An Online Pediatric Palliative Care Education and Mentoring (Project ECHO) in Nepal: A Program Implementation Case Study and Assessment of Changes in Healthcare Providers’ Knowledge, Confidence, and Attitudes
Bibliographic record
Abstract
OBJECTIVES: The goal of this implementation study was to describe the implementation and evaluation of the impact of an online pediatric palliative care training program in Nepal, using the Project ECHO model. METHODS: The study used mixed methods, including a program case study describing the online learning program and before-and-after surveys of program participants, assessing learning through changes in knowledge, comfort, and attitudes. An end-of-program survey was used to evaluate participants' overall experiences with the learning program and use of the learning resources. RESULTS: A literature review, stakeholder surveys, and expert input informed the design of the intervention. The course used the Project ECHO model of online education, with modifications based on the leadership team's previous ECHO experiences and local stakeholder input. The intervention occurred over 9 months, with 22 online teaching sessions. Each session consisted of a didactic lecture, case presentation, and interactive discussion with expert clinical teachers. Fifty-five clinicians in Nepal participated, including physicians (47%), nurses (44%), and psychotherapists (5%). Clinicians reported improvements in knowledge, skills, and attitudes after program participation. Program acceptability scores were high, with 93% of participants reporting that the course provided effective learning. CONCLUSIONS: Project ECHO can be successfully implemented to deliver continuing professional development in Nepal. Delivering palliative care education online using the Project ECHO model, leads to improved knowledge, skills, and attitudes for clinicians. Project ECHO suggests an innovative solution which can provide training and support to clinicians in settings where educational opportunities in palliative care are limited.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".