Cost effectiveness of a multi-stage return to work program for workers on sick leave due to low back pain, design of a population based controlled trial [ISRCTN60233560]
Bibliographic record
Abstract
BACKGROUND: To describe the design of a population based randomized controlled trial (RCT), including a cost-effectiveness analysis, comparing participative ergonomics interventions between 2-8 weeks of sick leave and Graded Activity after 8 weeks of sick leave with usual care, in occupational back pain management. DESIGN: An RCT and cost-effectiveness evaluation in employees sick-listed for a period of 2 to 6 weeks due to low back pain. Interventions used are 1. Communication between general practitioner and occupational physician plus Participative Ergonomics protocol performed by an ergonomist. 2. Graded Activity based on cognitive behavioural principles by a physiotherapist. 3. Usual care, provided by an occupational physician according to the Dutch guidelines for the occupational health management of workers with low back pain. The primary outcome measure is return to work. Secondary outcome measures are pain intensity, functional status and general improvement. Intermediate variables are kinesiophobia and pain coping. The cost-effectiveness analysis includes the direct and indirect costs due to low back pain. The outcome measures are assessed before randomization (after 2-6 weeks on sick leave) and 12 weeks, 26 weeks and 52 weeks after first day of sick leave. DISCUSSION: The combination of these interventions has been subject of earlier research in Canada. The results of the current RCT will: 1. crossvalidate the Canadian findings in an different sociocultural environment; 2. add to the cost-effectiveness on treatment options for workers in the sub acute phase of low back pain. Results might lead to alterations of existing (inter)national guidelines.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".