Promoting Interpersonal Relationships through Elbow Tag, a Traditional Sporting Game. A Multidimensional Approach

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Abstract

The aim of this research was to study from a multidimensional point of view (decisional, relational and energetic) the interpersonal relationships established by girls and boys in the traditional sport game of Elbow Tag. Scientific evidence has shown that Traditional Sport Games (TSG) trigger different effects on male and female genders in relation to emotional experiences, decision-making, conflicts and motor relationships. Despite the fact that these dimensions are intertwined, there are hardly any studies that interpret motor behaviors holistically, i.e., taking a multidimensional (360°) view of these dimensions. For this study, a quasi-experimental design was used and a type III design was applied, inspired by the observational methodology N/P/M. A total of 147 university students participated (M = 19.6, SD = 2.3): 47 girls (31.97%) and 100 boys (68.02%). A mixed ‘ad hoc’ registration system was designed with acceptable margins of data quality. Cross-tabulations, classification trees and T-patterns analysis were applied. The results indicated that social interactions between girls and boys in a mixed group were unequal. This difference was mainly due to decision-making (sub-role variable), which has much greater predictive power than the energetic variables (MV and steps).

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Manuel Ato, Juan J. López, Ana Benavente (2013)

En este trabajo se elabora un marco conceptual y se desarrollan unos principios básicos para fundamentar un sistema de clasificación de los diseños de investigación más usuales en psicología basado en tres estrategias (manipulativa, asociativa y descriptiva) de donde emanan varios tipos de estudios, tres para la estrategia manipulativa (experimentales, cuasiexperimentales y de caso único), tres para la asociativa (comparativos, predictivos y explicativos) y dos para la descriptiva (observacionales y selectivos).

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Discovering hidden time patterns in behavior: T-patterns and their detection.

Brianna Magnusson (2000)

This article deals with the definition and detection of particular kinds of temporal patterns in behavior, which are sometimes obvious or well known, but other times difficult to detect, either directly or with standard statistical methods. Characteristics of well-known behavior patterns were abstracted and combined in order to define a scale-independent, hierarchical time pattern type, called a T-pattern. A corresponding detection algorithm was developed and implemented in a computer program, called Theme. The proposed pattern typology and detection algorithm are based on the definition and detection of a particular relationship between pairs of events in a time series, called a critical interval relation. The proposed bottom-up, level-by-level (or breadth-first) search algorithm is based on a binary tree of such relations. The algorithm first detects simpler patterns. Then, more complex and complete patterns evolve through the connection of simpler ones, pattern completeness competition, and pattern selection. Interindividual T-patterns in a quarter-hour interaction between two children are presented, showing that complex hidden T-patterns may be found by Theme in such behavioral streams. Finally, implications for studies of complexity, self-organization, and dynamic patterns are discussed.