Impact of Hearing Loss and Amplification on Performance on a Cognitive Screening Test
Bibliographic record
Abstract
BACKGROUND: There have been numerous recent reports on the association between hearing impairment and cognitive function, such that the cognition of adults with hearing loss is poorer relative to the cognition of adults with normal hearing (NH), even when amplification is used. However, it is not clear the extent to which this is testing artifact due to the individual with hearing loss being unable to accurately hear the test stimuli. PURPOSE: The primary purpose of this study was to examine whether use of amplification during cognitive screening with the Montreal Cognitive Assessment (MoCA) improves performance on the MoCA. Secondarily, we investigated the effects of hearing ability on MoCA performance, by comparing the performance of individuals with and without hearing impairment. STUDY SAMPLE: Participants were 42 individuals with hearing impairment and 19 individuals with NH. Of the individuals with hearing impairment, 22 routinely used hearing aids; 20 did not use hearing aids. DATA COLLECTION AND ANALYSIS: Following a written informec consent process, all participants completed pure tone audiometry, speech testing in quiet (Maryland consonant-nucleus-consonant [CNC] words) and in noise (Quick Speech in Noise [QuickSIN] test), and the MoCA. The speech testing and MoCA were completed twice. Individuals with hearing impairment completed testing once unaided and once with amplification, whereas individuals with NH completed unaided testing twice. RESULTS: The individuals with hearing impairment performed significantly less well on the MoCA than those without hearing impairment for unaided testing, and the use of amplification did not significantly change performance. This is despite the finding that amplification significantly improved the performance of the hearing aid users on the measures of speech in quiet and speech in noise. Furthermore, there were strong correlations between MoCA score and the four frequency pure tone average, Maryland CNC score and QuickSIN, which remain moderate to strong when the analyses were adjusted for age. CONCLUSIONS: It is concluded that the individuals with hearing loss here performed less well on the MoCA than individuals with NH and that the use of amplification did not compensate for this performance deficit. Nonetheless, this should not be taken to suggest the use of amplification during testing is unnecessary because it might be that other unmeasured factors, such as effort required to perform or fatigue, were decreased with the use of amplification.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".