Screening for Vision Impairments in Individuals with Dementia Living in Long-Term Care: A Scoping Review
Bibliographic record
Abstract
Vision impairments are prevalent, but underdiagnosed in individuals with dementia living in long-term care (LTC). Effective screening tools could identify remediable vision problems. This scoping review was conducted to identify vision screening tests used with individuals with dementia and assesses their suitability for administration by nurses in LTC. A literature search using the Arksey and O'Malley (2005) method included research articles, conference proceedings, and dissertations. Data were included from participants over 65 years of age with a diagnosis of probable dementia. A panel of vision experts evaluated the suitability of the candidate vision tests. The search yielded 179 publications that met the inclusion criteria. Of 134 vision tests that were identified, 19 were deemed suitable for screening by nurses in LTC. Tests screened for acuity (12), visual field (1), anatomy (2), color vision (2), and general visual abilities (2). Tests were excluded because of complexity of interpretation (90), need for specialized training (83), use in research only (57), need for specialized equipment (54), not assessing visual function (44), long test duration (21), uncommonness (13), and needing an act reserved for specialists (7). Psychometric properties were not often reported for tests. Few of the tests identified had been validated for use with individuals with dementia. Based on our review, few tests were deemed suitable for use by nurses to assess this population in LTC. Identifying appropriate tools to screen vision in individuals with dementia is a necessary first step to interventions that could potentially improve functioning and quality of life.
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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 | 0.010 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.011 |
| 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) | 0.003 | 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".