Does age-related hearing loss deteriorate attentional resources?
Bibliographic record
Abstract
Recent work suggests that age-related hearing loss (HL) is a possible risk factor for cognitive decline in older adults. Resulting poor speech recognition negatively impacts cognitive, social and emotional functioning and may relate to dementia. However, little is known about the consequences of hearing loss on other non-linguistic domains of cognition. The aim of this study was to investigate the role of HL on covert orienting of attention, selective attention and executive control. We compared older adults with and without mild to moderate hearing loss (26-60 dB) performing (1) a spatial cueing task with uninformative central cues (social vs. nonsocial cues), (2) a flanker task and (3) a neuropsychological assessment of attention. The results showed that overall response times and flanker interference effects were comparable across groups. However, in spatial cueing of attention using social and nonsocial cues, hearing impaired individuals were characterized by reduced validity effects, though no additional group differences were found between social and nonsocial cues. Hearing impaired individuals also demonstrated diminished performance on the Montreal Cognitive Assessment (MoCA) and on tasks requiring divided attention and flexibility. This work indicates that while response speed and response inhibition appear to be preserved following mild-to-moderate acquired hearing loss, orienting of attention, divided attention and the ability to flexibly allocate attentional resources are more deteriorated in older adults with HL. This work suggests that hearing loss might exacerbate the detrimental influences of aging on visual attention.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".