Red Ginger (Zingiber officinale var. rubrum) Massage Reduces Stiffness and Functional Disability in Elderly with Osteoarthritis
Bibliographic record
Abstract
Introduction: Recent research has provided data on the efficacy of the massage therapy and the role of essential oil in the management of osteoarthritis (OA) symptoms. Although both areas of research have demonstrated strong evidence that the muscles and massage with essential oil may affect OA symptoms, massage with essential oil applied on the quadriceps muscle has received no attention. The purpose of this study was to identify the effect of red ginger massage on joint stiffness and functional disability in elderly with osteoarthritis.Methods: This study was a randomized control group pre-test and post-test experimental study design involving 62 elderly with osteoarthritis divided into two groups namely red ginger massage and control groups by random cluster sampling. The instrument used was Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Statistical test used were paired t-test and MANCOVA.Results: Baseline value of stiffness and functional disability in intervention group were 4.47 ± 1.717 and 35.93 ± 12.806. After 8 weeks stiffness and functional disability became 2.40 ± 1.380 and 19.50 ± 9.420 Stiffness and functional disability were decreased on intervention group with p-value 0.000 and 0.004. It means there was influenced by red ginger massage on stiffness and functional disability in elderly with osteoarthritis.Conclusion: Red ginger massage can be applied as a complementary treatment to help reduced joint stiffness and functional disability in addition to standard drug treatment usage in osteoarthritis disease.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".