Comparative Study of Core and Diaphragmatic Strengthening Versus Standard Physiotherapy on Core Stability, Forced Vital Capacity, and Clinical Outcomes in Non-Specific Low Back Pain
Bibliographic record
Abstract
Background: Non-specific low back pain (NSLBP) is a leading cause of disability worldwide. Traditional physiotherapy often focuses on general strengthening and posture correction, whereas core and diaphragmatic strengthening exercises target both spinal stability and respiratory function. However, the comparative effects of these two approaches on core stability, forced vital capacity (FVC), and clinical outcomes have not been adequately studied. Objective: To compare the effects of core and diaphragmatic strengthening exercises versus standard physiotherapy on core stability, forced vital capacity, and clinical outcomes in individuals with non-specific low back pain. Methods: This prospective cohort study involved 60 participants diagnosed with NSLBP. Participants were assigned to two groups based on their treatment preferences or clinical indication: Group 1 (Core and Diaphragmatic Strengthening) and Group 2 (Standard Physiotherapy). Group 1 received exercises aimed at improving core stability and diaphragmatic function, while Group 2 received standard physiotherapy focused on general strengthening, stretching, and postural education. Outcomes were measured at baseline, 4 weeks, and 8 weeks, including core stability (McGill Trunk Muscle Endurance Test), forced vital capacity (spirometry), and clinical outcomes (Visual Analog Scale for pain and Oswestry Disability Index). Results: Both groups showed significant improvements in core stability, FVC, and clinical outcomes. Group 1 demonstrated greater improvements in trunk endurance (p<0.05) and forced vital capacity (p<0.05) compared to Group 2. Additionally, pain and disability scores improved more significantly in Group 1, with a greater reduction in VAS (p<0.05) and ODI (p<0.05). Conclusion: Core and diaphragmatic strengthening exercises appear to be more effective than standard physiotherapy in improving core stability, forced vital capacity, and clinical outcomes in individuals with non-specific low back pain. These findings suggest that incorporating core and diaphragmatic exercises into rehabilitation programs for NSLBP may lead to better outcomes. Key words: Non-specific low back pain, core stability, diaphragmatic strengthening, forced vital capacity, physiotherapy, clinical outcomes, trunk endurance.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".