What are the essential components of a self-management program designed to help workers with chronic low back pain stay at work? A mapping review
Bibliographic record
Abstract
For many workers suffering from chronic low back pain (CLBP), the main challenge after a disabling episode is not returning to work in itself, but rather sustaining this reinstatement. The goal of this study was to identify key elements that should be included in a self-management (SM) program in order to facilitate a sustainable return to work for patients suffering from LBP. We conducted a mapping review to examine the current evidence surrounding this issue in four databases (CINAHL, PudMed, Scopus, Cochrane Library). Key content elements of SM programs, as well as facilitators/barriers associated with sustainable RTW were extracted and analysed. Only three studies that met our eligibility criteria. Results from these studies suggest that, in the context of RTW, the two most valuable components of an SM program are educational materials and strategies specifically tailored to the work context. Among this admittedly scarce evidence, we were able to identify valuable elements that should be included in SM programs in order to promote a sustainable RTW. Additional studies assessing the effectiveness of both current SM programs and programs developed based on our recommendations will be called for to further support our results.
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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 | 0.009 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.020 | 0.028 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".