Theory and practice in sport psychology and motor behaviour needs to be constrained by integrative modelling of brain and behaviour

Because of advances in technology, the non-invasive study of the human brain has enhanced the knowledge base within the neurosciences, resulting in an increased impact on the psychological study of human behaviour. We argue that application of this knowledge base should be considered in theoretical modelling within sport psychology and motor behaviour alongside existing ideas. We propose that interventions founded on current theoretical and empirical understanding in both psychology and the neurosciences may ultimately lead to greater benefits for athletes during practice and performance. As vehicles for exploring the arguments of a greater integration of psychology and neurosciences research, imagery and perception-action within the sport psychology and motor behaviour domains will serve as exemplars. Current neuroscience evidence will be discussed in relation to theoretical developments; the implications for sport scientists will be considered.     

CensusAtSchool 2000

This article covers the development of an ambitious Internet‐based project to conduct a simple census of the schoolchildren of England and Wales linked to the 2001 UK National Census.     

The Use of Incorrect Informative Priors in the Estimation of MIMIC Model Parameters with Small Sample Sizes

Recently, advancements in Bayesian structural equation modeling (SEM), particularly software developments, have allowed researchers to more easily employ it in data analysis. With the potential for greater use, come opportunities to apply Bayesian SEM in a wider array of situations, including for small sample size problems. Effective use of Bayseian estimation hinges on selection of appropriate prior distributions for model parameters. Researchers have suggested that informative priors may be useful with small samples, presuming that the mean of the prior is accurate with respect to the population mean. The purpose of this simulation study was to examine model parameter estimation for the Multiple Indicator Multiple Cause model when an informative prior distribution had an incorrect mean. Results demonstrated that the use of incorrect informative priors with somewhat larger variance than is typical, yields more accurate parameter estimates than do naïve priors, or maximum likelihood estimation. Implications for practice are discussed.     

Patterns in the Initial Teaching Assignments of Secondary English Teachers: Implications for Teacher Agency and Retention

This study examined the teaching assignments of English teachers in 13 Mid-Atlantic high schools across five states. Data on the experience levels of 175 English teachers teaching 246 classes and surveys from 85 teacher participants were collected. Findings reveal that major agency-thwarting challenges face new English teachers: They typically are assigned to teach the students who need the most assistance, do not have their own classrooms and believe that teacher tracking occurs in their schools. Results suggest that in order to increase teacher agency, retention, and student learning, we must shift the working conditions, rhetoric, and culture around new teachers.     

A Comparison of Estimation Techniques for IRT Models With Small Samples

The usefulness of item response theory (IRT) models depends, in large part, on the accuracy of item and person parameter estimates. For the standard 3 parameter logistic model, for example, these parameters include the item parameters of difficulty, discrimination, and pseudo-chance, as well as the person ability parameter. Several factors impact traditional marginal maximum likelihood (ML) estimation of IRT model parameters, including sample size, with smaller samples generally being associated with lower parameter estimation accuracy, and inflated standard errors for the estimates. Given this deleterious impact of small samples on IRT model performance, use of these techniques with low-incidence populations, where it might prove to be particularly useful, estimation becomes difficult, especially with more complex models. Recently, a Pairwise estimation method for Rasch model parameters has been suggested for use with missing data, and may also hold promise for parameter estimation with small samples. This simulation study compared item difficulty parameter estimation accuracy of ML with the Pairwise approach to ascertain the benefits of this latter method. The results support the use of the Pairwise method with small samples, particularly for obtaining item location estimates.     

Assessment of balance among adolescent track and field athletes

Track and field events place different demands on athletes and may have an effect on balance. This study investigated the effects of event specialty, gender, and leg dominance on balance among adolescent track and field athletes. Forty healthy adolescent track and field athletes (male = 23, female = 17) categorised into three different groups (sprinter = 20, distance runners = 13, throwers = 7) had their single leg static balance measured with the eyes open and the eyes closed using an AMTI force platform. Dependent variables included average displacement (cm) of the centre of pressure (COP) in the anterior/posterior direction and medial/lateral directions, the average velocity of the COP (cm/s) and the 95% ellipse area (cm²). Variables were analysed using a 3 (event specialty) × 2 (gender) × 2 (leg) ANOVA with repeated measures on the leg variable (p < 0.05). There was a significant difference (p < 0.05) in the average displacement of the COP in the medial/lateral direction for both the eyes open and closed condition, with the non-dominant leg demonstrating greater displacement than the dominant leg. This might increase the risk of injury for the non-dominant leg, but additional data should be collected and analysed on both dynamic balance and performance.