Screening tools for the identification of dementia for adults with age-related acquired hearing or vision impairment: a scoping review
Bibliographic record
Abstract
BACKGROUND: Cognitive screening tests frequently rely on items being correctly heard or seen. We aimed to identify, describe, and evaluate the adaptation, validity, and availability of cognitive screening and assessment tools for dementia which have been developed or adapted for adults with acquired hearing and/or vision impairment. METHOD: Electronic databases were searched using subject terms "hearing disorders" OR "vision disorders" AND "cognitive assessment," supplemented by exploring reference lists of included papers and via consultation with health professionals to identify additional literature. RESULTS: 1,551 papers were identified, of which 13 met inclusion criteria. Four papers related to tests adapted for hearing impairment; 11 papers related to tests adapted for vision impairment. Frequently adapted tests were the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MOCA). Adaptations for hearing impairment involved deleting or creating written versions for hearing-dependent items. Adaptations for vision impairment involved deleting vision-dependent items or spoken/tactile versions of visual tasks. No study reported validity of the test in relation to detection of dementia in people with hearing/vision impairment. Item deletion had a negative impact on the psychometric properties of the test. CONCLUSIONS: While attempts have been made to adapt cognitive tests for people with acquired hearing and/or vision impairment, the primary limitation of these adaptations is that their validity in accurately detecting dementia among those with acquired hearing or vision impairment is yet to be established. It is likely that the sensitivity and specificity of the adapted versions are poorer than the original, especially if the adaptation involved item deletion. One solution would involve item substitution in an alternative sensory modality followed by re-validation of the adapted test.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".