Clinical Assessment Tools for the Detection of Cognitive Impairment and Hearing Loss in the Ageing Population: A Scoping Review
Bibliographic record
Abstract
Objective: There is a strong association between cognitive impairment and hearing loss, both highly prevalent in the ageing population. Early detection of both hearing loss and cognitive impairment is essential in the management of these conditions to ensure effective and informed decisions on healthcare. The main objective was to identify existing and emerging cognitive and auditory assessment tools used in clinical settings (eg, memory clinics, audiology clinics), which manage the ageing population. Methods: A scoping review of peer-reviewed publications and results were reported according to the PRISMA-ScR guidelines. Results: A total of 289 articles were selected for data extraction. The majority of studies (76.1%) were conducted in 2017 or later. Tests of global cognitive function (ie, Mini-Mental State Exam, Montreal Cognitive Assessment) were the most commonly used method to detect cognitive impairment in hearing healthcare settings. Behavioral hearing testing (ie, pure-tone audiometry) was the most commonly used method to detect hearing loss in cognitive healthcare settings. Objective, physiological measures were seldom used across disciplines. Conclusion: Preferences among clinicians for short, accessible tests likely explain the use of tests of global cognitive function and behavioral hearing tests. Rapidly evolving literature has identified inherent limitations of administering global cognitive function tests and pure-tone testing in an ageing population. Using electrophysiological measures as an adjunct to standard methods of assessment may provide more reliable information for clinical recommendations in those with cognitive and hearing impairment, and subsequently achieve better healthcare outcomes. Plain Language Summary: 1. Hearing loss in mid-life (45– 65 years) is the number one modifiable risk factor for dementia, therefore early detection of hearing loss and cognitive impairment are essential to manage both conditions effectively.2. Tests of global cognitive function (eg, MMSE, MOCA) were the most commonly used tests to detect cognitive impairment in hearing healthcare clinics.3. Pure-tone audiometry was the most commonly used test to detect hearing loss in cognitive healthcare settings.4. Objective electrophysiological measures can overcome difficulties in assessing cognition and hearing loss in people with dementia, and can be a useful adjunct to existing assessment tests. Keywords: hearing loss, cognition, assessment, ageing, early detection
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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 | 0.017 | 0.098 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.024 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".