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- All Subjects: Elementary School
- All Subjects: mass spring model
- Genre: Academic theses
- Creators: Amazeen, Eric
- Creators: Amazeen, Polemnia
- Resource Type: Text
Description
Background: Childhood obesity is one of the most serious public health concerns in the United States and has been associated with low levels of physical activity. Schools are ideal physical activity promotion sites but school physical activity opportunities have decreased due the increased focus on academic performance. Before-school programs provide a good opportunity for children to engage in physical activity as well as improve their readiness to learn. Purpose: The purpose of this study was to examine the effect of a before-school running/walking club on children's physical activity and on-task behavior. Methods: Participants were third and fourth grade children from two schools in the Southwestern United States who participated in a before-school running/walking club that met two times each week. The study employed a two-phase experimental design with an initial baseline phase and an alternating treatments phase. Physical activity was monitored using pedometers and on-task behavior was assessed through systematic observation. Data analysis included visual analysis, descriptive statistics, as well as multilevel modeling. Results: Children accumulated substantial amounts of physical activity within the before-school program (School A: 1731 steps, 10:02 MVPA minutes; School B: 1502 steps, 8:30 MVPA minutes) and, on average, did not compensate by decreasing their physical activity during the rest of the school day. Further, on-task behavior was significantly higher on days the children attended the before-school program than on days they did not (School A=15.78%, pseudo-R2=.34 [strong effect]; School B=14.26%, pseudo-R2=.22 [moderate effect]). Discussion: Results provide evidence for the positive impact of before-school programs on children's physical activity and on-task behavior. Such programs do not take time away from academics and may be an attractive option for schools.
ContributorsStylianou, Michalis (Author) / Kulinna, Pamela H. (Thesis advisor) / Van Der Mars, Hans (Committee member) / Amazeen, Eric (Committee member) / Adams, Marc (Committee member) / Mahar, Matthew T. (Committee member) / Arizona State University (Publisher)
Created2014
Description
With improvements in technology, intensive longitudinal studies that permit the investigation of daily and weekly cycles in behavior have increased exponentially over the past few decades. Traditionally, when data have been collected on two variables over time, multivariate time series approaches that remove trends, cycles, and serial dependency have been used. These analyses permit the study of the relationship between random shocks (perturbations) in the presumed causal series and changes in the outcome series, but do not permit the study of the relationships between cycles. Liu and West (2016) proposed a multilevel approach that permitted the study of potential between subject relationships between features of the cycles in two series (e.g., amplitude). However, I show that the application of the Liu and West approach is restricted to a small set of features and types of relationships between the series. Several authors (e.g., Boker & Graham, 1998) proposed a connected mass-spring model that appears to permit modeling of more general cyclic relationships. I showed that the undamped connected mass-spring model is also limited and may be unidentified. To test the severity of the restrictions of the motion trajectories producible by the undamped connected mass-spring model I mathematically derived their connection to the force equations of the undamped connected mass-spring system. The mathematical solution describes the domain of the trajectory pairs that are producible by the undamped connected mass-spring model. The set of producible trajectory pairs is highly restricted, and this restriction sets major limitations on the application of the connected mass-spring model to psychological data. I used a simulation to demonstrate that even if a pair of psychological time-varying variables behaved exactly like two masses in an undamped connected mass-spring system, the connected mass-spring model would not yield adequate parameter estimates. My simulation probed the performance of the connected mass-spring model as a function of several aspects of data quality including number of subjects, series length, sampling rate relative to the cycle, and measurement error in the data. The findings can be extended to damped and nonlinear connected mass-spring systems.
ContributorsMartynova, Elena (M.A.) (Author) / West, Stephen G. (Thesis advisor) / Amazeen, Polemnia (Committee member) / Tein, Jenn-Yun (Committee member) / Arizona State University (Publisher)
Created2019