Effects of order of resistance training exercises on muscle hypertrophy in young adult men
Bibliographic record
Abstract
The purpose of the present study was to analyze the effects of the order of resistance training (RT) exercises on hypertrophy in young adult men. Thirty-six young adult men (age, 21.9 ± 2.5 years; body mass, 72.6 ± 12.1 kg, height, 176.9 ± 7.4 cm; body mass index, 23.1 ± 3.3 kg/m2) were randomly assigned to 1 of 2 training groups that performed a 6-week RT program in either (i) a traditional approach starting with multi-joint (MJ) exercises followed by single-joint exercises (SJ) (MJ-SJ, n = 19) or (ii) in reverse order (SJ-MJ, n = 17). Muscle thickness of the biceps brachii and mid-thigh were assessed by ultrasound. Lean soft tissue (LST) was assessed by dual-energy X-ray absorptiometry. Both groups similarly increased (P < 0.05) biceps brachii thickness (MJ-SJ = +14.2%, SJ-MJ = +13.8%). Alternatively, only the MJ-SJ group presented an increase in mid-thigh thickness from pre- to post-training (MJ-SJ = +7.2%, SJ-MJ = +3.9%). Upper limb LSTs (MJ-SJ = +5.2%, SJ-MJ = +7.5%) were statistically similar between conditions, and a trend for significance (P = 0.07) was found for trunk LST (MJ-SJ = +7.2%, SJ-MJ = +1.7%). Nonsignificant pre- to post-training changes were observed for lower limb LSTs (MJ-SJ = +0.7%, SJ-MJ = +1.8%). Our data suggest that both sequences are effective for increasing muscle hypertrophy over a short-term RT period; there may be a potentially beneficial hypertrophic effect for the mid-thigh by performing exercises in a manner that progresses from MJ to SJ exercises.
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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) | 0.001 | 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) | 0.001 | 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".