Pain coping in injured workers with chronic pain: what’s unique about workers?
Bibliographic record
Abstract
Purpose: Pain caused by a work injury is a complex phenomenon comprising multiple factors, e.g. age, gender, prior health status, occupation, job demands, and severity of injury. Little research has focused on injured workers with chronic pain. This study investigates injured workers’ pain coping. Methods: A descriptive cross-sectional study design was used to measure coping strategies of injured workers in a work rehabilitation program. Differences in coping strategies by demographics, injury-related variables, pain, disability, and depression were measured. Results: n = 479. The coping strategy with the highest mean score was “coping self statements” (Mean = 19.4, SD = 7.6), followed by “praying/hoping” (Mean = 18.2, SD = 9.7), and “catastrophizing” (Mean = 17.5, SD = 8.0). Statistical differences for coping strategies were noted between gender, marital status, depression levels, self-perceived disability levels, and pain (p < 0.01 for all). Conclusions: This study provided relevant information about how injured workers cope with pain. In conditions in which there may be a perceived lack of control (high pain intensity, high self-perceived disability, and high self rated depression), there were significantly higher amounts of both “catastrophizing” and “praying and hoping”. Therefore, workers with high pain and high self-perceived disability are more likely catastrophize their pain, leading to poor recovery outcomes.Implications for RehabilitationDepression is common in injured workers with chronic pain.Depressed injured workers use more catastrophizing to cope with pain and this may lead to poor recovery.Perceived control over pain could be a mitigating factor in recovery from an occupational injury.Workers with high ratings of pain and high perceived disability often catastrophize their pain and this could lead to poor recovery outcomes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 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".