Hearing Loss and Cognitive-Communication Test Performance of Long-Term Care Residents With Dementia: Effects of Amplification
Bibliographic record
Abstract
Purpose: The study aims were (a) to explore the relationship between hearing loss and cognitive-communication performance of individuals with dementia, and (b) to determine if hearing loss is accurately identified by long-term care (LTC) staff. The research questions were (a) What is the effect of amplification on cognitive-communication test performance of LTC residents with early- to middle-stage dementia and mild-to-moderate hearing loss? and (b) What is the relationship between measured hearing ability and hearing ability recorded by staff using the Resident Assessment Instrument-Minimum Data Set 2.0 (RAI-MDS; Hirdes et al., 1999)? Method: Thirty-one residents from 5 long-term care facilities participated in this quasiexperimental crossover study. Residents participated in cognitive-communication testing with and without amplification. RAI-MDS ratings of participants' hearing were compared to audiological assessment results. Results: Participants' speech intelligibility index scores significantly improved with amplification; however, participants did not demonstrate significant improvement in cognitive-communication test scores with amplification. A significant correlation was found between participants' average pure-tone thresholds and RAI-MDS ratings of hearing, yet misclassification of hearing loss occurred for 44% of participants. Conclusions: Measuring short-term improvement of performance-based cognitive communication may not be the most effective means of assessing amplification for individuals with dementia. Hearing screenings and staff education remain necessary to promote hearing health for LTC residents.
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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 | 0.003 | 0.012 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".