Personal listening device usage among Canadians and audiometric outcomes among 6–29 year olds
Bibliographic record
Abstract
Objective To describe personal listening device (PLD) usage and sociodemographic variables among a nationally representative sample of Canadians and examine audiometric outcomes among a subsample.Design Audiometry and in-person questionnaires were used to evaluate hearing and PLD usage across age, sex, household income/education level. PLD exposure was quantified using a common occupational noise limit.Study sample A randomised sample of 10,460 respondents, aged 6–79, with audiometric analysis of a subsample (n = 4807), aged 6–29, tested between 2012 and 2015.Results Loud PLD usage was reported by19.5% of Canadians. The highest prevalence was among teenagers (44.2%) and young adults (36.3%). Among children, 13.1% of users listened at loud volumes. High PLD usage (equivalent to or above 85 dBA, LEX 40) among 12–19 year olds was double that of 20–29 year olds: 10.2% versus 5.1%E. Five years or more of loud PLD usage was associated with significantly higher mean hearing thresholds compared to less years. No association between loud or high PLD usage and mean thresholds were found.Conclusion The majority used PLDs safely, however a small proportion reported high risk usage which will impact hearing should this pattern persist over many years.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".