This paper investigates whether encouraging children to become more physically active in their everyday life affects their primary school performance. We use data from a field quasi‐experiment called the Active Living Program, which aimed to increase active modes of transportation to school and active play among 8‐ to 12‐year‐olds living in low socioeconomic status (SES) areas in the Netherlands. Difference‐in‐differences estimations reveal that while the interventions increase time spent on physical activity during school hours, they negatively affect school performance, especially among the worst‐performing students. Further analyses reveal that increased restlessness during instruction time is a potential mechanism for this negative effect. Our results suggest that the commonly found positive effects of exercising or participating in sports on educational outcomes may not be generalizable to physical activity in everyday life. Policymakers and educators who seek to increase physical activity in everyday life need to weigh the health and well‐being benefits against the probability of increasing inequality in school performance.
In this study we measured the performance times on the Wheelchair Mobility Performance (WMP) test during different test conditions to see if the performance times changed when wheelchair settings were changed. The overall performance time on the WMP test increased when the tire pressure was reduced and also when extra mass was attached to the wheelchair. It can be concluded that the WMP test is sensitive to changes in wheelchair settings. It is recommended to use this field-based test in further research to investigate the effect of wheelchair settings on mobility performance time. Objective: The Wheelchair Mobility Performance (WMP) test is a reliable and valid measure to assess mobility performance in wheelchair basketball. The aim of this study was to examine the sensitivity to change of the WMP test by manipulating wheelchair configurations. Methods: Sixteen wheelchair basketball players performed the WMP test 3 times in their own wheelchair: (i) without adjustments (“control condition”); (ii) with 10 kg additional mass (“weighted condition”); and (iii) with 50% reduced tyre pressure (“tyre condition”). The outcome measure was time (s). If paired t-tests were significant (p < 0.05) and differences between conditions were larger than the standard error of measurement, the effect sizes (ES) were used to evaluate the sensitivity to change. ES values ≥0.2 were regarded as sensitive to change. Results: The overall performance times for the manipulations were significantly higher than the control condition, with mean differences of 4.40 s (weight – control, ES = 0.44) and 2.81 s (tyre – control, ES = 0.27). The overall performance time on the WMP test was judged as sensitive to change. For 8 of the 15 separate tasks on the WMP test, the tasks were judged as sensitive to change for at least one of the manipulations. Conclusion: The WMP test can detect change in mobility performance when wheelchair configurations are manipulated. https://www.medicaljournals.se/jrm/content/html/10.2340/16501977-2341
MULTIFILE
Introduction: A trauma resuscitation is dynamic and complex process in which failures could lead to serious adverse events. In several trauma centers, evaluation of trauma resuscitation is part of a hospital's quality assessment program. While video analysis is commonly used, some hospitals use live observations, mainly due to ethical and medicolegal concerns. The aim of this study was to compare the validity and reliability of video analysis and live observations to evaluate trauma resuscitations. Methods: In this prospective observational study, validity was assessed by comparing the observed adherence to 28 advanced trauma life support (ATLS) guideline related tasks by video analysis to life observations. Interobserver reliability was assessed by calculating the intra class coefficient of observed ATLS related tasks by live observations and video analysis. Results: Eleven simulated and thirteen real-life resuscitations were assessed. Overall, the percentage of observed ATLS related tasks performed during simulated resuscitations was 10.4% (P < 0.001) higher when the same resuscitations were analysed using video compared to live observations. During real-life resuscitations, 8.7% (p < 0.001) more ATLS related tasks were observed using video review compared to live observations. In absolute terms, a mean of 2.9 (during simulated resuscitations) respectively 2.5 (during actual resuscitations) ATLS-related tasks per resuscitation were not identified using live observers, that were observed through video analysis. The interobserver variability for observed ATLS related tasks was significantly higher using video analysis compared to live observations for both simulated (video analysis: ICC 0.97; 95% CI 0.97-0.98 vs. live observation: ICC 0.69; 95% CI 0.57-0.78) and real-life witnessed resuscitations (video analyse 0.99; 95% CI 0.99-1.00 vs live observers 0.86; 95% CI 0.83-0.89). Conclusion: Video analysis of trauma resuscitations may be more valid and reliable compared to evaluation by live observers. These outcomes may guide the debate to justify video review instead of live observations.
