Whole Person, Whole Journey: Developing a Person-Centred Regional Dementia Strategy
Bibliographic record
Abstract
We present the development of a regional dementia strategy in Southwestern Ontario, Canada. We worked with stakeholders in a regional health authority to develop a dementia strategy. We conducted interviews with persons with dementia and their care partners (n = 26) and health care administrators and policy makers (n = 33); and administered a priority-setting survey (n = 64). Both participant groups identified provider compassion, professionalism, and care in the early stages of dementia as system strengths. Both groups also highlighted a need for more integration and coordination, a need for more person-centred care, support for care partners, and more flexibility in the provision and receipt of services. The highest-ranked priorities were improving care partner support, improving access to care, and improving system-wide quality. We integrate these strengths, needs, and priorities in a strategic framework, "Whole Person, Whole Journey". Organizations developing a dementia strategy may use this framework as a springboard for their own work.
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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 | 0.016 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".