Facilitated Versus Self-Directed Educational Modalities in Palliative Care Training: A Randomized Controlled Trial of the CAPACITI Intervention
Bibliographic record
Abstract
Background: Community Access to Palliative Care via Interprofessional Teams Improvement (CAPACITI) is a virtual educational program designed to support primary care providers in delivering a palliative approach to care. This study evaluated whether expert-facilitated sessions result in greater self-rated competency than a self-directed format across three CAPACITI modules: Identification and Assessment, Communication, and Ongoing Management. Methods: We conducted a randomized controlled trial where 566 interprofessional primary care team members were randomized to facilitated or self-directed delivery of the CAPACITI program. Participants completed two validated surveys at baseline and after each module: the End-of-Life Professional Caregiver Survey and the CAPACITI Competencies survey. These assessed self-rated comfort and competency in providing palliative care. Results: Of the 566 participants randomized, 378 completed Module 1, and 270 and 192 completed Modules 2 and 3, respectively. Participants in both study arms demonstrated significant improvements in self-assessed comfort and competency following each module. No significant differences were observed between the facilitated and self-directed groups across either survey instrument. Conclusion: Participants in both the facilitated and self-directed study arms reported significant increases in self-rated comfort and competency in providing a palliative approach to care. CAPACITI demonstrates that a relatively large, intensive, and feasible training program can be implemented virtually across diverse care settings. These results support the broader application of structured, scalable educational interventions in primary care, particularly those grounded in practical content and adult learning principles. Trial registration number: ClinicalTrials.gov NCT05120154. Date registered: Oct 15, 2021. The authors affirm that this trial was registered prior to enrolling any participants.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".