigorous physical activity (MVPA) and if this varies by school location. Fifty-two children from an urban and rural school participated in a playground sports (PS) and nature-based orienteering intervention during playtime for one week. MVPA was assessed the day before and on the final day of the interventions using accelerometers. Intervention type (p < 0.05) and school location (p < 0.001) significantly influenced MVPA; with PS increasing MVPA more than nature-based orienteering. Urban children seemed to respond to the interventions more positively; however, differences in baseline MVPA might influence these changes. There was a positive correlation for fitness and MVPA during PS (r = 0.32; p < 0.05), but not nature-based orienteering (p > 0.05). The provision of PS influences PA the most; however, a variety of interventions are required to engage less fit children in PA.

Brief response to Ashton and colleagues regarding Fractionating Human Intelligence

Ashton and colleagues concede in their response (Ashton, Lee, & Visser, in this issue), that neuroimaging methods provide a relatively unambiguous measure of the levels to which cognitive tasks co-recruit dif- ferent functional brain networks (task mixing). It is also evident from their response that they now accept that task mixing differs from the blended models of the classic literature. However, they still have not grasped how the neuroimaging data can help to constrain models of the neural basis of higher order ‘g’. Specifically, they claim that our analyses are invalid as we assume that functional networks have uncorrelated capacities. They use the simple analogy of a set of exercises that recruit multiple muscle groups to varying extents and highlight the fact that individual differences in strength may correlate across muscle groups. Contrary to their claim, we did not assume in the original article (Hampshire, High- field, Parkin, & Owen, 2012) that functional networks had uncorrelated capacities; instead, the analyses were specifically designed to estimate the scale of those correlations, which we referred to as spatially ‘diffuse’ factors