Effect of Knee Strengthening Exercises and Lifestyle Modifications Through Mobile Phone Support in People Suffering From Knee Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: The study aimed to evaluate the effectiveness of mobile phone-based support in improving exercise adherence and outcomes in knee osteoarthritis. DESIGNS: A prospective comparative cohort study was conducted with a follow-up at 3, 6, and 12 wks, involving 210 participants allocated into intervention and control groups. The intervention group received knee exercise flyers and mobile phone-based adherence support, while the control group received only standard instructions after physiotherapy. Outcome measures included Western Ontario and McMaster Universities Arthritis Index scores, numeric rating scale pain scores, and quality of life assessments at baseline and follow-ups at 3, 6, and 12 wks. RESULTS: The intervention group exhibited significant reductions in Western Ontario and McMaster Universities Arthritis Index scores, pain scores, and improvement in quality of life over the 12-wk follow-up compared to baseline. The intervention group exhibited significantly greater improvements in the outcomes as compared to control group. CONCLUSIONS: A combined intervention of knee exercises leaflets and SMS/phone call adherence support led to significant improvements in pain, functional outcomes, and quality of life among individuals with knee osteoarthritis. These findings underscore the potential of mobile phone-based interventions as effective adjuncts to traditional therapies for knee osteoarthritis.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".