Hearing Screening for Residents in Long-Term Care Homes Who Live with Dementia: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Hearing loss is highly prevalent in older adults, particularly among those living with dementia and residing in long-term care homes (LTCHs). Sensory declines can have deleterious effects on functioning and contribute to frailty, but the hearing needs of residents are often unrecognized or unaddressed. OBJECTIVE: To identify valid and reliable screening measures that are effective for the identification of hearing loss and are suitable for use by nursing staff providing care to residents with dementia in LTCHs. METHODS: Electronic databases (Embase, Medline, PsycINFO, CENTRAL, and CINAHL) were searched using comprehensive search strategies, and a stepwise approach based on Arksey & O'Malley's scoping review and appraisal process was followed. RESULTS: There were 193 scientific papers included in the review. Pure-tone audiometry was the most frequently reported measure to test hearing in older adults living with dementia. However, measures including self- or other-reports and questionnaires, review of medical records, otoscopy, and the whisper test were found to be most suitable for use by nurses working with older adults living with dementia in LTCHs. CONCLUSION: Although frequently used, the suitability of pure-tone audiometry for use by nursing staff in LTCHs is limited, as standardized audiometry presents challenges for many residents, and specific training is needed to successfully adapt test administration procedures and interpret results. The whisper test was considered to be more suitable for use by staff in LTCH; however, it yields a limited characterization of hearing loss. There remains an urgent need to develop new approaches to screen hearing in LTCHs.
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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 | 0.009 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".