ENGAGEMENT IN ADVANCE CARE PLANNING: DO REGION-WIDE INTERVENTIONS WORK?
Bibliographic record
Abstract
Background Prior research suggests that only a small percentage of the general population is involved in ACP. Aim To compare engagement in ACP among the general population of Canadian adults with the engagement among adults in a health authority with a region-wide ACP engagement initiative (Fraser Health (FH), British Columbia). Methods An on-line opinion poll of a nationally representative sample of 1523 respondents including five questions regarding core ACP activities. Pearson χ2tests were used to compare the prevalence of ACP in FH and the rest of Canada. Results Compared to the rest of Canada, respondents from FH had higher levels of ACP awareness (20% against 15%, p=0.025) and higher rates of ACP discussions with family and friends (59% against 51%, p=0.004). However, they had lower rates of written ACPs (15% against 20%, p=0.018). Discussion The population of adults in FH tend to talk more with their family and friends about ACP than do adults in the rest of Canada. The fact that a lower number of respondents had written ACPs in FH could be explained by the fact that while FH had engaged professionals and the public around ACP, legislation supporting ACP was only recently declared. Conclusion Engagement with the public by a health authority makes a difference in the levels of ACP awareness and discussions with family and friends. However, regulatory frames need to be in place in order to provide optimal support to ACP interventions.
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 | 0.025 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".