Aging and Hearing Health: The Life-course Approach
Bibliographic record
Abstract
Sensory abilities decline with age. More than 5% of the world's population, approximately 360 million people, have disabling hearing loss. In adults, disabling hearing loss is defined by thresholds greater than 40 dBHL in the better hearing ear.Hearing disability is an important issue in geriatric medicine because it is associated with numerous health issues, including accelerated cognitive decline, depression, increased risk of dementia, poorer balance, falls, hospitalizations, and early mortality. There are also social implications, such as reduced communication function, social isolation, loss of autonomy, impaired driving ability, and financial decline. Furthermore, the onset of hearing loss is gradual and subtle, first affecting the detection of high-pitched sounds and with difficulty understanding speech in noisy but not in quiet environments. Consequently, delays in recognizing and seeking help for hearing difficulties are common. Age-related hearing loss has no known cure, and technologies (hearing aids, cochlear implants, and assistive devices) improve thresholds but do not restore hearing to normal. Therefore, health care for persons with hearing loss and people within their communication circles requires education and counseling (e.g., increasing knowledge, changing attitudes, and reducing stigma), behavior change (e.g., adapting communication strategies), and environmental modifications (e.g., reducing noise). In this article, we consider the causes, consequences, and magnitude of hearing loss from a life-course perspective. We examine the concept of "hearing health," how to achieve it, and implications for policy and practice.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".