Shoulder Retractor Strengthening Exercise to Minimize Rhomboid Muscle Activity and Subacromial Impingement
Bibliographic record
Abstract
PURPOSE: We investigated the best position for shoulder retractor strengthening exercise to maximize middle trapezius activity and minimize rhomboid major activity. Although both trapezius and rhomboids are scapular retractors, rhomboids also act as downward rotators of the scapula, which can worsen subacromial impingement. METHODS: Twelve healthy participants (age 30 [SD 6] y) with no history of shoulder pain were recruited for this study, which used fine-wire electromyography to examine maximal muscle activation of the middle trapezius and rhomboid major muscle fibres in four different positions: with the shoulder in 90° abduction with elbow completely extended and (1) shoulder internal rotation, (2) shoulder neutral rotation, (3) shoulder external rotation, and (4) rowing (shoulder neutral rotation and elbow flexed 90°). The ratio of trapezius to rhomboid muscles was compared with Wilcoxon signed-rank tests. RESULTS: Muscle activation ratio during shoulder retraction exercise was significantly lower by 22% (i.e., rhomboid was more active than middle trapezius) when performed with the shoulder in rowing position (elbow flexed) than with the shoulder in external rotation (elbow extended) position (p=0.031). All four positions produced coactivation of trapezius and rhomboids. DISCUSSION: Rowing position may not be the best position for shoulder retractor strengthening in patients with impingement syndrome. The preferable position for maximizing middle trapezius activity and minimizing rhomboid activity may be shoulder external rotation with elbow extended.
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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) | 0.001 | 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".