Canadian care priorities and service needs of rural people with dementia: A scoping review protocol
Bibliographic record
Abstract
Background: Age is one of the greatest risk factors of dementia, and the rural demographic is aging in Canada. Compared to their urban counterparts, rural older adults often face unique challenges in accessing cognitive healthcare, which is exacerbated by a shortage of healthcare specialists, public transportation, finances, education, services, and dispersed geography. This scoping review protocol outlines the methodology that will be used to examine the literature about the care priorities and service needs from the perspectives of rural older adults living with dementia in Canada. Methods: This scoping review protocol will follow the guidance of Arksey and O’Malley, Levac and colleagues, and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extensions for Scoping Reviews (PRISMA-ScR) checklist. The search strategy will identify relevant peer-reviewed literature in databases including CINAHL, EMBASE, PsycINFO, PubMed, Web of Science, and Scopus. The reference lists of applicable articles will be searched by hand to identify relevant articles. Two reviewers will conduct data extraction using a standardized data extraction table. Ethics and knowledge translation: Given this scoping review will be an examination of the published literature, human subjects will not be included in this research. Therefore, ethics approval is not required. Knowledge mobilization and dissemination strategies will include peer-reviewed journal articles, conference presentations, community workshops, newsletter articles, and webinars. This study may provide valuable information for healthcare practitioners, community leaders, and policymakers working to support people living with cognitive impairment and dementia in rural communities.
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 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 | 0.120 | 0.089 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.008 | 0.011 |
| Bibliometrics | 0.024 | 0.020 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.062 | 0.008 |
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".