The impact of combined age-related vision loss and dementia on the participation of older adults: A scoping review
Bibliographic record
Abstract
INTRODUCTION: There are a growing number of older adults with combined age-related vision loss (ARVL) and dementia. Existing literature shows the pervasive impact that both diagnoses have separately on the participation of older adults, however, little is known about the societal participation of older adults with both conditions. As such, the aim of this scoping review was to explore the combined impact of ARVL and dementia on the participation of older adults, with a specific focus on highlighting strategies that help mitigate the impact of ARVL and dementia on participation. METHODS: This study utilized a scoping review, informed by the framework by Arksey and O'Malley [1]. Two researchers independently ran a total of 62 search terms across four categories in six databases (PubMed, CINAHL, Scopus, Embase, Medline, PsycINFO), with an initial yield of 2,053 articles. Grey literature was also included in this scoping review and was retrieved from organizational websites, brochures, conference proceedings, and a Google Scholar search. The application of study inclusion criteria resulted in a final yield of 13 empirical studies and 10 grey literature sources. RESULTS: Following detailed thematic analysis of the empirical and grey literature sources, four themes emerged regarding the impact of combined ARVL and dementia on the participation of older adults including: 1) Managing the pragmatic aspects of a dual diagnosis; 2) Diverse approaches to risk assessment and management; 3) Adopting a multi-disciplinary approach to facilitate care and; 4) Using compensatory strategies to facilitate participation. CONCLUSIONS: The four themes highlight the challenges older adults with these combined diagnoses experience, which limit their opportunities for meaningful participation. Given the scarcity of research on this topic, future research should identify the type of ARVL and dementia diagnoses of study participants, conduct qualitative research about the lived experiences of older adults with a dual diagnosis, and broaden the geographic scope of research.
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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 | 0.026 | 0.111 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.023 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.002 |
| 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".