Auditory Processing of Older Adults With Probable Mild Cognitive Impairment
Bibliographic record
Abstract
Purpose: Studies suggest that deficits in auditory processing predict cognitive decline and dementia, but those studies included limited measures of auditory processing. The purpose of this study was to compare older adults with and without probable mild cognitive impairment (MCI) across two domains of auditory processing (auditory performance in competing acoustic signals and temporal aspects of audition). Method: The Montreal Cognitive Assessment (Nasreddine et al., 2005) was used to classify participants as with or without probable MCI. In this cross-sectional study, participants (n = 79) completed 4 measures of auditory processing: Synthetic Sentence Identification with Ipsilateral Competing Message (Gates, Beiser, Rees, D'Agostino, & Wolf, 2002), Dichotic Sentence Identification (Fifer, Jerger, Berlin, Tobey, & Campbell, 1983), Adaptive Tests of Temporal Resolution (ATTR; Lister & Roberts, 2006; across-channel and within-channel subtests), and time-compressed speech (Wilson, 1993; Wilson, Preece, Salamon, Sperry, & Bornstein, 1994). Audiometry was also conducted. Results: Those with probable MCI had significantly poorer performance than those without MCI on Synthetic Sentence Identification with Ipsilateral Competing Message, Dichotic Sentence Identification, and the ATTR within-channel subtest. No group differences were found for time-compressed speech, ATTR across-channel, or audiometric measures. Conclusions: Older adults with cognitive impairment not only have difficulty with competing acoustic signals but may also show poor temporal processing. The profile of auditory processing deficits among older adults with cognitive impairment may include multiple domains.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".