Enhancing Primary Care: The Role of Occupationnal Therapy in Chronic Pain Self-Management
Bibliographic record
Abstract
Context: One in five Canadians lives with chronic pain which significantly affects their daily activities and quality of life. Necessary healthcare services to manage chronic pain remain difficult to access in primary care. Occupational therapists play a central role in supporting patients in the adoption and daily use of pain self-management strategies and in learning how to adapt to their chronic condition to maintain their quality of life. Objective: The objective of this study was to make explicit how occupational therapists provide self-management support to people living with chronic pain to highlight their specific contribution to primary care teams. Study design and analysis: A qualitative descriptive research design was used. Semi-structured group interviews lasting 120 minutes were conducted with three groups of five occupational therapists. Data collected was analyzed by two co-researchers using NVivo and an inductive thematic analysis and content analysis approach. Setting: Quebec, Canada Population studied: Occupational therapists providing chronic self-management support interventions. Instruments: The Teams video conferencing platform and the Mentimeter interactive presentation software were used for data collection and recording. Results: It was made explicit that occupational therapy interventions aim to empower people living with chronic pain to develop their own competencies to 1) get inform and understand their condition, 2) use effectively self-management strategies and 3) self-regulate their daily and meaningful activities to manage chronic pain. Occupational therapists use specific treatment modalities not only to educate people with chronic pain but also to allow them to progressively experiment, assess, adopt and develop a routine that integrates personalized and effective self-management strategies. Conclusions: Occupational therapy can be a great addition to primary care team services for people living with chronic pain since it is a privileged context for making accessible essential self-management support services.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".