Feedback, necesidades psicológicas básicas y vitalidad subjetiva en futbolistas estudiantes de las preparatorias la UANL

Dado que el deporte representa un contexto de gran valor para el desarrollo de la madurez individual y social de los adolescentes, lo cual probablemente influirá en su desarrollo, maduración y en su comportamiento, así como en su forma de entender las relaciones sociales. De aquí la influencia que un entrenador pueda tener sobre sus jóvenes jugadores, ya que tiene un papel de gran relevancia, pues puede repercutir de forma significativa en los patrones de comportamiento, en las cogniciones y en los afectos que los mismos vayan a desarrollar (Graham, 2008). Una tarea fundamental del entrenador es proporcionar retroalimentación o feedback a los atletas durante el aprendizaje de las habilidades motoras. El entrenador debe de ser capaz de generar las condiciones del medio en donde se perciba la legitimidad de su retroalimentación al proporcionar el feedback a los atletas, y generar las condiciones en donde se satisfagan las necesidades psicológicas básicas, lo cual propiciará un sentimiento de vitalidad y energía, de acuerdo con la Teoría de la autodeterminación (Deci y Rian, 1985, 2000, 2002 y 2008). En el marco de la Teoría de la autodeterminación (Deci y Rian, 1985, 2000, 2002 y 2008) y la Teoría de de las necesidades psicológicas básicas (Deci y Ryan 1985, 2000), esta tesis doctoral tuvo como objetivo estudiar el modelo representado por los factores sociales (cantidad de feedback correctivo, percepción legítima), los factores personales (necesidades psicológicas básicas: autonomía, competencia y socialización) y el bienestar (vitalidad subjetiva) propuesto en esta misma secuencia, en concordancia con el modelo de Vallerand (1997). Para los fines del presente trabajo se consideró una muestra de 377 estudiantes del nivel medio superior que forman parte de los equipos representativos de fútbol soccer de las preparatorias de la UANL, durante el período comprendido Agosto-Diciembre 2012. El muestreo fue de tipo no probabilístico y por conveniencia. La muestra estuvo compuesta por futbolistas de edades comprendidas entre los 15 y 20 años (M = 16.46, DT = 1.077). El error muestral fue del 4%. En el estudio se utilizaron distintas escalas para medir las variables involucradas en el estudio, como son: la Subescala de la Cantidad del Feedback Correctivo y la Subescala de la Percepción Legítima, a partir de la Escala del Feedback Correctivo; la Escala de Necesidad de Autonomía (NAS), la Escala de Percepción de Competencia del Cuestionario de Motivación Intrínseca (IMI), y la Escala de Necesidad de Relación (NRS); y la Escala de Vitalidad Subjetiva. Entre los resultados más destacados se encontró que existen relaciones positivas y altamente significativas entre todas las variables del estudio; la cantidad de feedback correctivo ofrecido por el entrenador actuó como un predictor positivo de la percepción legítima y, éste a su vez, operó como un predictor positivo de la satisfacción de las necesidades psicológicas básicas; la cantidad de feedback correctivo ofrecido por el entrenador actuó como un predictor positivo de la percepción legítima y, este a su vez, como un predictor positivo de la vitalidad subjetiva; la cantidad de feedback correctivo ofrecido por el entrenador actuó como predictor positivo de la satisfacción de las necesidades psicológicas básicas y, éste a su vez, fue un predictor positivo de la vitalidad subjetiva; la percepción legítima percibida por el jugador actuó como un predictor positivo de la satisfacción de las necesidades psicológicas básicas y, éste a su vez, como predictor positivo de la vitalidad subjetiva. Además, el modelo general nos condujo a que la cantidad de feedback correctivo ofrecido por el entrenador el cual actuó como predictor positivo de la percepción legítima y, este a su vez, predijo la satisfacción de las necesidades psicológicas básicas, la cual a su vez, 15 predijo la vitalidad subjetiva de los jugadores. Los resultados mostraron la puesta a prueba de los diferentes modelos generados a través de la combinación de las distintas variables, las cuales están en línea con la secuencia teórica. Se confirmaron adecuados índices de ajuste en cada uno de los modelos hipotetizado. El análisis de la mediación de las necesidades psicológicas básicas se realizó siguiendo a Holmbeck (1997). Los resultados mostraron que la satisfacción de las necesidades psicológicas básicas es un mediador total entre la cantidad de feedback correctivo y la vitalidad subjetiva. Por otro lado, se encontró que las necesidades psicológicas básicas no fueron un mediador entre la percepción legítima y la vitalidad subjetiva. En conclusión, se tiene que el entrenador es quien genera las condiciones del contexto ya sean de promoción de la autonomía o de control, además, de él depende generar las condiciones que promuevan la percepción de legitimidad en los atletas, mismas que probablemente concebirán en los deportistas la satisfacción de las necesidades psicológicas básicas, que permitan percibir una sensación de bienestar o malestar en los atletas.

