The Long-term Effect of Multidisciplinary Back Training
Bibliographic record
Abstract
In Brief Study Design. Systematic review of randomized controlled trials. Objectives. To determine the long-term effect of multidisciplinary back training on the work participation of patients with nonspecific chronic low back pain. Summary of Background Data. Chronic low back pain is influenced by multiple factors. Multidisciplinary back training represents one of the options to take this multiplicity into account. So far, only evidence of the short-term effectiveness of this approach in terms of work participation is available. Methods. Electronic databases were searched and the references of various articles were screened for relevant publications. Ten studies met the inclusion criteria. All included studies were evaluated for their methodologic quality. Results. Five of the studies had a low methodologic quality. All high-quality studies found a positive effect on at least one of the 4 outcome measures used. Based on our criteria, effectiveness was found for the outcome measures of work participation and quality of life. No effectiveness was found for experienced pain and functional status. The intensity of the intervention seems to have no substantial influence on the effectiveness of the intervention. Conclusion. In the long-term, multidisciplinary back training has a positive effect on work participation in patients with nonspecific chronic low back pain. In this survey, the long-term effectiveness of multidisciplinary back training in terms of work participation by chronic patients with low back pain was evaluated. A systematic review of randomized controlled trials was performed. A positive effect of multidisciplinary back training on work participation was found.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.084 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.011 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".