A Multilayer Network Model for Motor Competence from the View of the Science of Complexity: A Multilayer Network Model for Motor Competence: P. F. Ribeiro Bandeira et al.

Motor competence is related to a large number of correlates of different natures, forming together a system with flexible parts that are synergically and cooperatively connected to produce a wide range of motor outcomes that cannot be explained from a predetermined linear view or a unique mechanism....

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Publicado en:Sports Medicine Vol. 55; no. 2; pp. 245 - 255
Autores principales: Ribeiro Bandeira, Paulo Felipe, Estevan, Isaac, Duncan, Michael, Lenoir, Matthieu, Lemos, Luís, Romo-Perez, Vicente, Valentini, Nadia, Martins, Clarice
Formato: pictorial tables/charts Journal Article
Publicado: Springer Nature Feb2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2025
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      pub: Springer Nature
      place: New York, New York
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        atl: A Multilayer Network Model for Motor Competence from the View of the Science of Complexity: A Multilayer Network Model for Motor Competence: P. F. Ribeiro Bandeira et al.
      aug:
        au:
          Ribeiro Bandeira, Paulo Felipe
          Estevan, Isaac
          Duncan, Michael
          Lenoir, Matthieu
          Lemos, Luís
          Romo-Perez, Vicente
          Valentini, Nadia
          Martins, Clarice
        affil: https://ror.org/05y26ar20 Department of Physical Education, Universidade Regional do Cariri, Crato, Brazil
      sug:
        subj:
          Motor Skills
          Conceptual Framework
          Models, Theoretical
          Metaphor
          Science
          Mathematics
          Self Regulation
          Motivation
          Obesity
      ab: Motor competence is related to a large number of correlates of different natures, forming together a system with flexible parts that are synergically and cooperatively connected to produce a wide range of motor outcomes that cannot be explained from a predetermined linear view or a unique mechanism. The diversity of interacting correlates, the various connections between them, and the fast changes between assessments at different time points are clear barriers to the study of motor competence. In this manuscript, we present a multilayer framework that accounts for the theoretical background and the potential mathematical procedures necessary to represent the non-linear, complex, and dynamic relationships between several underlying correlates that emerge as a motor competence network. Exploring motor competence from a new perspective that could be operationalized through multilayer networks seems promising, and allows more accurate inspection and representation of its topology and dynamics. This new perspective might also improve the understanding of motor competence structure and functionality over the developmental course. The use of the proposed approach could open up new horizons for the broad literature comprising motor competence.
      pubtype: Academic Journal
      doctype:
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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