Active Stiffness and Strength in People With Unilateral Anterior Shoulder Instability: A Bilateral Comparison
Bibliographic record
Abstract
CONTEXT: Active muscle stiffness might protect the unstable shoulder from recurrent dislocation. OBJECTIVE: To compare strength and active stiffness in participants with unilateral anterior shoulder instability and to examine the relationship between active stiffness and functional ability. DESIGN: Cross-sectional study. SETTING: University research laboratory. PATIENTS OR OTHER PARTICIPANTS: Participants included 16 males (age range, 16-40 years; height = 179.4 ± 6.1 cm; mass = 79.1 ± 6.8 kg) with 2 or more episodes of unilateral traumatic anterior shoulder instability. MAIN OUTCOME MEASURE(S): Active stiffness and maximal voluntary strength were measured bilaterally in participants. In addition, quality of life, function, and perceived instability were measured using the Western Ontario Stability Index, American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form, and Single Alpha Numeric Evaluation, respectively. RESULTS: We found less horizontal adduction strength (t(15) = -4.092, P = .001) and less stiffness at 30% (t(14) = -3.796, P = .002) and 50% (t(12) = -2.341, P = .04) maximal voluntary strength in the unstable than stable shoulder. Active stiffness was not correlated with quality of life, function, or perceived instability (r range, 0.0-0.25; P > .05). CONCLUSIONS: The observed reduction in stiffness in the unstable shoulder warrants inclusion of exercises in the rehabilitation program to protect the joint from perturbations that might lead to dislocation. The lack of association between active stiffness and quality of life, function, or perceived instability might indicate that stiffness plays a less direct role in shoulder stability.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".