Individual characteristics influencing the general population’s level of knowledge of end-of-life practices: a cross-sectional study
Bibliographic record
Abstract
Background: Informed end-of-life decision-making requires a high level of death literacy. We still know little about the general population's level of knowledge and its determinants. Aim: To assess knowledge of the general population regarding the legal status and definitions of various end-of-life practices, and to compare the level of knowledge according to individual characteristics known to influence death literacy. Design: A self-administered questionnaire featuring two evolving vignettes was used to assess participants' knowledge relating to the legal status of various end-of-life practices and whether these practices are Medical Aid in Dying (MAiD), which is legal in Canada. The questionnaire also assessed participants' individual characteristics such as their experience as caregivers for someone who received palliative care, their perception of health, and their financial situation. Setting/participants: Participants were community-based community-based Canadian adults able to read French or English. Results: In total, 27% of the participants associated the description of care withholding with MAiD, 39% incorrectly associated the description of continuous palliative sedation with MAiD, and 34% incorrectly indicated that the described intervention was illegal. Having cared for someone who received palliative care, at a younger age, a higher level of education, and having participated in advance care planning were associated with better knowledge regarding end-of-life practices. Conclusion: Gaps in knowledge about end-of-life practices exist in the general population, they are associated with different individual characteristics and may limit citizens' capacity to engage in informed end-of-life decision-making. Community-based interventions adapted to different audiences are essential to ensure a quality end-of-life for all.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".