Configuración teórica de la motivación de salud desde la teoría de la autodeterminación

El estudio de la motivación humana es un constructo altamente complejo y con una gran variabilidad de enfoques. La teoría de la autodeterminación (TAD) ha demostrado una relativa efectividad y consistencia en muchos aspectos relacionados con la salud, como por ejemplo el ejercicio físico, la alimentación, el sueño, el bienestar psicológico o el consumo de tabaco. Las investigaciones muestran que la motivación autodeterminada se corresponde con la motivación intrínseca y en cambio la motivación extrínseca y sus formas de regulación pueden corresponderse con comportamiento no autodeterminados, pudiendo llegar hasta la desmotivación. En este trabajo se formula una construcción teórica sobre este modelo, introduciendo la percepción de riesgo (PR) y la vulnerabilidad percibida (VP) como elementos que pueden variar el sentido final de la motivación e incluso mejorar alguna de sus regulaciones extrínsecas y la desmotivación. Una de las posibilidades teóricas que sugerimos para intentar neutralizar los tipos no autodeterminados es procurar aumentar la PR y la VP de la persona, ya que estando estas dos variables altas, la probabilidad de que la desmotivación aparezca se reduce significativamente, y las acciones forzadas de la regulación externa y la regulación introyectada pueden amortiguarse y aumentar la internalización lo que podría favorecer los comportamientos de salud.

Effects of a training program to enhance autonomy supportive behaviors among youth soccer coaches

This study aimed to evaluate the prevalence and implementation of a training emphasizing the use of autonomy supportive coaching behaviors among youth soccer coaches in game-play situations as well as evaluating its effects on motivational processes among athletes. Participants included youth sport soccer coaches and their intact teams. Coaches received a series of autonomy-supportive coaching training interventions based on successful programs in general and physical education (Reeve, Jang, Carrell, Jeon & Barch, 2004; Cheon, Reeve & Moon, 2012). Athletes completed questionnaires to assess perceived autonomy support, basic need satisfaction, and motivation (Harris & Watson, 2011). Observations indicated coaches were not able to significantly modify their behaviors, yet reflectively reported modest implementation of autonomy supportive behaviors. Coaches believed the training influenced their coaching style/philosophy in regards to the coach-athlete relationship and communication styles, emphasizing choice and rationales. Continued research is needed to enhance use of autonomy supportive behaviors with volunteer coaches in a youth sport environment.

Hand gesture recognition based on morphologic features

Comunicación presentada en el IX Simposium Nacional de Reconocimiento de Formas y Análisis de Imágenes, Benicàssim, Mayo, 2001.

Detecting implicit expressions of affect in text using EmotiNet and its extensions

In the past years, an important volume of research in Natural Language Processing has concentrated on the development of automatic systems to deal with affect in text. The different approaches considered dealt mostly with explicit expressions of emotion, at word level. Nevertheless, expressions of emotion are often implicit, inferrable from situations that have an affective meaning. Dealing with this phenomenon requires automatic systems to have “knowledge” on the situation, and the concepts it describes and their interaction, to be able to “judge” it, in the same manner as a person would. This necessity motivated us to develop the EmotiNet knowledge base — a resource for the detection of emotion from text based on commonsense knowledge on concepts, their interaction and their affective consequence. In this article, we briefly present the process undergone to build EmotiNet and subsequently propose methods to extend the knowledge it contains. We further on analyse the performance of implicit affect detection using this resource. We compare the results obtained with EmotiNet to the use of alternative methods for affect detection. Following the evaluations, we conclude that the structure and content of EmotiNet are appropriate to address the automatic treatment of implicitly expressed affect, that the knowledge it contains can be easily extended and that overall, methods employing EmotiNet obtain better results than traditional emotion detection approaches.

Capacidad predictiva de la autoeficacia académica sobre las dimensiones del autoconcepto en una muestra de adolescentes chilenos

El objetivo de este estudio fue analizar la capacidad predictiva de la autoeficacia académica sobre las dimensiones del autoconcepto en una muestra de 860 estudiantes chilenos. El análisis de regresión logística reveló que la autoeficacia académica fue un predictor positivo y significativo de las escalas académicas (Matemáticas, Verbal y Académica General), no académicas (Habilidades Físicas, Apariencia Física, Relaciones con el Sexo Opuesto, Relaciones con el Mismo Sexo, Relación con los Padres, Sinceridad- Veracidad), y de la escala de Autoestima, excepto de la escala de Estabilidad Emocional. Esta relación de predicción fue de mayor magnitud con las escalas académicas y autoestima.

