Qualitative Study of Health Care Providers' Uptake of the Project Extension for Community Health Outcomes for Chronic Pain
Bibliographic record
Abstract
INTRODUCTION: There is an enormous need for pain education among all health care professions before and after licensure. The study goal was to explore generic and chronic pain-specific factors that influenced uptake of a continuous education program for chronic pain, the Project Extension for Community Health Outcomes (ECHO) CHUM Douleur chronique. METHODS: The study team conducted 20 semistructured virtual interviews among participants of the program. Interviews were transcribed verbatim, and two analysts used a reflexive thematic analysis approach to generate study themes. RESULTS: Five aspects facilitating engagement, continued participation, and uptake of the Project ECHO were identified: rapid access to reliable information, appraising one's knowledge, cultivating meaningful relationships, breaking the silos of learning and practice, and exponential possibilities of treatment orchestrations for a complex condition with no cure. Although participants' experiences of the program was positive overall, some obstacles to engagement and continued participation were identified: heterogeneity of participants' profiles, feelings of powerlessness and discouragement in the face of complex incurable pain conditions, challenges in applying recommendations, medical hierarchy, and missed opportunity for advocacy. DISCUSSION: Many disease-specific and contextual factors contributed to an increased motivation to participate in the ECHO program. Some elements, such as the complexity of diagnosis and treatment, and the multidisciplinary requirements to manage cases were identified as elements motivating one's participation in the program but also acting as a barrier to knowledge uptake. These must be understood in the broader systemic challenges of the current health care system and lack of resources to access allied health care.
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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 | 0.018 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".