Cross-correlations between weather variables in Australia

The information on climate variations is essential for the research of many subjects, such as the performance of buildings and agricultural production. However, recorded meteorological data are often incomplete. There may be a limited number of locations recorded, while the number of recorded climatic variables and the time intervals can also be inadequate. Therefore, the hourly data of key weather parameters as required by many building simulation programmes are typically not readily available. To overcome this gap in measured information, several empirical methods and weather data generators have been developed. They generally employ statistical analysis techniques to model the variations of individual climatic variables, while the possible interactions between different weather parameters are largely ignored. Based on a statistical analysis of 10 years historical hourly climatic data over all capital cities in Australia, this paper reports on the finding of strong correlations between several specific weather variables. It is found that there are strong linear correlations between the hourly variations of global solar irradiation (GSI) and dry bulb temperature (DBT), and between the hourly variations of DBT and relative humidity (RH). With an increase in GSI, DBT would generally increase, while the RH tends to decrease. However, no such a clear correlation can be found between the DBT and atmospheric pressure (P), and between the DBT and wind speed. These findings will be useful for the research and practice in building performance simulation.

Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

Using Trauma Injury Severity Score (TRISS) variables to predict length of hospital stay following trauma in New Zealand

Aim – To develop and assess the predictive capabilities of a statistical model that relates routinely collected Trauma Injury Severity Score (TRISS) variables to length of hospital stay (LOS) in survivors of traumatic injury. Method – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until discharge from Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Cubic-root transformed LOS was analysed using two-level mixed-effects regression models. Results – 1498 eligible patients were identified, 1446 (97%) injured from a blunt mechanism and 52 (3%) from a penetrating mechanism. For blunt mechanism trauma, 1096 (76%) were male, average age was 37 years (range: 15-94 years), and LOS and TRISS score information was available for 1362 patients. Spearman’s correlation and the median absolute prediction error between LOS and the original TRISS model was ρ=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ρ=0.38 and 6.0 days, respectively. Insufficient data were available for the analysis of penetrating mechanism models. Conclusions – Neither the original TRISS model nor the refined model has sufficient ability to accurately or reliably predict LOS. Additional predictor variables for LOS and other indicators for morbidity need to be considered.

A comparative study of manufacturing practices and performance variables

The reported study was conducted to compare and contrast current manufacturing practices between two countries, Australia and Malaysia, and identify the practices that significantly influence their manufacturing performances. The results are based on data collected from surveys using a standard questionnaire in both countries. Evidence indicates that product quality and reliability is the main competitive factor for manufacturers. Maintaining a supplier rating system and regularly updating it with field failure and warranty data and making use of product data management are found to be effective manufacturing practices. In terms of the investigated manufacturing performance, Australian manufacturers are marginally ahead of their Malaysian counterparts. However, Malaysian manufacturers came out ahead on most dimensions of advanced quality and manufacturing practices, particularly in the adoption of product data management, effective supply chains and relationships with suppliers and customers.

Generating rules with predicates, terms and variables from the pruned neural networks

Artificial neural networks (ANN) have demonstrated good predictive performance in a wide range of applications. They are, however, not considered sufficient for knowledge representation because of their inability to represent the reasoning process succinctly. This paper proposes a novel methodology Gyan that represents the knowledge of a trained network in the form of restricted first-order predicate rules. The empirical results demonstrate that an equivalent symbolic interpretation in the form of rules with predicates, terms and variables can be derived describing the overall behaviour of the trained ANN with improved comprehensibility while maintaining the accuracy and fidelity of the propositional rules.

Distribution profiles of key weather variables in Australian capital cities : implications for energy efficient building design

Local climate is a critical element in the design of energy efficient buildings. In this paper, ten years of historical weather data in Australia's eight capital cities were profiled and analysed to characterize the variations of climatic variables in Australia. The method of descriptive statistics was employed. Either the pattern of cumulative distribution and/or the profile of percentage distribution are presented. It was found that although weather variables vary with different locations, there is often a good, nearly linear relation between a weather variable and its cumulative percentage for the majority of middle part of the cumulative curves. By comparing the slopes of these distribution profiles, it may be possible to determine the relative range of changes of the particular weather variables for a given city. The implications of these distribution profiles of key weather variables on energy efficient building design are also discussed.

Important omitted spatial variables in safety models: Understanding contributing crash causes at intersections

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causation—rests upon the pursuit of numerous lines of inquiry. The research community has focused on analytical methods development (negative binomial specifications, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might think of different lines of inquiry in terms of ‘low lying fruit’—areas of inquiry that might provide significant improvements in understanding crash causation. It is the contention of this research that omitted variable bias caused by the exclusion of important variables is an important line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant ability to better understand contributing factors to crashes. This study—believed to represent a unique contribution to the safety literature—develops and examines the role of a sizeable set of spatial variables in intersection crash occurrence. In addition to commonly considered traffic and geometric variables, examined spatial factors include local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools. The results indicate that inclusion of these factors results in significant improvement in model explanatory power, and the results also generally agree with expectation. The research illuminates the importance of spatial variables in safety research and also the negative consequences of their omissions.