Effects of Lower Extremity Alignment During Barbell Squat Training on Muscle Volumes
Bibliographic record
Abstract
ABSTRACT: Chiu, LZF, and Fry, AC. Effects of lower extremity alignment during barbell squat training on muscle volumes. J Strength Cond Res 39(10): 1053-1061, 2025-Squat training increases monoarticular hip and knee extensor muscle size. Biomechanical studies demonstrate that hip muscle demands are different for squats performed with "knees in" vs. "knees out" tibiofemoral alignment. To: (a) determine whether these differences in hip muscle demands influence hip extensor muscle size adaptations and (b) examine the safety of these squat variations, training with "knees in" vs. "knees out" squats was compared. Eleven healthy women ("knees in": n = 6) completed 6 weeks' barbell squat training. Fat-free muscle volumes were reconstructed from magnetic resonance imaging, and self-reported knee health was assessed using the Knee Injury and Osteoarthritis Outcome Score (KOOS). Both groups increased lower-body strength ( p < 0.001) and vasti muscles' volumes ( p < 0.02). However, no muscles with a hip extensor action increased in size ( p > 0.05). Surprisingly, gluteus maximus volume decreased in the "knees in" group ( p = 0.045). Smaller gluteus maximus may indicate muscle atrophy or water loss concomitant to glycogen depletion. As the former indicates reduced and the latter increased muscle loading, "knees in" squat seems to affect gluteus maximus loading, although the direction of this change is unclear. The 5 KOOS outcomes were not different between groups, nor did they change over time ( p > 0.05). Both squat variations are tolerable for novice women trainees, and a longer training intervention may be required to establish differential hip extensor muscle adaptations between variations.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".