Passive coping is a risk factor for disabling neck or low back pain
Bibliographic record
Abstract
BACKGROUND: Despite evidence suggesting that coping is an important concept in the study of pain, its role in predicting the development of disabling pain has not been previously studied. To assess the relationship between coping and the development of disabling pain. METHODS: From a random sample of adults, we formed a cohort of individuals with non-disabling neck and/or low back pain (n=571). Participants were followed 6 and 12 months after the index survey. Coping was measured with the Vanderbilt Pain Management Inventory. The Chronic Pain Questionnaire was used to measure the presence of disabling neck and/or low back pain. We used Cox proportional hazards regression analyses to investigate the role of passive coping in the development of disabling pain while controlling for confounders. RESULTS: Passive coping was a strong, independent risk factor for disabling neck and/or back pain. Those using moderate to high levels of passive coping strategies were at an over five-fold increased risk of developing disabling pain (Moderate: HRR=5.19, 95% CI=1.78-15.1; High: HRR=6.80, 95% CI=2.36-19.6). Active coping was not found to be a significant risk factor for disabling neck and/or back pain. CONCLUSION: Passive coping is a strong and independent predictor of disabling neck and/or back pain. This strong relationship identifies passive coping as a marker for risk of disability and can allow for the identification of individuals at risk and in need of intervention to aid in improving their overall adjustment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".