Building capacity for dementia care: training program to develop primary care memory clinics.
Bibliographic record
Abstract
PROBLEM BEING ADDRESSED: Currently, dementia care provided by family physicians is suboptimal and access to specialist resources is limited. With the aging population, there is a need for system-wide, programmatic interventions to improve the diagnosis and management of patients with memory difficulties. The development of primary care memory clinics addresses this need. OBJECTIVE: The Memory Clinic Training Program aims to develop highly functioning interprofessional memory clinics that assist family physicians in providing improved care for patients with dementia and other forms of cognitive impairment. PROGRAM DESCRIPTION: The interprofessional training program consists of a 2-day case-based workshop, 1 day of observership and clinical training at the Centre for Family Medicine Memory Clinic, and 2 days of on-site mentorship at each newly formed memory clinic. CONCLUSION: The Memory Clinic Training Program is an accredited, comprehensive program designed to assist family practice groups with developing primary care memory clinics. These clinics aim to transform the current limited practice capability of individual family physicians into a systematic, comprehensive, interprofessional health care service that improves capacity and quality of primary care for patients with cognitive impairment and dementia.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.005 |
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".