The annual incidence and course of neck pain in the general population: a population-based cohort study
Bibliographic record
Abstract
Although neck pain is a common source of disability, little is known about its incidence and course. We conducted a population-based cohort study of 1100 randomly selected Saskatchewan adults to determine the annual incidence of neck pain and describe its course. Subjects were initially surveyed by mail in September 1995 and followed-up 6 and 12 months later. The age and gender standardized annual incidence of neck pain is 14.6% (95% confidence interval: 11.3, 17.9). Each year, 0.6% (95% confidence interval: 0.0-1.1) of the population develops disabling neck pain. The annual rate of resolution of neck pain is 36.6% (95% confidence interval: 32.7, 40.5) and another 32.7% (95% confidence interval: 25.5, 39.9) report improvement. Among subjects with prevalent neck pain at baseline, 37.3% (95% confidence interval: 33.4, 41.2) report persistent problems and 9.9% (95% confidence interval: 7.4, 12.5) experience an aggravation during follow-up. Finally, 22.8% (95% confidence interval: 16.4, 29.3) of those with prevalent neck pain at baseline report a recurrent episode. Women are more likely than men to develop neck pain (incidence rate ratio=1.67, 95% confidence interval 1.08-2.60); more likely to suffer from persistent neck problems (incidence rate ratio=1.19, 95% confidence interval 1.03-1.38) and less likely to experience resolution (incidence rate ratio=0.75, 95% confidence interval 0.63-0.88). Neck pain is a disabling condition with a course marked by periods of remission and exacerbation. Contrary to prior belief, most individuals with neck pain do not experience complete resolution of their symptoms and disability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".