Dynamic Neuromuscular Stabilization Exercise and Chronic Lumbar Disc Herniation: Effects on Pain, Mobility, and Trunk Endurance—A Randomized Controlled Trial
Bibliographic record
Abstract
ABSTRACT Background This randomized controlled trial investigated the effects of an 8‐week Dynamic Neuromuscular Stabilization (DNS) exercise program on pain intensity, lumbar range of motion, functional disability, and trunk muscle endurance in women with chronic lumbar disc herniation. Methods A total of 30 women aged 30–40 years with chronic lumbar disc herniation (L4–L5 or L5–S1, pain duration ≥ 3 months, Visual Analog Scale (VAS) 3–7) were randomly assigned to either an experimental group ( n = 15), performing DNS exercises (45–60 min, 3 times/week for 8 weeks), or a control group ( n = 15), continuing routine physical activity (self‐directed walking/light stretching). Pain intensity was measured using the VAS, lumbar range of motion using the modified Schober test, functional disability using the Oswestry Disability Index (ODI), and trunk muscle endurance using the McGill endurance test. Data were analyzed using Paired and independent t ‐tests to assess within‐ and between‐group differences (SPSS v25, p < 0.05). Results The control group showed no significant changes ( p > 0.05). In contrast, the experimental group demonstrated significant improvements in all outcome variables ( p < 0.05). Postintervention comparisons revealed significant between‐group differences favoring the experimental group across all measures ( p < 0.007). Pain intensity decreased by 4.0 (95% CI: −4.5 to −3.5), lumbar range of motion increased by 5.0 cm (95% CI: 4.2 to 5.8), functional disability decreased by 26.2 (95% CI: −29.1 to −23.3), and trunk flexor endurance increased by 24.4 s (95% CI: 20.1 to 28.7). Conclusion An 8‐week DNS program significantly reduced pain, improved lumbar mobility, decreased functional disability, and enhanced trunk muscle endurance in women with chronic lumbar disc herniation, suggesting its potential as an effective rehabilitation strategy.
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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 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".