Lessons Learned from the Chronic Pain Clinic: A Qualitative Study of the Perspectives of Healthcare Providers
Bibliographic record
Abstract
Aim: The chronic pain clinic (CPC) was established to address chronic non-cancer pain and opioid-related harm. Materials & methods: Employing community participatory research design First Nation Metis representatives, clinicians and a researcher collectively agreed to document lessons learned from healthcare providers' perspective, 1 year post-clinic-implementation. 17 individual interviews were conducted. Results: Thematic analysis revealed that a multidisciplinary team offered client-centered care, education, counseling and multimodal treatment options. Medication reviews and case management ensured patient safety. Communication and education of community providers enhanced pain management capacity ensuring safe opioid prescribing. Evidence-based best practices were implemented through system-level monitoring. Access to Indigenous healing strategies provided culturally responsive spiritual care upon request. Conclusion: The multidisciplinary and multimodal CPC care model effectively manages chronic non-cancer pain.
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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 | 0.019 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".