Does resistance training improve pain intensity, quality of life, and disability in people with chronic nonspecific low back pain? A systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: Systematic review with meta-analysis to evaluate the efficacy of resistance training (RT) in improving pain intensity, quality of life, and disability in people with nonspecific chronic low back pain (NSCLBP) METHOD: Searches were conducted in April 2025 using MEDLINE, Scopus, Web of Science, and the Cochrane Library. Randomized controlled trials (RCTs) that compared RT interventions with any treatment and assessed pain intensity, quality of life, or disability in adults with NSCLBP were included. A pairwise random-effects meta-analysis was performed by subgroup according to the comparison treatment. Risk of bias was assessed with the Cochrane Risk of Bias 2.0 tool (RoB 2), and certainty of evidence was evaluated using the GRADE approach RESULTS: < 0.00001) favoring RT. Only pain intensity reached clinical significance. The certainty of the evidence was rated as "moderate" for all variables CONCLUSIONS: RT programs effectively reduce pain intensity and disability in patients with NSCLBP. Moderate certainty of evidence suggests that RT can be recommended for NSCLBP. Further research is required to confirm these findings PROSPERO REGISTRATION NO: CRD42024505897
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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 | 0.020 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.030 | 0.044 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".