How different types of meditation can enhance athletic performance depending on the specific sport skills

(Wie verschiedene Arten von Meditation die sportliche Leistung in Abhängigkeit von den jeweiligen sportlichen Fähigkeiten steigern können)

Long-term engagement in mindfulness meditation has been found to be effective in achieving optimal athletic performance through decreasing the level of anxiety, ruminative thinking, and enhancing the experience of flow. Besides long-term training effects, the past years have seen an increasing interest in the impact of single bouts of meditation on cognition. In particular, focused attention meditation (FAM) and open monitoring meditation (OMM) instantly bias cognitive-control styles toward "more" (i.e., serial processing) versus "less" (i.e., parallel processing) top-down control, respectively. In this opinion article, we argue that the distinction between FAM and OMM is particularly effective when considering different types of sports. We speculate that FAM may enhance performance in closed-skills sports (i.e., archery, gymnastic), based on serial processing, in which the environmental is predictable and the response is "self-paced." In contrast, we consider OMM to promote performance in open-skills sports (i.e., soccer, sailboarding), based on parallel processing, in which the environmental contingencies determine an "externally-paced" response. We conclude that successful meditation-based intervention on athletic performance requires a theoretically guided selection of the best-suited techniques specific to certain types of sports.
© Copyright 2017 Journal of Cognitive Enhancement. Springer. Alle Rechte vorbehalten.

Bibliographische Detailangaben
Schlagworte:
Notationen:Naturwissenschaften und Technik Biowissenschaften und Sportmedizin Trainingswissenschaft
Tagging:Mindfulness
Veröffentlicht in:Journal of Cognitive Enhancement
Sprache:Englisch
Veröffentlicht: 2017
Online-Zugang:https://link.springer.com/article/10.1007/s41465-017-0018-3
Jahrgang:1
Heft:2
Seiten:122-126
Dokumentenarten:Artikel
Level:hoch