2 resultados para Social Evaluation

em Universidade Técnica de Lisboa


Relevância:

30.00% 30.00%

Publicador:

Resumo:

O presente relatório refere-se às atividades, do estágio inserido no Ramo de Aprofundamento de Competências Profissionais do Segundo Ciclo, desenvolvidas no âmbito da Reabilitação Psicomotora em Saúde Mental. Estas práticas de estágio foram realizadas no Centro de Atividades Ocupacionais (CAO) – Casa Do Sol e no Centro de Apoio Social do Pisão (CASP). A Intervenção no CAO e no CASP foi dirigida a indivíduos adultos com perturbação psiquiátrica, de ambos os sexos, residentes e/ou utentes destes centros. Esta intervenção foi constituída pelas seguintes quatro etapas: 1ª Observação informal das aulas de expressão corporal, dos momentos de refeições, dos ateliês de carpintaria, jardinagem, artes plásticas e culinária; 2ª Reabilitação / Intervenção psicomotora (duração aproximada de 6 meses); 3ª Avaliação formal de alguns casos utilizando instrumentos de avaliação nomeadamente a Bateria Psicomotora de Vítor da Fonseca (BPM) e a Escala do Comportamento Adaptativo Verão Portuguesa de Sofia Santos e Pedro Morato (ECAP). 4ª Elaboração e Ajustamento do Plano Terapêutico.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

Over the last few years, football entered in a period of accelerated access to large amount of match analysis data. Social networks have been adopted to reveal the structure and organization of the web of interactions, such as the players passing distribution tendencies. In this study we investigated the influence of ball possession characteristics in the competitive success of Spanish La Liga teams. The sample was composed by OPTA passing distribution raw data (n=269,055 passes) obtained from 380 matches involving all the 20 teams of the 2012/2013 season. Then, we generated 760 adjacency matrixes and their corresponding social networks using Node XL software. For each network we calculated three team performance measures to evaluate ball possession tendencies: graph density, average clustering and passing intensity. Three levels of competitive success were determined using two-step cluster analysis based on two input variables: the total points scored by each team and the scored per conceded goals ratio. Our analyses revealed significant differences between competitive performances on all the three team performance measures (p < .001). Bottom-ranked teams had less number of connected players (graph density) and triangulations (average clustering) than intermediate and top-ranked teams. However, all the three clusters diverged in terms of passing intensity, with top-ranked teams having higher number of passes per possession time, than intermediate and bottom-ranked teams. Finally, similarities and dissimilarities in team signatures of play between the 20 teams were displayed using Cohen’s effect size. In sum, findings suggest the competitive performance was influenced by the density and connectivity of the teams, mainly due to the way teams use their possession time to give intensity to their game.