EFFECTIVENESS OF STABILITY BALL EXERCISES COMBINES WITH ERGONOMIC SETTING IN PREGNANCY RELATED LOW BACK PAIN. A RANDOMIZED CONTROL TRIAL
Bibliographic record
Abstract
Background: Pregnancy related low back pain (PR-LBP) is very common, which affects activities of daily life including work, sleep, physical activity and compromise the quality of life. The prevention PR-LBP through physical therapy is uncommon in Pakistani population. Objective: to determine the effectiveness of stability ball exercises (SBE) in combination with ergonomic training (ET) in pregnancy related low back pain (PR-LBP). Methodology: A single blinded, randomized clinical trial was conducted at physical therapy department of Haleema Siraj Hospital Rawalpindi Pakistan. A total of n=90, who were coming to the clinic for follow-up, fulfilled the inclusion criteria and were thus recruited through non-probability convenient sampling technique. The study participants were randomly divided in to two groups i.e. SBE (n=45) and combination of SBE with ES (n=45), through lottery method. Quebec disability scale (QDS) was used to determine the functional disability. Results: The mean age of study participants was 26.5±4.56723 years. Significant improvement was observed in both groups with larger effect size throughout the treatment duration (p<0.05).Conclusion: SBE and combination of SBE with ES significantly reduced low back pain and functional disability Keywords: activities of daily living, disability, ergonomic, posture, pregnancy, pregnancy related low back pain, stability ball exercises.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| 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 | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".