Sex differences in response to rehabilitation treatment for musculoskeletal pain: the mediating role of post-traumatic stress symptoms
Bibliographic record
Abstract
Aim: Numerous investigations have revealed sex differences in recovery outcomes in individuals who have sustained work-related musculoskeletal injuries (WRMIs). Previous research has also revealed significant sex differences in the prevalence and severity of post-traumatic stress symptoms (PTSS) following musculoskeletal injury. This study investigated whether PTSS mediated sex differences in recovery outcomes in individuals receiving treatment for a work-related musculoskeletal injury. The recovery outcomes of interest in the present study were pain severity and pain-related disability. Methods: The study sample included 137 individuals (68 men; 69 women) with WRMIs who were enrolled in a 7-week physical rehabilitation program. Participants completed measures of pain severity, pain disability and PTSS at admission and termination of the physical rehabilitation program. Results: Consistent with previous research, independent samples t-tests revealed that women obtained significantly higher baseline scores on measures of pain severity (P < 0.01), number of pain sites (P < 0.001), depression (P < 0.001) and PTSS (P < 0.001) compared to men. Also consistent with previous research, the measure of PTSS, assessed at baseline, was prospectively associated with treatment-related disability reduction (P < 0.01), and return to work (P < 0.01). Bootstrap regression analyses revealed that PTSS partially mediated the relation between sex and pain-related disability. Conclusions: The results of the present study suggest that the experience of PTSS might be one of the factors that explain sex differences in recovery outcomes following a WRMI. The results call for greater attention to the assessment and intervention of PTSS in individuals who have sustained WRMIs.
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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) | 0.000 | 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) | 0.003 | 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".