Claudino João Gustavo, Cronin John, Mezêncio Bruno, McMaster Daniel Travis, McGuigan Michael, Tricoli Valmor, Amadio Alberto Carlos, Serrão Julio Cerca
University of São Paulo, School of Physical Education and Sport-Laboratory of Biomechanics, Brazil; Auckland University of Technology, Sport Performance Research Institute, New Zealand.
Auckland University of Technology, Sport Performance Research Institute, New Zealand; Edith Cowan University, School of Exercise and Health Sciences, Australia.
J Sci Med Sport. 2017 Apr;20(4):397-402. doi: 10.1016/j.jsams.2016.08.011. Epub 2016 Aug 25.
The primary objective of this meta-analysis was to compare countermovement jump (CMJ) performance in studies that reported the highest value as opposed to average value for the purposes of monitoring neuromuscular status (i.e., fatigue and supercompensation). The secondary aim was to determine the sensitivity of the dependent variables.
Systematic review with meta-analysis.
The meta-analysis was conducted on the highest or average of a number of CMJ variables. Multiple literature searches were undertaken in Pubmed, Scopus, and Web of Science to identify articles utilizing CMJ to monitor training status. Effect sizes (ES) with 95% confidence interval (95% CI) were calculated using the mean and standard deviation of the pre- and post-testing data. The coefficient of variation (CV) with 95% CI was also calculated to assess the level of instability of each variable. Heterogeneity was assessed using a random-effects model.
151 articles were included providing a total of 531 ESs for the meta-analyses; 85.4% of articles used highest CMJ height, 13.2% used average and 1.3% used both when reporting changes in CMJ performance. Based on the meta-analysis, average CMJ height was more sensitive than highest CMJ height in detecting CMJ fatigue and supercompensation. Furthermore, other CMJ variables such as peak power, mean power, peak velocity, peak force, mean impulse, and power were sensitive in tracking the supercompensation effects of training.
The average CMJ height was more sensitive than highest CMJ height in monitoring neuromuscular status; however, further investigation is needed to determine the sensitivity of other CMJ performance variables.
本荟萃分析的主要目的是比较在报告最高值而非平均值以监测神经肌肉状态(即疲劳和超量恢复)的研究中,反向纵跳(CMJ)的表现。次要目的是确定因变量的敏感性。
系统评价与荟萃分析。
对多个CMJ变量的最高值或平均值进行荟萃分析。在PubMed、Scopus和Web of Science中进行了多次文献检索,以识别利用CMJ监测训练状态的文章。使用测试前后数据的均值和标准差计算效应量(ES)及其95%置信区间(95%CI)。还计算了95%CI的变异系数(CV),以评估每个变量的不稳定程度。使用随机效应模型评估异质性。
纳入151篇文章,为荟萃分析提供了总共531个效应量;85.4%的文章在报告CMJ表现变化时使用了最高CMJ高度,13.2%使用了平均值,1.3%同时使用了两者。基于荟萃分析,平均CMJ高度在检测CMJ疲劳和超量恢复方面比最高CMJ高度更敏感。此外,其他CMJ变量,如峰值功率、平均功率、峰值速度、峰值力、平均冲量和功率,在跟踪训练的超量恢复效应方面很敏感。
在监测神经肌肉状态方面,平均CMJ高度比最高CMJ高度更敏感;然而,需要进一步研究以确定其他CMJ表现变量的敏感性。