Patient and family perceptions of rural primary care interprofessional memory clinics for diagnosis and management of dementia: a mixed methods study
Bibliographic record
Abstract
BACKGROUND: Aging rural populations globally are leading to rising numbers of rural people living with dementia, who experience challenges in receiving a diagnosis and accessing formal supports. Guidelines recommend that primary care play a lead role in diagnosis and post-diagnostic care coordination, yet there are few rural-based examples. The purpose of this study was to better understand the experiences of rural patients and caregivers attending rural primary care-based memory clinics. METHODS: The parallel mixed methods (quantitative and qualitative) design included a 10-item questionnaire (n = 27) and telephone interviews (n = 8) with patients and caregivers attending 6 rural primary care memory clinics in the province of Saskatchewan, Canada. RESULTS: The majority of those who completed the questionnaire agreed that results of assessments were thoroughly explained, they felt free to discuss concerns, were told about treatments, that it was helpful having all the health-care professionals together, and they learned about available supports. Results were mixed regarding whether they needed more information about the condition and its course. Four themes were identified in interviews: benefits of local rural-based care, sense of being heard, value of team-based care, and feeling supported for the future. CONCLUSIONS: The rural memory clinics, run by local health-care professionals, address barriers previously reported by rural patients and families including geographic distances to services, challenges obtaining a diagnosis, limited specialist access, and challenges accessing post-diagnosis information and support.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".