Effect of Intention to Squat Explosively on Acute Countermovement Jump Performance
Bibliographic record
Abstract
ABSTRACT: O'Grady, MW, Young, WB, Behm, DG, and Talpey, SW. Effect of intention to squat explosively on acute countermovement jump performance. J Strength Cond Res 35(12): 3348-3354, 2021-The purpose of this study was to investigate the influence of squatting with the intention of moving the bar as fast as possible during the ascent phase on potentiating countermovement jump (CMJ) performance. Fourteen recreationally resistance-trained men (age = 22.1 ± 1.7 years, height = 179.9 ± 4.2 cm, body mass = 83.8 ± 6.6 kg) with a predicted 1 repetition maximum half-squat of 201.0 ± 27.8 kg participated in this study. Subjects performed 3 CMJs before and then 4 and 8 minutes after a squat conditioning activity (CA). Conditions were randomized. For 1 condition, the CA involved subjects performing 4 repetitions of the half-squat with a 5RM load in a controlled manner (CON) at a self-selected normal squatting tempo. In the other condition, subjects used the same number of repetitions and load; however, they were instructed to move the bar up as fast as possible during the concentric phase of the half-squat (VMAX). Half-squat peak force (N), peak power (W), peak velocity (m·s-1), and rate of force development (RFD) were measured for each CA using a force platform and linear position transducer. At 4 and 8 minutes post-CA, CMJ height, relative peak power, peak velocity, and peak force were also measured. Despite there being significant increases in the half-squat peak power, peak velocity and maximum RFD in the VMAX condition, neither condition significantly improved any post-CMJ variable. Some small improvements in jump height were observed in certain individuals after the VMAX condition, suggesting that an explosive half-squat CA may potentiate CMJ performance in certain individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".