Using Virtual Learning to Build Pediatric Palliative Care Capacity in South Asia: Experiences of Implementing a Teleteaching and Mentorship Program (Project ECHO)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Palliative care is an important component of pediatric cancer treatment that provides holistic support for children and their families. In low- and middle-income countries, where 98% of the children needing palliative care reside, access to palliative care services is often very limited. Training opportunities for healthcare professionals are essential to improve access to palliative care in these settings. Virtual learning, which brings training and mentorship directly to learners, can improve access to educational opportunities for staff in resource-limited settings. In this report, we describe a novel and evolving model of building pediatric palliative care (PPC) capacity in South Asia. We describe the design, implementation, challenges, and subsequent modifications of our program, as well as the impact of the program for participants and for PPC service delivery in South Asia. Our teleteaching and mentoring program (Project ECHO) [Extension for Community Healthcare Outcomes] consisted of biweekly videoconference sessions with didactic teaching and case-based discussions. The program focused on engaging participants in meaningful learning by focusing on opportunities for participant interaction through teachings and case discussions. Participants identified the program as particularly beneficial for improving their knowledge and confidence in managing seriously ill children. Project ECHO is a novel model of building PPC capacity that is suitable for resource-limited settings. Key modifications to the Project ECHO model include a course-specific leadership team, developing learning plans to address the specific learning needs of participants, focusing on ensuring learner participation during sessions, and using social media and electronic resources to create opportunities for further learning outside of ECHO sessions. These adaptations may improve the efficacy of Project ECHO and others using virtual learning programs in resource-limited settings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 it