Sex-Related Differences in the Associations Between Montreal Cognitive Assessment Scores and Pure-Tone Measures of Hearing
Bibliographic record
Abstract
PURPOSE: Hearing loss (HL) is associated with cognitive performance in older adults, including performance on the Montreal Cognitive Assessment (MoCA), a brief cognitive screening test. Yet, despite well-established sex-related differences in both hearing and cognition, very few studies have tested whether there are sex-related differences in auditory-cognitive associations. METHOD: = 69 years, 60% women). Hearing was measured using audiometry (pure-tone average [PTA] of thresholds at 500, 1000, 2000, and 4000 Hz in the worse ear). Cognition was assessed using the MoCA. Additionally, we calculated MoCA scores with hearing-dependent subtests excluded from scoring (MoCA-Modified). RESULTS: Men and women did not differ in age, education, or history of depression. Women had better hearing than men. Women with normal hearing were more likely to pass the MoCA compared with their counterparts with HL. In contrast, the likelihood of passing the MoCA did not depend on hearing status in men. Linear regression analysis showed an interaction between sex and PTA in the worse ear. PTAs were significantly correlated with both MoCA and MoCA-Modified scores in women, whereas this was not observed in the men. CONCLUSIONS: This study is one of the first to demonstrate significant sex-related differences in auditory-cognitive associations even when hearing-related cognitive test items are omitted. Potential mechanisms underlying these female-specific effects are discussed. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.19233297.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".