Acute effects of lower trapezius activation exercises on shoulder muscle activation during overhead functional tasks in symptomatic and asymptomatic adults
Bibliographic record
Abstract
Introduction: Shoulder musculoskeletal disorders are associated with atypical kinematics and muscle activity. Exercises to activate weakened muscles may reduce pain and disability. The objectives of this study were to test the effectiveness of exercises for activating the lower trapezius and to compare changes in shoulder muscle activity during functional tasks before and after the exercises in symptomatic and asymptomatic groups. Methods: Eighteen adults, nine with subacromial pain syndrome and nine asymptomatic controls, participated in this study. A within-session repeated measures case-control design was employed. Participants performed overhead functional tasks before and after completing lower trapezius activation exercises. Electromyography (EMG) data of scapular muscles were captured during the tasks and exercises. One-way analysis of variance (ANOVA) compared muscle activations during the exercises. Paired t-test statistical parametric mapping assessed changes in muscle activity after the exercises. Results: = 1.38) , but this effect did not persist in either group. Discussion: The exercise protocol successfully increased lower trapezius activation immediately post-exercise, but the effects were short-lived. The findings suggest that while lower trapezius activation exercises can temporarily alter muscle activation, their efficacy for acute prevention or rehabilitation is limited. Further research is needed to explore the effects of longitudinal training programs on functional task performance.
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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".