MusicCohort: Pilot feasibility of a protocol to assess students’ physical and mental health in a Canadian post-secondary school of music
Bibliographic record
Abstract
Abstract Objective Music-related physical and mental health conditions are common among post-secondary music students, with many studies reporting a prevalence greater than 70%. However, there is currently no consensus on appropriate, validated assessments for this population. The aim of this pilot study was to test the feasibility of an assessment protocol developed for a German longitudinal study with Canadian post-secondary music students, and to compare the health of music students to non-music students. Using a cross-sectional design, first-semester music and non-music control students were recruited at two campuses at the same university. Both groups completed questionnaires and physical testing, including range of motion, core strength, and pressure pain threshold. Nineteen music students and 50 non-music student controls participated in this study. Results The German protocol is feasible in a Canadian post-secondary setting. Canadian music students demonstrated similar health outcomes to those in the parent study. All participants demonstrated poorer mental and physical quality of life than the Canadian norms, though this was not statistically significant. The results of this study should be confirmed in a larger study. Future studies with larger sample sizes can provide further insight into the health of Canadian music students, providing a basis for prevention and intervention.
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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 | 0.022 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".