The Canadian STOP-PAIN Project
Bibliographic record
Abstract
OBJECTIVES: The Canadian STOP-PAIN Project assessed the human and economic burden of chronic pain (CP) in individuals on waitlists of Canadian multidisciplinary pain treatment facilities. This article focuses on sex differences. Objectives were to (1) determine the pain characteristics and related biopsychosocial factors that best differentiated women and men with CP; and (2) examine whether public and private costs associated with CP differed according to sex. MATERIALS AND METHODS: Sample consisted of 441 women and 287 men who were evaluated using self-administered questionnaires and a structured interview protocol. A subsample (233 women and 137 men) recorded all pain-related expenditures in a comprehensive diary over 3 months. RESULTS: Results revealed that the burden of illness associated with CP was comparable in both sexes for average and worst pain intensity, pain impact on daily living, quality of life, and psychological well-being. The same was true for pain-related costs. The results of a hierarchical logistic regression analysis, in which sex was treated as the dependent variable, showed that factors that differentiated men and women were: work status, certain circumstances surrounding pain onset, present pain intensity, intake of particular types of pain medication, use of certain pain management strategies, pain beliefs, and utilization of particular health care resources. DISCUSSION: This study suggests that women and men who are referred to multidisciplinary pain treatment facilities do not differ significantly in terms of their pain-related experience. However, the aspects that differ may warrant further clinical attention when assessing and managing 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".