Dementia-Related Education and Support Service Availability, Accessibility, and Use in Rural Areas: Barriers and Solutions
Bibliographic record
Abstract
This scoping review mapped and synthesized published literature related to education and support services for individuals with dementia and their caregivers living rurally. Specifically, we investigated education and support service needs, availability and use of services, barriers to service access and use, and solutions to these barriers. Empirical, English-language articles (2,381) were identified within MEDLINE, CINAHL, PSYCINFO, and EMBASE. Articles were screened according to Arksey and O'Malley's (2005) five-stage scoping review methodology and the recommendations of Levac et al. (2010). Findings suggest limited availability of rural dementia-related support and education services, particularly respite care and day programs. Service use varied across studies, with barriers including low knowledge regarding services, practicality, and resource issues (e.g., transportation, financial), values and beliefs, stigma, and negative perceptions of services. Solutions included tailored and person-centred services, technological service provision, accessibility assistance, inter-organization collaboration, education regarding services, and having a "point of entry" to service use.
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 | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".