Effects of Low- vs. High-Load Resistance Training on Muscle Strength and Hypertrophy in Well-Trained Men
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Bibliographic record
Abstract
The purpose of this study was to compare the effect of low- versus high-load resistance training (RT) on muscular adaptations in well-trained subjects. Eighteen young men experienced in RT were matched according to baseline strength and then randomly assigned to 1 of 2 experimental groups: a low-load RT routine (LL) where 25-35 repetitions were performed per set per exercise (n = 9) or a high-load RT routine (HL) where 8-12 repetitions were performed per set per exercise (n = 9). During each session, subjects in both groups performed 3 sets of 7 different exercises representing all major muscles. Training was performed 3 times per week on nonconsecutive days, for a total of 8 weeks. Both HL and LL conditions produced significant increases in thickness of the elbow flexors (5.3 vs. 8.6%, respectively), elbow extensors (6.0 vs. 5.2%, respectively), and quadriceps femoris (9.3 vs. 9.5%, respectively), with no significant differences noted between groups. Improvements in back squat strength were significantly greater for HL compared with LL (19.6 vs. 8.8%, respectively), and there was a trend for greater increases in 1 repetition maximum (1RM) bench press (6.5 vs. 2.0%, respectively). Upper body muscle endurance (assessed by the bench press at 50% 1RM to failure) improved to a greater extent in LL compared with HL (16.6 vs. -1.2%, respectively). These findings indicate that both HL and LL training to failure can elicit significant increases in muscle hypertrophy among well-trained young men; however, HL training is superior for maximizing strength adaptations.
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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 | 0.000 |
| 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) | 0.000 | 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 it