“Knees Out” or “Knees In”? Volitional Lateral vs. Medial Hip Rotation During Barbell Squats
Bibliographic record
Abstract
ABSTRACT: Chiu, LZF. "Knees out" or "Knees in"? Volitional lateral versus medial hip rotation during barbell squats. J Strength Cond Res 38(3): 435-443, 2024-Medial or lateral hip rotation may be present during barbell squats, which could affect the hip frontal and transverse plane moments. Male (n = 14) and female (n = 18) subjects performed squats using their normal technique and with volitional medial and lateral hip rotation. Hip net joint moments (NJM) were calculated from 3-dimensional motion capture and force platform measurements. Statistical significance was set for omnibus tests (α = 0.05) and Bonferroni's corrected for pairwise comparisons (αt-test = 0.0056). Normal squats required hip extensor, adductor, and lateral rotator NJM. Lateral rotation squats had smaller hip extensor (p = 0.002) and lateral rotator (p < 0.001) NJM and larger hip adductor (p < 0.001) NJM than normal squats. Medial rotation squats had smaller hip extensor (p = 0.002) and adductor (p < 0.001) NJM and larger hip lateral rotator (p < 0.001) NJM than normal squats. These differences exceeded the minimum effects worth detecting. As gluteus maximus exerts hip extensor and lateral rotator moments, and the adductor magnus exerts hip extensor and adductor moments, these muscles combined would be required to meet these hip demands, supporting previous research that has established these muscles as the primary contributors to the hip extensor NJM. Lateral rotation squats reduce hip lateral rotator and increase hip adductor NJM, which may be hypothesized as preferentially loading adductor magnus. Medial rotation squats increase hip lateral rotator and decrease hip adductor NJM; therefore, this variant may shift loading to the gluteus maximus.
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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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".