Effect of backward walking versus home-based core program on pain and core function in non-specific low back pain: a randomized controlled trial
Bibliographic record
Abstract
Purpose. This study aimed to investigate and compare the effect of backward walking (BW) and home-based core stabilization exercises (CSE) on core muscle endurance and pain in females with non-specific low back pain (NSLBP). Materials and methods. Forty-five females with NSLBP were randomized into three equal groups: BW, CSE, and control. Core endurance was assessed using McGill’s core endurance tests (flexor endurance test, extensor endurance test, and lateral bridge tests on both sides). Pain was assessed using a visual analogue scale. Assessments were conducted at baseline and after six weeks of intervention. Results. Compared to baseline assessment, a mixed-design MANOVA revealed significant improvement in all core endurance test times in the BW and CSE groups (P < 0.05), with no significant change in the control group (P > 0.05). Both intervention groups experienced significant pain reduction after training, while the control group had significantly higher pain scores (P < 0.05). Regarding post-test group differences, core endurance improved significantly in both intervention groups compared to the control group (P < 0.05). Pain scores were significantly lower in both intervention groups compared to the control group (P < 0.05). No significant difference was detected in any outcome measures between the two intervention groups (P > 0.05). Conclusion. BW improves core muscle endurance and reduces pain in patients with NSLBP and is as effective as home-based CSE.
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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) | 0.005 | 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) | 0.007 | 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".