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Back Squat Post-Activation Performance Enhancement on Parameters of a 3-Min All-Out Running Test: A Complex Network Analysis Perspective
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This study investigated the impact of post-activation performance enhancement (PAPE) on the parameters of the 3 min all-out test (3MT) in non-motorized tethered running, applying the concept of complex networks for integrative analysis. Ten recreational runners underwent anthropometric assessments, a one-repetition maximum test (1RM), a running ramp test, and 3MT trials under both PAPE and CONTROL conditions across five separate sessions. The conditioning activity consisted of two sets of six back squats at 60% 1RM. For each scenario, complex network graphs were constructed and analyzed using Degree, Eigenvector, PageRank, and Betweenness centrality metrics. In the PAPE condition, anthropometric parameters and parameters related to aerobic efficiency exhibited greater centrality, ranking among the top five nodes. Paired Student’s t-tests (p ≤ 0.05) revealed significant differences between conditions for end power (EP-W) (CONTROL: 407.83 ± 119.30 vs. PAPE: 539.33 ± 177.10 (effect size d = −0.84)) and end power relativized by body mass (rEP-W·kg−1) (CONTROL: 5.38 ± 1.70 vs. PAPE: 6.91 ± 2.00 (effect size d = −0.76)), as well as for the absolute and relative values of peak output power, mean output power, peak force, and mean force. These findings suggest that PAPE alters the configuration of complex networks, increasing network density, and may enhance neuromuscular function and running economy. Moreover, PAPE appears to modulate both aerobic and anaerobic contributions to performance. These results highlight the importance of network-based approaches for advancing exercise science and providing individualized strategies for training and performance optimization.
Title: Back Squat Post-Activation Performance Enhancement on Parameters of a 3-Min All-Out Running Test: A Complex Network Analysis Perspective
Description:
This study investigated the impact of post-activation performance enhancement (PAPE) on the parameters of the 3 min all-out test (3MT) in non-motorized tethered running, applying the concept of complex networks for integrative analysis.
Ten recreational runners underwent anthropometric assessments, a one-repetition maximum test (1RM), a running ramp test, and 3MT trials under both PAPE and CONTROL conditions across five separate sessions.
The conditioning activity consisted of two sets of six back squats at 60% 1RM.
For each scenario, complex network graphs were constructed and analyzed using Degree, Eigenvector, PageRank, and Betweenness centrality metrics.
In the PAPE condition, anthropometric parameters and parameters related to aerobic efficiency exhibited greater centrality, ranking among the top five nodes.
Paired Student’s t-tests (p ≤ 0.
05) revealed significant differences between conditions for end power (EP-W) (CONTROL: 407.
83 ± 119.
30 vs.
PAPE: 539.
33 ± 177.
10 (effect size d = −0.
84)) and end power relativized by body mass (rEP-W·kg−1) (CONTROL: 5.
38 ± 1.
70 vs.
PAPE: 6.
91 ± 2.
00 (effect size d = −0.
76)), as well as for the absolute and relative values of peak output power, mean output power, peak force, and mean force.
These findings suggest that PAPE alters the configuration of complex networks, increasing network density, and may enhance neuromuscular function and running economy.
Moreover, PAPE appears to modulate both aerobic and anaerobic contributions to performance.
These results highlight the importance of network-based approaches for advancing exercise science and providing individualized strategies for training and performance optimization.
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