Hearing impairment among workers and satisfaction with the use of hearing aids
Bibliographic record
Abstract
BACKGROUND: Hearing problems can have adverse effects on an individual's job performance, as well as on unemployment or underemployment and increased risk of stress-related sick leave. OBJECTIVE: To investigate hearing impairment among workers and satisfaction with the use of hearing aids. METHODS: Cross-sectional study with workers who are hearing aid users. Subjects underwent pure tone audiometry and answered the Hearing Handicap Inventory for Adults and the Satisfaction with Amplification in Daily Life questionnaires. RESULTS: Participants were 36 workers between 36 and 75 years old, with an average age of 53.47 years, 52.7% male and 47.3% female. There was a mild to moderate hearing handicap perception, with worse results for women in the emotional domain. As hearing loss increased, workers' frustration increased when talking to coworkers. Everyone was satisfied with the use of their hearing aids. Satisfaction increased with increasing age and decreased with increasing hearing loss. The greater the frustration when talking to co-workers, the lower the overall satisfaction with hearing aid use; the lower the satisfaction with the competence of the professional who assisted in adapting the hearing aid; the lower the satisfaction in environments with background noise and overall worse personal image. The worse the attitudes and emotional responses of workers regarding their hearing impairment, the lower the overall satisfaction with the hearing aid. CONCLUSIONS: Despite the use of hearing aids, workers perceive having a hearing impairment, especially women. As hearing loss and frustration in talking with co-workers increased, satisfaction decreased.
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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 | 0.002 |
| 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) | 0.003 | 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".