Correlates of Hearing Aid Use in UK Adults
Bibliographic record
Abstract
OBJECTIVES: Hearing impairment is ranked fifth globally for years lived with disability, yet hearing aid use is low among individuals with a hearing impairment. Identifying correlates of hearing aid use would be helpful in developing interventions to promote use. To date, however, no studies have investigated a wide range of variables, this has limited intervention development. The aim of the present study was to identify correlates of hearing aid use in adults in the United Kingdom with a hearing impairment. To address limitations in previous studies, we used a cross-sectional analysis to model a wide range of potential correlates simultaneously to provide better evidence to aid intervention development. DESIGN: The research was conducted using the UK Biobank Resource. A cross-sectional analysis of hearing aid use was conducted on 18,730 participants aged 40 to 69 years old with poor hearing, based on performance on the Digit Triplet test. RESULTS: Nine percent of adults with poor hearing in the cross-sectional sample reported using a hearing aid. The strongest correlate of hearing aid use was self-reported hearing difficulties (odds ratio [OR] = 110.69 [95% confidence interval {CI} = 65.12 to 188.16]). Individuals who were older were more likely to use a hearing aid: for each additional year of age, individuals were 5% more likely to use a hearing aid (95% CI = 1.04 to 1.06). People with tinnitus (OR = 1.43 [95% CI = 1.26 to 1.63]) and people with a chronic illness (OR = 1.97 [95% CI = 1.71 to 2.28]) were more likely to use a hearing aid. Those who reported an ethnic minority background (OR = 0.53 [95% CI = 0.39 to 0.72]) and those who lived alone (OR = 0.80 [95% CI = 0.68 to 0.94]) were less likely to use a hearing aid. CONCLUSIONS: Interventions to promote hearing aid use need to focus on addressing reasons for the perception of hearing difficulties and how to promote hearing aid use. Interventions to promote hearing aid use may need to target demographic groups that are particularly unlikely to use hearing aids, including younger adults, those who live alone and those from ethnic minority backgrounds.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".