Systematic Review of Prognostic Factors for Return to Work in Workers with Sub Acute and Chronic Low Back Pain
Bibliographic record
Abstract
Purpose We systematically reviewed the evidence on factors that predict duration of sick leave in workers after 6 weeks low back pain (LBP) related sick leave. We hypothesized that different factors affect the duration of the leave depending on the time away from work. Methods The review occurred in seven phases: (1) developing the central question, (2) conducting the literature search, (3) identifying relevant publications, (4) quality appraisal, (5) data extraction, (6) evidence synthesis, and (7) knowledge translation. We searched for studies that reported episodes of LBP and sick leave that lasted more than 6 weeks. All included studies reported at least one prognostic factor where return to work was the outcome. Results We identified twenty-two relevant publications. The impact of pain, functional status and radiating pain seems to change with duration of work disability. Workers' recovery expectations remain important after 6 weeks. Modified duties are rarely studied in later phases of work disability. Depression/mental health did not appear to be an important factor in later phases. Workplace physical factors remain important. There is insufficient evidence that pain catastrophising and fear avoidance are predictive factors in later phases. There was moderate evidence for age in the later phases. Functional capacity and claim related factors were supported by some evidence. Discusion Physical demands in the workplace are preventing workers from getting back to work in a timely fashion across phases. The psychosocial work environment is understudied in later phases. Overall, we cannot conclude that prognostic factors change over time.
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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 | 0.010 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".