Understanding Needs for Chronic Musculoskeletal Pain Management in a Northern Dene and Métis Community: A Community Based Needs Assessment
Bibliographic record
Abstract
Background: Chronic musculoskeletal (MSK) pain disproportionately affects Indigenous Peoples, and rural/remote communities face significant barriers in accessing care. La Loche, a Dene/Métis community in northern Saskatchewan, has limited access to specialized chronic pain management services and specialized health providers. Aims: The aim of this needs assessment was to gain insight into the community's priorities, strengths, and concerns regarding chronic MSK pain management. Community engagement and relationship building were essential to ensure that cultural protocols were respected and community worldviews were accurately represented. Methods: A community-directed needs assessment was conducted in collaboration with local health care providers and community members. To ensure appropriate representation of community-led priorities, reflexive thematic analysis was utilized and rooted within interpretive description and informed by community-based participatory research and Two-Eyed Seeing. Open discussions were conducted in person, over the phone, or via Zoom in a semistructured format. Thirteen individuals were interviewed (eight community members, five health care professionals). Results: Interviews conducted with community members and health care providers were analyzed separately. Both yielded the same four major overarching themes: (1) impact of pain on daily living, (2) barriers limiting access to care and the understanding of pain between health care provider and patient, (3) systemic oppression and negative experiences with health care, and (4) strength-based solutions. Conclusions: Five recommendations were developed to promote culturally safe and patient-centered environments for chronic MSK pain communication and future care delivery: (1) person-centered and community-directed care, (2) clinic model and staffing requirements, (3) practitioner education and awareness, (4) community education and awareness, and (5) community resources.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".