Work-Related Low Back Pain Treatment: A Randomized Controlled Trial from Tehran, Iran, Comparing Multidisciplinary Educational Program versus Physiotherapy Education
Bibliographic record
Abstract
STUDY DESIGN: Clinical trial. PURPOSE: To compare the multidisciplinary educational program versus physiotherapy education among Iranian nurses. OVERVIEW OF LITERATURE: Low back pain (LBP) can accompany significant occupational injuries in the nursing profession. There is no agreement on the most effective educational practice. METHODS: This study was conducted from August 17, 2014 to September 22, 2014 in Tehran, Iran. Eligible nurses with chronic mechanical LBP (n=136) were classified into an intervention group (n=66) or the control group (n=70). The intervention group received physiotherapy education for 120-minutes followed by a 120-minute health education session based on predictive constructs of social cognitive theory (SCT). The control group received the 120-minute physiotherapy education. Disability rate, pain severity and back pain prevention behavior were measured at initially and 3 months after intervention using visual analogue scale, Roland-Morris disability questionnaire and nursing low back pain preventive behaviors questionnaire. RESULTS: The two groups were the same in terms of all studied variables at the initiation of the study. At the 3-month follow up, predictive constructs of LBP preventive behaviors of participants in the intervention were improved (p<0.001). Significant decreases were evident at 3 months in pain severity (p=0.03) and disability (p=0.003). CONCLUSIONS: The designed multidisciplinary educational intervention could decrease chronic mechanical LBP in nurses.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".