Muslim perspectives on advance care planning: a model for community engagement
Bibliographic record
Abstract
BACKGROUND: Advance care planning is the process of communicating and documenting a person's future health care preferences. Despite its importance, knowledge of advance care planning is limited, especially among the Islamic community. In addition, little is known about how the Islamic community views advance care planning in the context of their religious and cultural beliefs. OBJECTIVES: We aimed to increase knowledge of the importance of advance care planning, to improve health care provider and public knowledge, and to encourage dialogue between the community and health care providers. METHODS: We organized a community event and assembled a multi-disciplinary panel. Through a moderated discussion, the panel members offered their perspectives of advance care planning within a Muslim context. RESULTS: Approximately 100 individuals attended the event including community members, health care providers, medical students, and faith leaders. More than 90% of respondents rated the event as very good or excellent, found the session useful and were encouraged to reflect further on advance care planning. CONCLUSION: This event was successful in raising awareness about advance care planning within the Islamic community as well as educating health care providers on Islamic views. This model of community and health care provider engagement may also be beneficial for other faith groups wishing to discuss advance care planning within their respective religious and cultural contexts.
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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 | 0.014 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.007 |
| 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".