Aging, Cognitive Decline and Hearing Loss: Effects of Auditory Rehabilitation and Training with Hearing Aids and Cochlear Implants on Cognitive Function and Depression among Older Adults
Bibliographic record
Abstract
A growing interest in cognitive effects associated with speech and hearing processes is spreading throughout the scientific community essentially guided by evidence that central and peripheral hearing loss is associated with cognitive decline. For the present research, 125 participants older than 65 years of age (105 with hearing impairment and 20 with normal hearing) were enrolled, divided into 6 groups according to their degree of hearing loss and assessed to determine the effects of the treatment applied. Patients in our research program routinely undergo an extensive audiological and cognitive evaluation protocol providing results from the Digit Span test, Stroop color-word test, Montreal Cognitive Assessment and Geriatric Depression Scale, before and after rehabilitation. Data analysis was performed for a cross-sectional and longitudinal study of the outcomes for the different treatment groups. Each group demonstrated improvement after auditory rehabilitation or training on short- and long-term memory tasks, level of depression and cognitive status scores. Auditory rehabilitation by cochlear implants or hearing aids is effective also among older adults (median age of 74 years) with different degrees of hearing loss, and enables positive improvements in terms of social isolation, depression and cognitive performance.
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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 | 0.001 |
| 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) | 0.001 | 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".