Effect of Hearing Protection Use on Pianists’ Performance and Experience: Comparing Foam and Musician Earplugs
Bibliographic record
Abstract
Professional musicians are often exposed to high noise levels and thus face the risk of noise-induced hearing loss. Yet, adoption rates for hearing protection among musicians are low. Previous surveys indicate that the chief concern is the effect of hearing protection use on performance. However, few studies have investigated actual changes in performance when wearing hearing protection. We report an experiment investigating differences in pianists' performance and experience with and without hearing protection. We compare the effect of foam earplugs and musician earplugs, designed to preserve sound quality with a flat frequency response. The analysis revealed that participants performed overall more loudly with the foam earplugs than with the musician earplugs, and in turn performances with the musician earplugs were louder than the open condition, indicating a compensatory effect. However, this effect was stronger for novel excerpts than for familiar excerpts. No effect was observed on dynamic range. Furthermore, we observed an acclimatization effect, whereby the effect of hearing protection use, observed on the first performance, decreased on the second performance. In terms of experience, participants reported changes in coloration, difficulties gauging dynamics and articulation, and increased effort required when performing with hearing protection. These effects were more pronounced when wearing the foam earplugs, and the participants reported finding the musician earplugs more comfortable to wear and play with. In conclusion, hearing protection use affects pianists' performance particularly in terms of dynamics and their experience more so in terms of coloration. But the effects are less marked for familiar pieces and after repetition, suggesting that pianists can quickly adjust their playing when playing familiar pieces with hearing protection.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".