A model for community-led peer-facilitated advance care planning workshops for the public
Bibliographic record
Abstract
Background: The core to successful advance care planning (ACP) facilitation is helping people determine their values, beliefs and wishes, and understand substitute decision-making. Recognizing the potential for community members to support public awareness and education we developed a model of ACP education, whereby peer facilitators associated with community organizations host workshops that educate and assist members of the public with ACP. Objectives: Describe the development and evaluation of the model for community-led peer-facilitated ACP workshops for the public. Design: Descriptive mixed methods. Methods: A training curriculum and program model were co-developed with two community organizations that had been successful in delivering ACP workshops independently in their communities. Herein we describe a mixed-methods evaluation of three cycles of implementation and improvement of the model. Results: The model centers on three key concepts; the right content (based around three steps Think, Talk, Plan), the right facilitator, and the right approach. A suite of tools was designed to support the three groups involved in the delivery of the ACP workshops: the public participants, the peer facilitators, and the community-based organizations. The peer-facilitator training addresses the facilitator's learning needs of ACP content knowledge, facilitation skills, and understanding change behavior. Training evaluation data from 106 facilitators confirmed that the curriculum prepared them to facilitate the workshops. Qualitative data revealed that support from organizations with established reputations in their community is critical, with mentoring from more experienced facilitators beneficial. Conclusion: Our model demonstrates the potential of community-led, peer-facilitated ACP initiatives to enhance the capacity of community to upstream ACP conversations. Reaching a broader audience and creating a supportive, inclusive environment for individuals to comfortably learn about ACP can drive the much-needed culture shift to normalize ACP. Meaningful community engagement, empowerment, and partnerships are essential for the successful development and widespread impact of these initiatives.
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 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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".