Individualized Endurance Training Based on Recovery and Training Status in Recreational Runners

MEDICINE & SCIENCE IN SPORTS & EXERCISE(2022)

引用 5|浏览0
暂无评分
摘要
Purpose Long-term development of endurance performance requires a proper balance between strain and recovery. Because responses and adaptations to training are highly individual, this study examined whether individually adjusted endurance training based on recovery and training status would lead to greater adaptations compared with a predefined program. Methods Recreational runners were divided into predefined (PD; n = 14) or individualized (IND; n = 16) training groups. In IND, the training load was decreased, maintained, or increased twice a week based on nocturnal heart rate variability, perceived recovery, and heart rate-running speed index. Both groups performed 3-wk preparatory, 6-wk volume, and 6-wk interval periods. Incremental treadmill tests and 10-km running tests were performed before the preparatory period (T-0) and after the preparatory (T-1), volume (T-2), and interval (T-3) periods. The magnitude of training adaptations was defined based on the coefficient of variation between T-0 and T-1 tests (high >2x, low <0.5x). Results Both groups improved (P < 0.01) their maximal treadmill speed and 10-km time from T-1 to T-3. The change in the 10-km time was greater in IND compared with PD (-6.2% +/- 2.8% vs -2.9% +/- 2.4%, P = 0.002). In addition, IND had more high responders (50% vs 29%) and fewer low responders (0% vs 21%) compared with PD in the change of maximal treadmill speed and 10-km performance (81% vs 23% and 13% vs 23%), respectively. Conclusions PD and IND induced positive training adaptations, but the individualized training seemed more beneficial in endurance performance. Moreover, IND increased the likelihood of high response and decreased the occurrence of low response to endurance training.
更多
查看译文
关键词
ENDURANCE PERFORMANCE, RUNNING PERFORMANCE, HEART RATE VARIABILITY, PERCEIVED RECOVERY, PERIODIZATION
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要