Short Term Effect of Mulligan's Mobilization Versus Kinesio Taping on Knee Pain and Disability for Osteoarthritis of Knee
Bibliographic record
Abstract
Background: Mulligan’s mobilization and Kinesio taping treatment techniques found to be effective on improving pain and functional disability for osteoarthritis of knee. Hence the purpose is to compare the effect of Mulligan’s mobilization and kinesio taping on improvement of pain and functional disability in subjects with osteoarthritis of knee.Method: An experimental study design, 40 subjects with osteoarthritis of knee joint randomized 20 subjects each into Mobilization Group and Taping Group. Mobilization Group was treated with Mulligan’s Mobilization and Taping Group was treated with Therapeutic Kinesio Taping thrice a week for 2 weeks. Outcome measurements such as Visual analog scale (VAS) for pain, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) for functional disability was measured before and after 2 weeks post intervention.Results: Analysis using Paired ‘t’ test and Wilcoxon signed rank test found that there is a statistically significant improvement in VAS and WOMAC within the group. Comparative analysis using Independent‘t’ test and Mann Whitney U test found there is a statistically significant difference in post-intervention means between the groups.Conclusion: The study concluded that both Mulligan’s Mobilization and Kinesio Taping techniques significantly shown short term effect on improvement of pain and functional disability for subjects with osteoarthritis of knee. However, there is no statistically significant difference in short term improvements between Mulligan’s Mobilization and Kinesio Taping. Among both, Mulligan’s Mobilization technique found clinically more effective with greater percentage of improvement than Kinesio Taping technique.
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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 | 0.001 | 0.001 |
| 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) | 0.004 | 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".