A scoping review to inform the development of dementia care competencies
Bibliographic record
Abstract
Health professionals and care partners of persons living with dementia have expressed that learning needs related to dementia care are a priority. There are currently a variety of training programs available in Ontario (Canada) to address aspects of dementia care, but no commonly accepted description of the core knowledge, skills, and abilities (i.e., competencies) that should underpin dementia-related training and education in the province. The aim of this study was to review current evidence to inform the later development of competency statements describing the knowledge, skills, and actions required for dementia care among care providers ranging from laypersons to health professionals. We also sought to validate existing dementia care principles and align new concepts to provide a useful organizing framework for future competency development. We distinguished between micro-, meso-, and macro-level concepts to clarify the competencies required by individuals situated in different locations across the healthcare system, linking competency development in dementia care to broader system transformation. This review precedes the co-development of a holistic competency framework to guide approaches to dementia care training in Ontario.
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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 | 0.017 | 0.059 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.026 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".