Chronic Pain: The Extra Burden on Canadian Women
Bibliographic record
Abstract
HEALTH ISSUE: Chronic pain is a major health problem associated with significant costs to both afflicted individuals and society as a whole. These costs seem to be disproportionately borne by women, who generally have higher prevalence rates for chronic pain than do men. KEY FINDINGS: Data obtained from 125,574 respondents to the Canadian Community Health Survey (2000-2001) indicated that 18% of Canadian women suffered from chronic pain, compared to 14% of men. This gender discrepancy, however, seemed to be linked primarily to differences in age, income, and education between adult men and women in this large sample. Age, income, depression and functional interference with activities were strongly associated with chronic pain in general. No gender differences were found in the intensity of pain experienced. Ethnicity was not strongly associated with chronic pain prevalence, although Asians were the group with the highest chronic pain prevalence in the over-65 age group and Aboriginal Canadians had the highest prevalence in the under-65 age group. DATA GAPS AND RECOMMENDATIONS: Current gaps in our knowledge include the types of chronic pain women experience, their impact on domestic responsibilities and parenting and health care utilization patterns of women with chronic pain. Data sources such as provincial databases of billing claims may be useful in the future to enrich our knowledge of health care utilization and analgesic medication use. Enhanced surveillance, assessment, and early identification of pain disorders are recommended to improve outcomes. Considering current demographic patterns toward an older population, there is also some urgency to the development of patient education and self-management programs.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.002 |
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".