FOSTERING ENGAGEMENT: AN EXPLORATION OF INNOVATIVE DEMENTIA ENVIRONMENTS FROM FOUR COUNTRIES
Bibliographic record
Abstract
Abstract Dementia is one of the major age-related diseases and challenges those affected, societies, as well as health care systems worldwide. In an effort to better meet the needs of people living with dementia (PlwD), innovative care concepts for community-dwelling PlwD, as well as those in need for long-term care are being developed worldwide. Aiming to strengthen independence and slow down the cognitive decline, efforts concentrate on continuously engaging PlwD in activities of daily life, despite a progression of the disease. This international symposium will provide five presentations on different innovative care environments in the community, which stimulate and support an active daily life of PlwD. The first presentation dissects the care environment of Green Care Farms in the Netherlands and its effects on the engagement of residents. The second presentation discusses activity programming and self-directed behavior in Canadian long-term care. The third presentation presents social participation of PlwD in shared housing arrangements in Germany. The fourth presentation describes how the neighborhood-built environment can contribute to social health aspects for PlwD in German municipalities and the fifth presentation considers the feasibility and effectiveness of a virtual care farm activity in the United States.
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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.002 | 0.003 |
| 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".