THE RELATIONSHIP BETWEEN COGNITIVE FUNCTIONING AND HEARING ABILITY IN OLDER ADULTS
Bibliographic record
Abstract
Built on the recent epidemiologic evidence of the association between hearing loss and cognitive impairment, the present study aimed to investigate the relationship between cognitive functioning and hearing ability in a group of healthy community-dwelling older adults with a wide range of ages and hearing status. Montreal Cognitive Assessment (MoCA), a cognitive screening test for detecting mild cognitive impairment (Nasreddine et al., 2005), was used to assess cognitive functioning. Hearing ability was measured by clinical audiometric and speech-in-noise testing. The study included eighty older participants with an age range of 56–89 years and hearing status ranging from near-normal hearing to moderate hearing loss. The results showed that older individual’s MoCA score was strongly associated with hearing ability. Hearing (i.e., pure tone threshold) significantly predicted individual performance on MoCA, particularly for those test items that rely heavily on auditory input. Taken together, these findings highlight the intimate relationship between cognitive functioning and hearing ability, which should be recognized by the medical professionals in order to better serve the aging community (Work supported by NIH).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| 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".