A connectionist computational method for face recognition

In this work, a modified version of the elastic bunch graph matching (EBGM) algorithm for face recognition is introduced. First, faces are detected by using a fuzzy skin detector based on the RGB color space. Then, the fiducial points for the facial graph are extracted automatically by adjusting a grid of points to the result of an edge detector. After that, the position of the nodes, their relation with their neighbors and their Gabor jets are calculated in order to obtain the feature vector defining each face. A self-organizing map (SOM) framework is shown afterwards. Thus, the calculation of the winning neuron and the recognition process are performed by using a similarity function that takes into account both the geometric and texture information of the facial graph. The set of experiments carried out for our SOM-EBGM method shows the accuracy of our proposal when compared with other state-of the-art methods.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

The Gaia-ESO Survey: Empirical determination of the precision of stellar radial velocities and projected rotation velocities

Context. The Gaia-ESO Survey (GES) is a large public spectroscopic survey at the European Southern Observatory Very Large Telescope. Aims. A key aim is to provide precise radial velocities (RVs) and projected equatorial velocities (vsini) for representative samples of Galactic stars, which will complement information obtained by the Gaia astrometry satellite. Methods. We present an analysis to empirically quantify the size and distribution of uncertainties in RV and vsini using spectra from repeated exposures of the same stars. Results. We show that the uncertainties vary as simple scaling functions of signal-to-noise ratio (S/N) and vsini, that the uncertainties become larger with increasing photospheric temperature, but that the dependence on stellar gravity, metallicity and age is weak. The underlying uncertainty distributions have extended tails that are better represented by Student’s t-distributions than by normal distributions. Conclusions. Parametrised results are provided, which enable estimates of the RV precision for almost all GES measurements, and estimates of the vsini precision for stars in young clusters, as a function of S/N, vsini and stellar temperature. The precision of individual high S/N GES RV measurements is 0.22–0.26 km s-1, dependent on instrumental configuration.

Diseño y validación de una escala de autoevaluación de competencias digitales para estudiantes de Pedagogía

Este trabajo presenta el proceso de validación de una Escala de Autoevaluación de competencias digitales para estudiantes de Pedagogía. La estructura del instrumento contempla cinco dimensiones: Pedagógica - Social, Ética y Legal - Técnica - Gestión Escolar y Desarrollo Profesional. El procedimiento consideró la validación de contenido, validación de constructo a través del Análisis Factorial y la determinación de fiabilidad a través del alfa de Cronbach. La escala se aplicó a una muestra de 161 estudiantes de Pedagogía de la Universidad del Bío-Bío (Chile) que habían comenzado la actividad de práctica profesional. El proceso desarrollado permitió dar validez científica al instrumento diseñado.

Self-Description Questionnaire II (versión breve): evidencia de fiabilidad y validez en una muestra de adolescentes chilenos

El objetivo de este estudio fue analizar la fiabilidad y validez de las puntuaciones de la versión breve del Self-Description Questionnaire II (SDQ-II-S) en población chilena. La muestra se compuso de 1255 adolescentes chilenos, con un rango de edad de 13 a 17 años (M = 15.10; DT = 1.30). El análisis factorial confirmatorio corroboró la estructura original de 11 factores correlacionados del SDQ-II-S. La multidimensionalidad del cuestionario también fue avalada por la pequeña magnitud de las correlaciones entre los 11 factores (M = 0.26). Los coeficientes alfa de Cronbach variaron desde 0.70 hasta 0.84, y se destacó una adecuada fiabilidad. Para profundizar en el análisis de la validez de constructo del SDQ-II-S, se relacionaron las puntuaciones de las diferentes escalas con puntuaciones en medidas de ansiedad (Inventario de Ansiedad Estado-Rasgo) y autoeficacia (Escala de Autoeficacia Percibida Específica de Situaciones Académicas). Los resultados pusieron de manifiesto que estos cuestionarios permiten analizar constructos diferenciados aunque relacionados. Los datos de este trabajo destacan que el SDQ-II-S presenta adecuadas propiedades psicométricas en población chilena, contrarrestando las carencias existentes en lo que respecta a la evaluación del autoconcepto, y resaltan interesantes aplicaciones tanto en el ámbito aplicado como en el de la investigación.