Low-back-pain related disability: An integration of psychological risk factors into the stress process model
Bibliographic record
Abstract
The purpose of this study was to verify the usefulness of an adaptation of the stress process model in organizing the psychological variables associated with the development of low-back-pain related disability. French-speaking Canadian workers on compensated sick leave (N=439) due to recent occupational low back pain (LBP) were evaluated during the sub-acute stage of LBP (between 30 and 83 days after injury). They were assessed for the following factors: life events, injury-specific cognitive appraisal, emotional distress, avoidance coping, and functional disability. Confirmatory factor analyses were used to test and modify the measurement model. An important modification in the measurement model was the association of catastrophizing with the emotional distress factor. During the sub-acute stage, path analyses revealed a satisfactory fit of the following model (the following coefficients are standardized): (a) life events (.30) and cognitive appraisal (.42) explained emotional distress (r(2)=.30); (b) emotional distress (.42) and cognitive appraisal (.36) explained the use of avoidance coping (r(2)=.45); and (c) emotional distress (.24) and avoidance coping (.56) explained functional disability (r(2)=.53). The stress model tested here reaffirms the importance of life events in the development of disability through the more established emotional distress factor. Also, cognitive appraisal appears to have an indirect effect on disability through activity avoidance and distress. This adaptation of the stress model makes it possible to integrate risk factors into a reduced set of meaningful factors and proposes a more general adaptation explanation of disability than the specific fear-avoidance model.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".