Changes in perceived stress during a mindfulness-based stress reduction (MBSR) intervention predicting occupational recovery from work-related stress: a longitudinal study
Bibliographic record
Abstract
Abstract Purpose The Mindfulness-Based Stress Reduction (MBSR) group intervention is increasingly being used in clinics to alleviate stress-related symptoms. The aim was to evaluate the association between pre-post changes in levels of perceived stress during the MBSR program and occupational recovery from prolonged work-related stress. Potential moderators of the association were assessed. Methods This study was based on secondary analyses of pre-existing data from 450 patients commencing an MBSR program between 15 October 2015 and 2 April 2019. Data on clinical, sociodemographic, and psychosocial factors were collected via an online survey administered at baseline and the end of the MBSR program. Pre-post changes in levels of perceived stress were evaluated using Cohen’s Perceived Stress Scale (PSS-10). The outcome was stable (versus unstable) employment for at least four consecutive weeks evaluated at 26-week and 52-week follow-ups. Missing data were managed with multiple imputation. Associations were analyzed using logistic regression, with adjustment for confounding factors from clinical, occupational, and psychosocial factors in the latest held job. Results The average reduction in PSS-10 scores was 5.0 (SD = 5.5). Each one-point pre-post reduction on the PSS-10 scale was associated with a lower risk of full-time sick-leave at 26-week (OR = 1.12, 95% CI = 1.04, 1.20) and 52-week follow-up (OR = 1.19, 95% CI = 1.09, 1.30). None of these associations were moderated by any predictors. Conclusion A greater reduction in levels of perceived stress during participation in an MBSR program, predicts enhanced occupational recovery from long-term work-related stress.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".