Chronic Pain in Canada ‐ Prevalence, Treatment, Impact and the Role of Opioid Analgesia
Bibliographic record
Abstract
OBJECTIVE: To assess the prevalence, treatment and impact of chronic pain in Canada. METHODS: A stratified random sample of 2012 adult Canadians (weighted by sex, age and region according to 1996 census data) was surveyed by telephone in 2001 to determine the prevalence of chronic pain, defined as continuous or intermittent pain for at least six months. A second sample of 340 chronic pain sufferers who were taking prescription medication for their pain was studied in detail to determine current therapeutic approaches and to assess the social and economic impact of chronic pain. RESULTS: Chronic noncancer pain was reported by 29% of the respondents, with increased frequency in women and older age groups. The average duration of pain was 10.7 years and the average intensity was 6.3 (on a scale from 1 to 10), with 80% reporting moderate or severe pain. Anti-inflammatory agents were prescribed for 49% of respondents and opioid analgesics were prescribed for 22% (two-thirds of these were codeine). Almost 70% were worried about addiction potential, and one-third felt that strong analgesics should be reserved for terminal illnesses. Almost one-half were unable to attend social and family events, and the mean number of days absent from work in the past year due to chronic pain was 9.3. INTERPRETATION: Chronic noncancer pain is common in Canadian adults and has a major social and economic impact. Despite growing evidence supporting the efficacy and safety of major opioid analgesics for chronic noncancer pain, less than 10% of chronic pain patients taking prescription medication were treated with a major opioid. Chronic pain is undertreated in Canada, and major opioid analgesics are probably underutilized in the management of moderate to severe pain as part of a multidisciplinary treatment program.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".