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      The Effects of Cluster-Set and Traditional-Set Postactivation Potentiation Protocols on Vertical Jump Performance

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          Abstract

          Purpose: To compare the effects of 2 postactivation potentiation (PAP) protocols using traditional-set or cluster-set configurations on countermovement jump performance. Methods: Twenty-six male basketball players completed 3 testing sessions separated by 72 hours. On the first session, subjects performed barbell jump squats with progressively heavier loads to determine their individual optimum power load. On the second and third sessions, subjects completed 2 PAP protocols in a randomized order: 3 sets of 6 repetitions of jump squats using optimum power load performed with either a traditional-set (no interrepetition rest) or a cluster-set (20-s rest every 2 repetitions) configuration. After a warm-up, countermovement jump height was measured using a force platform before, 30 seconds, 4 minutes, and 8 minutes after completing the PAP protocols. The following kinetic variables were also analyzed and compared: relative impulse, ground reaction force, eccentric displacement, and vertical leg-spring stiffness. Results: Across both conditions, subjects jumped lower at post 30 seconds by 1.21 cm, and higher in post 4 minutes by 2.21 cm, and in post 8 minutes by 2.60 cm compared with baseline. However, subjects jumped higher in the cluster condition by 0.71 cm (95% confidence interval, 0.37 to 1.05 cm) in post 30 seconds, 1.33 cm (95% confidence interval, 1.02 to 1.65 cm) in post 4 minute, and 1.64 cm (95% confidence interval, 1.41 to 1.88 cm) in post 8 minutes. The superior countermovement jump performance was associated with enhanced kinetic data. Conclusions: Both protocols induced PAP responses in vertical jump performance using jump squats at optimum power load. However, the cluster-set configuration led to superior performance across all time points, likely due to reduced muscular fatigue.

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          Most cited references34

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          The new statistics: why and how.

          We need to make substantial changes to how we conduct research. First, in response to heightened concern that our published research literature is incomplete and untrustworthy, we need new requirements to ensure research integrity. These include prespecification of studies whenever possible, avoidance of selection and other inappropriate data-analytic practices, complete reporting, and encouragement of replication. Second, in response to renewed recognition of the severe flaws of null-hypothesis significance testing (NHST), we need to shift from reliance on NHST to estimation and other preferred techniques. The new statistics refers to recommended practices, including estimation based on effect sizes, confidence intervals, and meta-analysis. The techniques are not new, but adopting them widely would be new for many researchers, as well as highly beneficial. This article explains why the new statistics are important and offers guidance for their use. It describes an eight-step new-statistics strategy for research with integrity, which starts with formulation of research questions in estimation terms, has no place for NHST, and is aimed at building a cumulative quantitative discipline.
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            Measures of Reliability in Sports Medicine and Science

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              Meta-analysis of postactivation potentiation and power: effects of conditioning activity, volume, gender, rest periods, and training status.

              There is no clear agreement regarding the ideal combination of factors needed to optimize postactivation potentiation (PAP) after a conditioning activity. Therefore, a meta-analysis was conducted to evaluate the effects of training status, volume, rest period length, conditioning activity, and gender on power augmentation due to PAP. A total of 141 effect sizes (ESs) for muscular power were obtained from a total of 32 primary studies, which met our criteria of investigating the effects of a heavy preconditioning activity on power in randomized human trials. The mean overall ES for muscle power was 0.38 after a conditioning activity (p 85%) 0.31 (p 10 minutes (0.02) (p < 0.05). Significant differences were found between untrained 0.14 and athletes 0.81 and between trained 0.29 and athletes. The primary findings of this study were that a conditioning activity augmented power output, and these effects increased with training experience, but did not differ significantly between genders. Moreover, potentiation was optimal after multiple (vs. single) sets, performed at moderate intensities, and using moderate rest periods lengths (7-10 minutes).
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                Author and article information

                Journal
                International Journal of Sports Physiology and Performance
                Human Kinetics
                1555-0265
                1555-0273
                April 1 2020
                April 1 2020
                : 15
                : 4
                : 464-469
                Article
                10.1123/ijspp.2019-0186
                fda53dd7-65ac-4ae1-b96a-5e6c6209d2ea
                © 2020
                History

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