The Effects of Self-Massage on Osteoarthritis of the Knee: a Randomized, Controlled Trial
Bibliographic record
Abstract
INTRODUCTION: Recent research has provided a rationale for the efficacy and use of massage therapy in the management of knee osteoarthritis (OA) symptoms. Additionally, research has also implicated the role of the quadriceps muscles in the genesis of knee OA. Although both areas of research have demonstrated strong evidence that the muscles and massage therapy may affect knee OA symptoms, self-massage applied on the quadriceps muscle has received no attention. METHODS: Conducted at the Lourdes Wellness Center in Collingswood, NJ, the study investigated the outcomes of a self-massage intervention applied to the quadriceps muscle on reported pain, stiffness, physical function, and knee range of motion in adults with diagnosed knee OA. Forty adults with diagnosed knee OA were randomly assigned to either an intervention (n = 21) or a wait list control (n = 19) group. The participants applied a narrated 20-minute self-massage therapy twice weekly during ten supervised and three unsupervised intervention sessions. The control group had four supervised assessments with no intervention. Outcome measures were the Western Ontario and McMaster's Osteoarthritis Index (WOMAC) and assessment of knee range of motion. RESULTS: Between-groups analyses of WOMAC pain, stiffness, function subscales, and total WOMAC scores indicated significant difference between groups (p < .05), n = 36). No significant differences were seen in range of motion. CONCLUSIONS: The study demonstrated that participants who have OA of the knee benefit from the self-massage intervention therapy. Further studies are needed to clarify the long-term effects of self-massage on the progression and symptoms of knee OA.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".