Prevalence of Hearing Loss Among University Music Students
Bibliographic record
Abstract
This study examined the hearing sensitivity of student musicians (N = 53) and non-musicians (N = 54) between the ages of 17 and 31. The two groups were compared for differences in hearing threshold levels, incidences of hearing loss described by pure tone average levels, and incidences of notches at 3, 4 or 6 kHz. Survey data was also used to explore relationships between hearing sensitivity and gender, age, music lesson starting age, musical instruments played, number of years playing that instrument, instrument type, use of hearing protection and personal music device listening time. No significant differences in hearing threshold levels between the two groups was found. Overall prevalence of notches was 1.9% for musicians versus 9.3% for non-musicians using the Niskar (2001) algorithm, or 20.8% for musicians versus 31.5% for non-musicians using the Coles (2000) algorithm. Both algorithms identified more non-musicians with notches, although the difference between the two groups was not significant. Musicians who use hearing protection had significantly more incidences of notches, and there was a weak correlation found between hearing sensitivity and age. The other survey parameters studied showed very little or no relationship with hearing sensitivity. The results do not show any indication that music students are at a higher risk of noise-induced hearing loss than non-music students. Cette etude a examine la sensibilite auditive d’etudiants musiciens (N = 53) et des non musiciens (N = 54) âges entre 17 et 31 ans. Les deux groupes ont ete compares pour les differences de seuil auditif, les incidences de la perte auditive decrite par la moyenne des sons purs, et les incidences d’encoches neurosensorielles a 3, 4 ou 6 kHz. Les donnees ont egalement ete utilisees pour explorer les relations entre la sensibilite auditive et l'âge, le sexe, l'âge du debut des cours de musique, les instruments de musique joues, le nombre d'annees jouant cet instrument, le type d'instrument, l'utilisation de protection auditive et le temps d'ecoute d’appareils de musique personnelle. Aucune difference significative dans les niveaux de seuil auditif entre les deux groupes n'a ete trouvee. La prevalence globale d’encoches neurosensorielles etait de 1,9% pour les musiciens contre 9,3% pour les non-musiciens utilisant l'algorithme Niskar (2001), et de 20,8% pour les musiciens contre 31,5% pour les non musiciens utilisant l'algorithme de Coles (2000). Les deux algorithmes ont identifie plus de non musiciens avec des encoches, bien que la difference entre les deux groupes ne soit pas significative. Les musiciens qui utilisent la protection auditive ont beaucoup plus d’encoches neurosensorielles, et il y a eu une faible correlation entre la sensibilite auditive et l'âge. Les autres parametres etudies ont montre tres peu ou pas de relation avec la sensibilite auditive. Les resultats ne montrent aucune indication que les etudiants musiciens courent un risque plus eleve de perte auditive induite par le bruit que les etudiants non-musiciens.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".