Energy expenditure and dietary intake in professional football players in the Dutch Premier League: Implications for nutritional counselling

ABSTRACT

Selecting effective dietary strategies for professional football players requires comprehensive information on their energy expenditure (EE) and dietary intake. This observational study aimed to assess EE and dietary intake over a 14-day period in a representative group (n = 41) of professional football players playing in the Dutch Premier League (Eredivisie). Daily EE, as assessed by doubly labelled water, was 13.8 ± 1.5 MJ/day, representing a physical activity level (PAL) of 1.75 ± 0.13. Weighted mean energy intake (EI), as assessed by three face-to-face 24-h recalls, was 11.1 ± 2.9 MJ/day, indicating 18 ± 15% underreporting of EI. Daily EI was higher on match days (13.1 ± 4.1 MJ) compared with training (11.1 ± 3.4 MJ; P < 0.01) and rest days (10.5 ± 3.1 MJ; P < 0.001). Daily carbohydrate intake was significantly higher during match days (5.1 ± 1.7 g/kg body mass (BM)) compared with training (3.9 ± 1.5 g/kg BM; P < 0.001) and rest days (3.7 ± 1.4 g/kg BM; P < 0.001). Weighted mean protein intake was 1.7 ± 0.5 g/kg BM. Daytime distribution of protein intake was skewed, with lowest intakes at breakfast and highest at dinner. In conclusion, daily EE and PAL of professional football players are modest. Daily carbohydrate intake should be increased to maximize performance and recovery. Daily protein intake seems more than adequate, but could be distributed more evenly throughout the day.     

Promoting historical contextualisation in classrooms: an observational study

The aim of this observational study is to explore how history teachers promote historical contextualisation in their lessons. Historical contextualisation is the ability to situate phenomena and individuals’ actions in the context of time, historical location, long-term developments, or specific events to give meaning to these phenomena and actions. Using the Framework for Analysing the Teaching of Historical Contextualisation (FAT-HC), five trained raters observed eight history teachers twice. To further analyse the observation scores, the FAT-HC items were divided into eight categories while distinguishing between items that demonstrate historical contextualisation and items focusing on engaging students in historical contextualisation processes. The results indicate that the teachers in the sample did not explicitly promote historical contextualisation in their lessons. No teacher obtained a mean FAT-HC score >2.00 on a four-point scale. The teachers mainly demonstrated historical contextualisation, while engaging students in historical contextualisation processes was observed far less often. The findings can be used to help teachers formulate domain-specific instruction to promote students’ ability to perform historical contextualisation.     

Promoting historical contextualization: the development and testing of a pedagogy

The aim of this explorative study was to develop and test a pedagogy aimed at promoting students’ ability to perform historical contextualization. Teaching historical contextualization was conceptualized in terms of four pedagogical design principles: (1) making students aware of the consequences of a present-oriented perspective when examining the past, (2) enhancing the reconstruction of a historical context, (3) enhancing the use of the historical context to explain historical phenomena and (4) enhancing historical empathy. The effectiveness of these principles was explored in a lesson unit focusing on the seventeenth and eighteenth centuries. In a quasi-experimental pre-test–post-test design with experimental and control conditions, the effects of the pedagogy on 15- and 16-year-old students’ ability to perform historical contextualization were examined (n = 131). The results indicated that students in the experimental condition significantly improved their ability to perform historical contextualization compared to students in the control condition. These findings could be used to help teachers and other educational professionals design and implement historical contextualization tasks and instructions.     

A Comparison of Item-Selection Methods for Adaptive Tests with Content Constraints

In test assembly, a fundamental difference exists between algorithms that select a test sequentially or simultaneously. Sequential assembly allows us to optimize an objective function at the examinee's ability estimate, such as the test information function in computerized adaptive testing. But it leads to the non-trivial problem of how to realize a set of content constraints on the test—a problem more naturally solved by a simultaneous item-selection method. Three main item-selection methods in adaptive testing offer solutions to this dilemma. The spiraling method moves item selection across categories of items in the pool proportionally to the numbers needed from them. Item selection by the weighted-deviations method (WDM) and the shadow test approach (STA) is based on projections of the future consequences of selecting an item. These two methods differ in that the former calculates a projection of a weighted sum of the attributes of the eventual test and the latter a projection of the test itself. The pros and cons of these methods are analyzed. An empirical comparison between the WDM and STA was conducted for an adaptive version of the Law School Admission Test (LSAT), which showed equally good item-exposure rates but violations of some of the constraints and larger bias and inaccuracy of the ability estimator for the WDM.     

