Meaningful engagement of patients and families in a complex trial of advance care planning in primary care
Bibliographic record
Abstract
Engagement of Patient and Family Advisors (PFAs) is increasingly recommended as best practice in research. During the design and conduct of a large trial of advance care planning (ACP) in primary care, we expanded on the funder’s (Patient-Centered Outcomes Research Institute®) requirement for an engagement plan and sought to develop an innovative approach to fostering and sustaining meaningful engagement of PFAs throughout all phases of the trial. Structures were developed that integrated PFAs into planning and provided the foundation for their ongoing participation. A continuous quality improvement approach became the framework for ongoing engagement. This involved setting goals; collecting data through surveys, interviews, and observations; and using data to inform revisions to the engagement approach. We also tracked PFA activities and ideas and documented how they impacted the trial. This article summarizes our experience and describes the challenges we faced and how we addressed them. We also outline key lessons learned about encouraging participation; approaches to preparation and coaching; fostering equity across PFAs and other roles in the trial team; creating a range of opportunities that match PFA skills, preferences, and expectations; the importance of regular feedback; and the need for training of all trial staff. Our experience demonstrates that successful and impactful engagement is possible but requires consistent commitment and intentional dedication of sufficient resources. Experience Framework This article is associated with the Patient, Family & Community Engagement lens of The Beryl Institute Experience Framework (https://theberylinstitute.org/experience-framework/). Access other PXJ articles related to this lens. Access other resources related to this lens.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".