Effect of Reduced Audibility on Mini-Mental State Examination Scores
Bibliographic record
Abstract
BACKGROUND: The interaction of audition and cognition has been of interest to researchers and clinicians, especially as the prevalence of hearing loss and cognitive decline increases with advancing age. Cognitive screening tests are commonly used to assess cognitive status in individuals reporting changes in memory or function or to monitor cognitive status over time. These assessments are administered verbally, so performance may be adversely affected by hearing loss. Previous research on the impact of reduced audibility on cognitive screening test scores has been limited to older adults with sensorineural hearing loss (SNHL) or young adults with normal hearing and simulated audibility loss. No comparisons have been conducted to determine whether age-related SNHL and its impact on cognitive screening tests is successfully modeled by audibility reduction. PURPOSE: The purpose of this study was to examine the effects of reduced audibility on the Mini-Mental State Examination (MMSE), a common bedside cognitive screening instrument, by comparing performance of cognitively normal older adults with SNHL and young adults with normal hearing. DESIGN: A 1:1 gender-matched case-control design was used for this study. STUDY SAMPLE: Thirty older adults (60-80 years old) with mild to moderately severe SNHL (cases) and 30 young adults (18-35 years old) with normal hearing (controls) served as participants for this study. Participants in both groups were selected for inclusion if their cognitive status was within normal limits on the Montreal Cognitive Assessment. DATA COLLECTION AND ANALYSIS: Case participants were administered a recorded version of the MMSE in background noise at a signal-to-noise ratio of +25-dB SNR. Control participants were administered a digitally filtered version of the MMSE that reflected the loss of audibility (i.e., threshold elevation) of the matched case participant at a signal-to-noise ratio of +25-dB SNR. Performance on the MMSE was scored using standard criteria. RESULTS: Between-group analyses revealed no significant difference in the MMSE score. However, within-group analyses showed that education was a significant effect modifier for the case participants. CONCLUSIONS: Reduced audibility has a negative effect on MMSE score in cognitively intact participants, which contributes to and confirms the findings of earlier studies. The findings suggest that observed reductions in score on the MMSE were primarily due to loss of audibility of the test item. The negative effects of audibility loss may be greater in individuals who have lower levels of educational attainment. Higher levels of educational attainment may offset decreased performance on the MMSE because of reduced audibility. Failure to consider audibility and optimize communication when administering these assessments can lead to invalid results (e.g., false positives or missed information), misdiagnosis, and inappropriate recommendations for medication or intervention.
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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 | 0.002 | 0.002 |
| 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".