Occupational Health Problems of Violists: An Epidemiological Study
Bibliographic record
Abstract
This research is the first known large-scale, instrument-specific, epidemiological study on the occupational health problems of violists. An online survey was developed based on a biopsychosocial framework to assess demographics, pain, musculoskeletal and non-musculoskeletal problems, music performance anxiety, and musician identity. Additionally, this is the first study known to investigate violists' perceptions and attitudes regarding viola jokes and negative stereotypes associated with viola players and their effects on violists' occupational health. Validated tools used to measure violists' health problems included the short-form McGill Pain Questionnaire (SF-MPQ) and the Musician's Identity Measurement Scale (MIMS). Results: This survey yielded a cohort N = 324 that was diverse in age, education, and professional involvement. The overall prevalence for violists that experienced musculoskeletal pain in the past year was 79%. For violists in pain, 51% reported being reluctant to inform others of their playing-related pain. In the past year, 89% of violists experienced music performance anxiety. 49% of violists reported having negative thoughts about viola jokes, with 23% indicating they experience music performance anxiety because of viola jokes. The prevalence rates for non-musculoskeletal problems, perceived factors that influence pain, and the influence of viola jokes suggest that high levels of biopsychosocial stressors are often associated with the classical music genre and playing the viola. The results from this research can be used to enhance music teacher-training programs, inform performance practice and viola pedagogy, and educate clinicians about the health risks of playing the viola.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".