Effect of Conservative Interventions for Musculoskeletal Disorders in Preprofessional and Professional Dancers: A Systematic Review
Bibliographic record
Abstract
Background: Preprofessional and professional dancers are among the athletes who sustain the most musculoskeletal disorders. In recent years, conservative treatment and preventive measures have been investigated in this population. However, no systematic review regarding their effectiveness has been conducted. Hypothesis/Purpose: The aim of this systematic review was to locate, appraise and synthesize the available information on conservative interventions currently used for treating and preventing MSK disorders and their effect on pain and function in preprofessional and professional dancers. Study design: Systematic review. Methods: A systematic literature search was conducted using PubMed, CINHAL, ERIC, SportDiscus and Psychology and behavioral science collection. Prospective and retrospective cohort studies, as well as randomized and non-randomized controlled trials investigating conservative interventions for musculoskeletal disorders in preprofessional and professional dancers were included in this study. The main outcome measures included pain intensity, function, and performance. All included studies were evaluated for risk of bias using the Downs and Black checklist. Results: Eight studies were included in the review. These studies included ballet and contemporary dancers, as well as professional and preprofessional dancers. In total, the studies included 312 dancers, 108 male and 204 female. Studies had a risk of bias that ranged from poor (8/28) to good (21/28) on the Downs and Black checklist. The conservative interventions used included customized toe caps, dry-needling, motor imagery, and strength and conditioning programs. The use of customized toe caps, motor imagery and strength and conditioning programs had promising results regarding pain and function in dancers. Conclusion: In order to reach a solid conclusion, more quality studies are needed. The addition of control groups to studies, as well as multimodal interventions should be considered. Level of Evidence: I.
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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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".