Pediatric Project ECHO <sup>®</sup> : A Virtual Community of Practice to Improve Palliative Care Knowledge and Self-Efficacy among Interprofessional Health Care Providers
Bibliographic record
Abstract
Background: Health care providers (HCPs) require ongoing training and mentorship to fully appreciate the palliative care needs of children. Project ECHO ® (Extension for Community Healthcare Outcomes) is a model for delivering technology-enabled interprofessional education and cultivating a community of practice among HCPs who care for children with life-limiting illness. Objectives: To develop, implement, and evaluate the Project ECHO model within the pediatric palliative care (PPC) context. Specific objectives were to evaluate (1) participation levels, (2) program acceptability, (3) HCP knowledge changes, (4) HCP self-efficacy changes, and (5) perceived practice changes after six months. Intervention: An interprofessional PPC curriculum was informed by a needs assessment. The curriculum was delivered through monthly virtual 90-minute TeleECHO sessions (didactic presentation and case-based learning) from January 2018 to December 2019. The program was freely available to all HCPs wishing to participate. Design: A mixed-methods design with repeat measures was used. Surveys were distributed at baseline and six months to assess outcomes using 7-point Likert scales. Descriptive and inferential statistical analyses were conducted. The study was approved by the Research Ethics Board at the Hospital for Sick Children. Results: Twenty-four TeleECHO sessions were completed with a mean of 32 ± 12.5 attendees. Acceptability scores ( n = 43) ranged from 5.1 ± 1.1 to 6.5 ± 0.6. HCPs reported improvements in knowledge and self-efficacy across most topics (11 out of 12) and skills (8 out of 10) with demonstrated statistical significance ( p < 0.05). Most participants reported positive practice impacts, including enhanced ability to provide PPC in their practice. Conclusion: Project ECHO is a feasible and impactful model for fostering a virtual PPC-focused community of practice among interprofessional HCPs.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".