Reductions in Perceived Injustice are Associated with Reductions in Pain Catastrophizing in Individuals with Low Back Pain
Bibliographic record
Abstract
Purpose: This study examined whether reductions in pain catastrophizing were associated with reductions in perceived injustice in individuals with occupational low back pain receiving physical therapy combined with a brief psychological intervention (Empowered Relief) to improve pain self-management skills. Methods: A secondary analysis of a quasi-experimental study was conducted with 63 participants with subacute and chronic low back pain. Perceived injustice and pain catastrophizing were measured at baseline (T1) and four weeks post-intervention (T2). Correlation and regression analyses were performed to identify predictors of changes in perceived injustice. Ethical approval was obtained from the Université de Sherbrooke Research Ethics Board (#2022-3392). Results: < 0.001). Regression analyses revealed that pain stage and reductions in pain catastrophizing were significantly associated with decreases in perceived injustice. Regression analyses also revealed that reductions in the "rumination" subscale of pain catastrophizing significantly predicted changes in both subscales of perceived injustice. Conclusion: The results demonstrate that reductions in pain catastrophizing are associated with reductions in perceived injustice during the subacute phase. The findings also shed light on shared mechanisms between pain catastrophizing and perceived injustice, emphasizing the role of rumination. The findings from this study underscore the importance of early psychological intervention for occupational low back pain, particularly in the subacute phase to improve recovery.
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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 | 0.004 |
| 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 | 0.001 |
| 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".