Individuals With Mild Cognitive Impairment and Alzheimer's Disease Benefit From Audiovisual Speech Cues and Supportive Sentence Context
Bibliographic record
Abstract
Purpose Speech perception in noise becomes difficult with age but can be facilitated by audiovisual (AV) speech cues and sentence context in healthy older adults. However, individuals with Alzheimer's disease (AD) may present with deficits in AV integration, potentially limiting the extent to which they can benefit from AV cues. This study investigated the benefit of these cues in individuals with mild cognitive impairment (MCI), individuals with AD, and healthy older adult controls. Method This study compared auditory-only and AV speech perception of sentences presented in noise. These sentences had one of two levels of context: high (e.g., “Stir your coffee with a spoon”) and low (e.g., “Bob didn't think about the spoon”). Fourteen older controls ( M age = 72.71 years, SD = 9.39), 13 individuals with MCI ( M age = 79.92 years, SD = 5.52), and nine individuals with probable Alzheimer's-type dementia ( M age = 79.38 years, SD = 3.40) completed the speech perception task and were asked to repeat the terminal word of each sentence. Results All three groups benefited (i.e., identified more terminal words) from AV and sentence context. Individuals with MCI showed a smaller AV benefit compared to controls in low-context conditions, suggesting difficulties with AV integration. Individuals with AD showed a smaller benefit in high-context conditions compared to controls, indicating difficulties with AV integration and context use in AD. Conclusions Individuals with MCI and individuals with AD do benefit from AV speech and semantic context during speech perception in noise (albeit to a lower extent than healthy older adults). This suggests that engaging in face-to-face communication and providing ample context will likely foster more effective communication between patients and caregivers, professionals, and loved ones.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".