Biomechanical risk factors for rotator cuff syndrome in high-risk occupations: A prospective study protocol
Bibliographic record
Abstract
BACKGROUND: Rotator cuff syndrome (RCS) is the most common upper limb musculoskeletal disorder worldwide. RCS negatively impacts quality of life and comes with high costs to the individual and society through time loss of work or healthcare usage. Identifying modifiable risk factors for RCS is a critical avenue for exploration to improve prevention and treatment of RCS. OBJECTIVE: The overarching goal of this research is to explore the connection between shoulder kinematics and RCS in high-risk occupations and determine if pre-injury shoulder kinematics during a standardized overhead reaching motion are a risk factor for symptomatic RCS. METHODS: A prospective cohort design will be used to assess 292 individuals who work in high-risk occupations, such as construction, farming, and healthcare. Workers without any shoulder pain or disorders will be asked to attend an in-laboratory baseline testing session. First participants will complete questionnaires about their baseline symptoms, personal characteristics, and work exposures. They will then perform a standardized functional reaching task while their shoulder movement is tracked with optical motion capture. Participants will be surveyed every 3 months for two years; individuals with any indications of shoulder symptoms that develop during the study period will be further assessed with clinical impingement tests. Logistic regression and survival analyses will be performed to determine if scapular kinematics pre-injury, combined with several individual and work-related factors, are a risk factor for development of RCS. PROPOSED RESULTS: These findings will provide empirical evidence to clarify the contribution of biomechanics to injury development. Specifically, it is expected that scapular kinematics at the baseline assessment will be a risk factor for the development of RCS. CONCLUSIONS: This research represents a crucial step for understanding shoulder musculoskeletal health. This information is foundational for development of innovative, evidence-based treatment and prevention strategies.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.008 |
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".