Strategies used during the cognitive evaluation of older adults with dual sensory impairment: a scoping review
Bibliographic record
Abstract
BACKGROUND: Dual sensory impairment (DSI), the combination of visual and hearing impairments, is associated with increased risk for age-related cognitive decline and dementia. Administering cognitive tests to individuals with sensory impairment is challenging because most cognitive measures require sufficient hearing and vision. Considering sensory limitations during cognitive test administration is necessary so that the effects of sensory and cognitive abilities on test performance can be differentiated and the validity of test results optimized. OBJECTIVE: To review empirical strategies that researchers have employed to accommodate DSI during cognitive testing of older adults. METHODS: Seven databases (MEDLINE, Embase, Web of Science, CINAHL, PsycINFO, Global Health and the Evidence-Based Medicine Reviews databases) were searched for relevant articles integrating the three concepts of cognitive evaluation, aging, and DSI. Given the inclusion criteria, this scoping review included a total of 67 papers. RESULTS: Twenty-eight studies reported five categories of strategies for cognitive testing of older adult participants with DSI: the assistance of experts, the modification of standardized test scoring procedures, the use of communication strategies, environmental modifications, and the use of cognitive tests without visual and/or auditory items. CONCLUSIONS: The most used strategy reported in the included studies was drawing on the assistance of team members from related fields during the administration and interpretation of cognitive screening measures. Alternative strategies were rarely employed. Future research is needed to explore the knowledge-to-practice gap between research and current clinical practice, and to develop standardized testing strategies.
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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 | 0.022 | 0.093 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.021 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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 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".