A Strategy for Optimizing Item-Pool Management

Item-pool management requires a balancing act between the input of new items into the pool and the output of tests assembled from it. A strategy for optimizing item-pool management is presented that is based on the idea of a periodic update of an optimal blueprint for the item pool to tune item production to test assembly. A simulation study with scenarios involving different levels of quality of the initial item pool, item writing, and management for a previous item pool from the Law School Admission Test (LSAT) showed that good item-pool management had about the same main effects on the item-writing costs and the number of feasible tests as good item writing, but the two factors showed strong interaction effects.     

Identifying students with dyslexia in higher education

An increasing number of students with dyslexia enter higher education. As a result, there is a growing need for standardized diagnosis. Previous research has suggested that a small number of tests may suffice to reliably assess students with dyslexia, but these studies were based on post hoc discriminant analysis, which tends to overestimate the percentage of systematic variance, and were limited to the English language (and the Anglo-Saxon education system). Therefore, we repeated the research in a non-English language (Dutch) and we selected variables on the basis of a prediction analysis. The results of our study confirm that it is not necessary to administer a wide range of tests to diagnose dyslexia in (young) adults. Three tests sufficed: word reading, word spelling and phonological awareness, in line with the proposal that higher education students with dyslexia continue to have specific problems with reading and writing. We also show that a traditional postdiction analysis selects more variables of importance than the prediction analysis. However, these extra variables explain study-specific variance and do not result in more predictive power of the model.     

The Effects of Ignoring a Level in Multilevel Analysis

Ignoring a level can have a substantial impact on the conclusions of a multilevel analysis. For intercept-only models and for balanced data, we derive these effects analytically. For more complex random intercept models or for unbalanced data, a simulation study is performed. Most important effects concern estimates and corresponding standard errors of the variance parameters at adjacent levels and of the coefficients of the predictors at the ignored and bordering levels. Therefore, we conclude that if the researcher is interested in a specific level, she/he should account for both the upper and lower level. Conclusions are illustrated using empirical data from educational research.     

Group incentives for teachers and their effects on student learning: a systematic review of theory and evidence

The effects of teachers’ group incentives on student achievement are examined by reviewing theoretical arguments and empirical studies published between 1990 and 2011. Studies from developing countries reported positive effects of group incentives on student test scores. However, experimental studies from developed countries reported insignificant effects. Some of the evidence appears to show a positive association between small group size of teachers and the effectiveness of group incentives. Still, it is uncertain whether the key to successful group incentives in teaching emanates from the incentive size, teacher group size, teacher intrinsic motivation, or type of incentive (rank type vs. non-rank type). Furthermore, most studies show that individual teacher incentives have positive effects unlike studies on group incentives. However, there is a lack of comparative studies of group incentives and individual incentives. We conclude that current empirical evidence has unclear policy implications and recommend additional experimental research.     

Some Conceptual Issues in Observed‐Score Equating

In spite of all of the technical progress in observed‐score equating, several of the more conceptual aspects of the process still are not well understood. As a result, the equating literature struggles with rather complex criteria of equating, lack of a test‐theoretic foundation, confusing terminology, and ad hoc analyses. A return to Lord's foundational criterion of equity of equating, a derivation of the true equating transformation from it, and mainstream statistical treatment of the problem of estimating the transformation for various data‐collection designs exist as a solution to the problem.     

Bias Corrections for Standardized Effect Size Estimates Used With Single-Subject Experimental Designs

A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect sizes are adjusted using Hedges’ small sample bias correction. Next, the within-subject standard deviation is estimated by a 2-level model per study or by using a regression model with the subjects identified using dummy predictor variables. The effect sizes are corrected using an iterative raw data parametric bootstrap procedure. The results indicate that the first and last approach succeed in reducing the bias of the fixed effects estimates. Given the difference in complexity, we recommend the first approach.