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青少年运动员的训练负荷、睡眠时间与日常幸福感及恢复指标之间的关系

Relationships Between Training Load, Sleep Duration, and Daily Well-Being and Recovery Measures in Youth Athletes.

作者信息

Sawczuk Thomas, Jones Ben, Scantlebury Sean, Till Kevin

机构信息

1 Leeds Beckett University and Queen Ethelburga's Collegiate.

2 Leeds Beckett University, Queen Ethelburga's Collegiate, Yorkshire Carnegie Rugby Club , and The Rugby Football League.

出版信息

Pediatr Exerc Sci. 2018 Aug 1;30(3):345-352. doi: 10.1123/pes.2017-0190. Epub 2018 Feb 24.

Abstract

PURPOSE

To assess the relationships between training load, sleep duration, and 3 daily well-being, recovery, and fatigue measures in youth athletes.

METHODS

Fifty-two youth athletes completed 3 maximal countermovement jumps (CMJs), a daily well-being questionnaire (DWB), the perceived recovery status scale (PRS), and provided details on their previous day's training loads (training) and self-reported sleep duration (sleep) on 4 weekdays over a 7-week period. Partial correlations, linear mixed models, and magnitude-based inferences were used to assess the relationships between the predictor variables (training and sleep) and the dependent variables (CMJ, DWB, and PRS).

RESULTS

There was no relationship between CMJ and training (r = -.09; ±.06) or sleep (r = .01; ±.06). The DWB was correlated with sleep (r = .28; ±.05, small), but not training (r = -.05; ±.06). The PRS was correlated with training (r = -.23; ±.05, small), but not sleep (r = .12; ±.06). The DWB was sensitive to low sleep (d = -0.33; ±0.11) relative to moderate; PRS was sensitive to high (d = -0.36; ±0.11) and low (d = 0.29; ±0.17) training relative to moderate.

CONCLUSIONS

The PRS is a simple tool to monitor the training response, but DWB may provide a greater understanding of the athlete's overall well-being. The CMJ was not associated with the training or sleep response in this population.

摘要

目的

评估青少年运动员的训练负荷、睡眠时间与三项每日幸福感、恢复情况及疲劳指标之间的关系。

方法

52名青少年运动员在7周内的4个工作日完成了3次最大纵跳(CMJ)、一份每日幸福感问卷(DWB)、感知恢复状态量表(PRS),并提供了前一天的训练负荷(训练)和自我报告的睡眠时间(睡眠)细节。采用偏相关、线性混合模型和基于量级的推断来评估预测变量(训练和睡眠)与因变量(CMJ、DWB和PRS)之间的关系。

结果

CMJ与训练(r = -0.09;±0.06)或睡眠(r = 0.01;±0.06)之间无关联。DWB与睡眠相关(r = 0.28;±0.05,小效应),但与训练无关(r = -0.05;±0.06)。PRS与训练相关(r = -0.23;±0.05,小效应),但与睡眠无关(r = 0.12;±0.06)。相对于中等睡眠,DWB对低睡眠敏感(d = -0.33;±0.11);相对于中等训练,PRS对高训练(d = -0.36;±0.11)和低训练(d = 0.29;±0.17)敏感。

结论

PRS是监测训练反应的一个简单工具,但DWB可能能更深入了解运动员的整体幸福感。在该人群中,CMJ与训练或睡眠反应无关。

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