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The profiling of university of Ljubljana students according to their motives for exercise participation

INTRODUCTION: The main research objective is the analysis of the grouping of the students of the University of Ljubljana, with respect to the intensity of different types of exercise participation motives, their gender, discipline and year of study, level of physical activity, status of physical edu...

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Detalles Bibliográficos
Autores principales: Cerar, Katja, Kondrič, Miran, Sindik, Joško
Formato: Online Artículo Texto
Lenguaje:English
Publicado: De Gruyter 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5329774/
https://www.ncbi.nlm.nih.gov/pubmed/28289470
http://dx.doi.org/10.1515/sjph-2017-0014
Descripción
Sumario:INTRODUCTION: The main research objective is the analysis of the grouping of the students of the University of Ljubljana, with respect to the intensity of different types of exercise participation motives, their gender, discipline and year of study, level of physical activity, status of physical education class, organization of physical activities during study, and place of residence. METHODS: Data were collected using personal data sheets during enrolling students at the University of Ljubljana. Students completed The Exercise Motivations Inventory (EMI-2), with additional data about sociodemographic parameters. RESULTS: The results reveal that the students could be grouped in three distinctive clusters, which can be very clearly explained in terms of the prevalence of exercise participation motives in general. The students grouped in the first cluster have the lowest average values (means) in all exercise participation motives. The students grouped in the second cluster have the profile with moderate means in all exercise participation motives, while the students grouped in the third cluster have the profile with the highest means in all exercise participation motives. CONCLUSIONS: The results indicate overall higher motivation for physical activity in men. All the sub-samples are different in their relevant features used in clustering (e.g., male students are dominant in life sciences, etc.), which provide a guide both for the explanation of the results obtained and for practical implications.