A scoping review of dementia education programs to assess for the inclusion of culture
Bibliographic record
Abstract
This scoping review examined literature on dementia education programs (DEPs) for healthcare providers and students. The search was conducted using the Discover! search engine that includes 63 databases. The review included a total of 25 articles that met the eligibility criteria. There were numerous DEPs that varied by frequency and duration, mode of delivery, content, target population, program evaluation measures, and outcomes. Most involved nursing staff and students and took place in Canada, the US, and the UK. The most common delivery mode was a one-time in-person session and a wide variety of topics were covered, both general (e.g., understanding dementia) and specific (e.g., driving, delirium). Twenty different tools were used to measure primarily changes in knowledge and attitudes, with little attention paid to performance and care provision. Only three studies on DEPs focused on culture in terms of race and ethnicity. The implications of this scoping review for education are that DEPs need to meaningfully address culture and culturally safe care in order to respond to the increasing diversity of older adults and care providers. In terms of future research on DEPs, program evaluation must attend to the importance of consistent measures, translation of knowledge to practice, and sustainability.
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 | 0.026 | 0.098 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.024 | 0.024 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".