Comparison of the Hang High Pull and Loaded Jump Squat for the Development of Vertical Jump and Isometric Force-Time Characteristics
Bibliographic record
Abstract
Oranchuk, DJ, Robinson, TL, Switaj, ZJ, and Drinkwater, EJ. Comparison of the hang high pull and loaded jump squat for the development of vertical jump and isometric force-time characteristics. J Strength Cond Res 33(1): 17-24, 2019-Weightlifting movements have high skill demands and require expert coaching. Loaded jumps have a comparably lower skill demand but may be similarly effective for improving explosive performance. The purpose of this study was to compare vertical jump performance, isometric force, and rate of force development (RFD) after a 10-week intervention using the hang high pull (hang-pull) or trap-bar jump squat (jump-squat). Eighteen National Collegiate Athletic Association Division II swimmers (8 males, 10 females) with at least 1 year of resistance training experience volunteered to participate. Testing included the squat jump (SJ), countermovement jump, and the isometric midthigh pull (IMTP). Vertical ground reaction forces were analyzed to obtain jump height and relative peak power. Relative peak force, peak RFD, and relative force at 5 time bands were obtained from the IMTP. Subjects were randomly assigned to either a hang pull (n = 9) or jump-squat (n = 9) training group and completed a 10-week, volume-equated, periodized training program. Although there was a significant main effect of training for both groups, no statistically significant between-group differences were found (p ≥ 0.17) for any of the dependent variables. However, medium effect sizes in favor of the jump-squat training group were seen in SJ height (d = 0.56) and SJ peak power (d = 0.69). Loaded jumps seem equally effective as weightlifting derivatives for improving lower-body power in experienced athletes. Because loaded jumps require less skill and less coaching expertise than weightlifting, loaded jumps should be considered where coaching complex movements is difficult.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".