Validity and reliability of the Musicians’ Health Literacy Questionnaire, MHL-Q19
Bibliographic record
Abstract
High prevalence of musicians' physical and mental performance-related health issues (PRHI) has been demonstrated over the last 30 years. To address this, health promotion strategies have been implemented at some post-secondary music institutions around the world, yet the high prevalence of PRHI has persisted. In 2018, an international group of researchers formed the Musicians' Health Literacy Consortium to determine how best to decrease PRHI, and to examine the relationship between PRHI and health literacy. An outcome of the Consortium was the development of a new health literacy tool for musicians, the MHL-Q19, which drew from the theoretical framework of the European health literacy suite of tools, HLS-EU. The aim of the current study was to evaluate the validity and reliability of the MHL-Q19. Participants completed a battery of questionnaires, including the HLS-EU-Q16 for the assessment of general health literacy; the Musculoskeletal Pain Intensity and Interference Questionnaire for Musicians (MPIIQM); the RAND-12 quality of life questionnaire; and the General Self-Efficacy scale (GSE). We hypothesized that the MHL-Q19 would have a weak correlation with the HLS-EU-Q16; moderate correlation with the physical component scale and weak correlation with the mental component scale of the RAND-12; moderate correlation with the GSE; and finally, moderate correlation with pain interference and weak correlation with pain intensity of the MPIIQM. A total of 549 post-secondary music students from six English-speaking countries completed the battery of questionnaires, and 328 of these participants provided valid responses to the MHL-Q19 alone 2 weeks later. The tool showed acceptable internal consistency and test-retest reliability. Three of our hypotheses were supported, although the strength of the correlations varied from what we had predicted. The fourth hypothesis was not supported; our findings indicate that lower health literacy scores were weakly related to higher MPIIQM pain intensity and interference scores. The results of this study support the notion that musicians' health literacy is a distinct construct that cannot be fully evaluated with existing health literacy tools. Given that this is a new instrument, the evidence presented is positive and promising. Further studies will be needed to refine the tool.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".