Pain as a mediator of sleep problems in arthritis and other chronic conditions
Bibliographic record
Abstract
OBJECTIVE: To examine the associations between arthritis and insomnia symptoms and unrefreshing sleep, as well as the role of pain as a mediator of these relationships. METHODS: Analyses were conducted on the cross-sectional, nationally representative, weighted sample of adults > or =18 years of age (n = 118,336) in the 2000/2001 Canadian Community Health Survey. Four logistic regression models were estimated for each sleep problem (model 1: arthritis only; model 2: model 1 + sociodemographic characteristics, lifestyle factors, and other chronic conditions; model 3: model 2 + mental health [stress, depression]; and model 4: model 3 + pain). Mediation by pain was quantified by the percentage change in the effect of arthritis on a particular sleep problem by comparing models 3 and 4. RESULTS: The prevalence of insomnia symptoms and unrefreshing sleep in persons with arthritis was 24.8% and 11.9%, respectively. These estimates are twice as high as those for persons without arthritis. In multivariate regression analyses, the addition of pain decreased the effect of arthritis by 53% (insomnia symptoms) and 64% (unrefreshing sleep). The effect of arthritis was still statistically significant in these models, suggesting that pain is a partial mediator of these relationships. CONCLUSION: Insomnia symptoms and unrefreshing sleep affect a considerable proportion of individuals with arthritis. Pain mediates a substantial amount of the relationship between arthritis and sleep problems. Better pain management could significantly improve sleep in individuals with arthritis.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".