The impact of a children’s palliative care education and mentoring program (Project ECHO) on healthcare providers’ knowledge, confidence, and attitudes in Bhutan
Bibliographic record
Abstract
BACKGROUND: Palliative care services are unavailable for the vast majority of children in Bhutan. Children's palliative care has not been incorporated into training programs for health professions, leading to limited knowledge and awareness of how best to support children facing serious or life-threatening conditions. OBJECTIVES: To describe the impact of the Project ECHO children's palliative care course on participants' knowledge, comfort, and attitudes and to evaluate the overall acceptability of an online training to support palliative care training in Bhutan. METHODS: Before-and-after surveys of program participants were conducted, assessing changes in knowledge, comfort, and attitudes. Participants' overall experiences and acceptability of the learning program were assessed through an end-of-program survey. RESULTS: Participants were primarily nurses (49%) or physicians (34%). Most participants (68%) worked in pediatric and/or neonatal care. Participants' knowledge of core palliative care concepts improved significantly between the beginning and end of the course. Participants' comfort and attitudes toward palliative care also improved, with significance effect sizes in most domains (11/18). Satisfaction with the program was high, with 100% of participants agreeing that the training was applicable to their clinical practice. Although most participants (56%) identified a personal need for additional clinical training to support practice change. SIGNIFICANCE OF RESULTS: Project ECHO can be used to deliver palliative care education, with improved palliative care knowledge, comfort, and attitudes among program participants. A short online training program can generate interest in palliative care, which can be leveraged to further develop palliative care services in settings where palliative care is currently unavailable.
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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 | 0.003 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".