The Trajectory of Chronic Pain: Can a Community‐Based Exercise/Education Program Soften the Ride?
Bibliographic record
Abstract
The entire primary care record of six patients attending a community-based education/exercise self-management program for chronic noncancer pain (YMCA Pain Exercise/Education Program [Y-PEP]) was reviewed. Medical visits, consultations and hospital admissions were coded as related or unrelated to their pain diagnoses. Mood disruption, financial concerns, conflicts with employers/insurers, analgesic doses, medication side effects and major life events were also recorded. The 'chronic pain trajectory' resembled a roller coaster with increased health care visits at the time of initial injuries and during 'crises' (reinjury, conflict with insurers/employers, failed back-to-work attempts and life events). Visits decreased when conflicts were resolved. Analgesic doses increased during 'crises' but did not fall after resolution. After attending Y-PEP, health care use fell for four of six patients and two returned to work. Primary care physicians need to recognize the functional limitations and psychosocial complications experienced by their chronic pain patients. A program such as Y-PEP may promote active self-management strategies resulting in lowered health care use.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".