Ribeiro Bandeira Paulo Felipe, Estevan Isaac, Duncan Michael, Lenoir Matthieu, Lemos Luís, Romo-Perez Vicente, Valentini Nadia, Martins Clarice
Department of Physical Education, Universidade Regional do Cariri, Crato, Brazil.
AFIPS Research Group; Department of Teaching of Physical Education, Arts and Music, University of Valencia, Valencia, Spain.
Sports Med. 2025 Feb;55(2):245-254. doi: 10.1007/s40279-024-02164-4. Epub 2024 Dec 27.
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.
运动能力与大量不同性质的相关因素有关，共同构成一个具有灵活部分的系统，这些部分通过协同和合作的方式相互连接，以产生广泛的运动结果，而这些结果无法从预先确定的线性观点或单一机制来解释。相互作用的相关因素的多样性、它们之间的各种联系以及不同时间点评估之间的快速变化，显然是运动能力研究的障碍。在本手稿中，我们提出了一个多层框架，该框架阐述了作为运动能力网络出现的几个潜在相关因素之间的非线性、复杂和动态关系所需的理论背景和潜在数学程序。从一个可以通过多层网络实施的新视角探索运动能力似乎很有前景，并且能够更准确地检查和表示其拓扑结构和动态变化。这个新视角还可能增进对运动能力在整个发展过程中的结构和功能的理解。所提出方法的使用可能为包含运动能力的广泛文献开辟新的视野。
