Study on Carryover Effect of Mulligan’s Mobilization with Movement under Water Versus Land Based Mulligan’s Mobilization with Movement on Functional Mobility of Knee Joint
Bibliographic record
Abstract
Background: Knee osteoarthritis causes pain and functional disability more commonly in elderly population. Knee osteoarthritis is not only the most common type of arthritis but also causes greater disability and clinical symptoms. This study has been done to find out and compare the carryover effects of Mulligan’s mobilization with movement with and without water. Methods: Ethical clearance was obtained from Institutional Ethical Committee, KIMSDU, Karad. An experimental study was conducted with 84 subjects which were divided into two groups using consecutive sampling with random allocation was done. Group A was treated with under water Mulligan’s MWM and Group B was treated with land based Mulligan’s MWM. The outcome measures used were Visual Analogue Scale (VAS), Western Ontario and McMaster Universities index (WOMAC) and 30 seconds sit to stand test. Results: Pre-interventional analysis done for VAS, WOMAC and 30 Second sit to stand test showed no significant difference with p values 0.1931, 0.9408, 0.4580 respectively. Post-interventional analysis done for VAS showed Not quite significant difference, p=0.0768, for WOMAC no significant difference (p= 0.9919) and 30 seconds sit to stand score showed very significant difference (p=0.0044) Conclusion: The study concludes that there is very significant effect of underwater Mulligan’s mobilization with movement on functional mobility of knee joint.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".