Playing-Related Injuries and Posture Among Saxophonists
Bibliographic record
Abstract
AIMS: Playing-related injuries are common among musicians, but little is known about the nature of injuries and complaints in saxophone players. This research explored playing-related musculoskeletal disorders (PRMDs) and postures among saxophonists. The aims were to: 1) investigate the prevalence of PRMDs among saxophonists; 2) determine the most problematic body parts; and 3) identify their main postural habits and determine whether these postural habits may be related to the prevalence of pain in specific body parts. METHODS: An online questionnaire was used to collect data from professional and college-level saxophonists throughout North America. RESULTS: From 109 saxophonists who responded, 83 (76.15%) reported ever having a PRMD, 54 (50%) reported having a PRMD in the past year, 30 (27.52%) reported having a PRMD in the past month, and 23 (21.10%) reported having a PRMD in the past week. Top rated areas of pain were the right wrist, neck, mouth/jaw, and left wrist. The most common self-reported postural habits were forward head position and rounded upper back. Postures that correlated with higher pain ratings were rounded upper back and backward pelvic tilt. The rounded upper back, backward pelvic tilt, and excessive curve in low back postures were significantly correlated with the presence of PRMD problems in the right wrist. CONCLUSIONS: Saxophonists in this survey experienced a high prevalence of PRMDs, especially of the wrists, neck, and mouth/jaw. Certain postural habits may contribute to higher pain ratings or PRMD locations within saxophonists.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".