Impact of Health Education Programme on Adherence to Treatment in Knee Osteoarthritis: An Interventional Study on Egyptian Patients
Bibliographic record
Abstract
AIM: To measure the level of adherence of patients with primary knee osteoarthritis (KOA) to an interventional therapeutic and rehabilitation programme and investigate factors that hinder patients' adherence. METHODS: A total of 154 participants with primary knee osteoarthritis (KOA) were divided into intervention and control groups. The intervention protocol included patient education on the nature and treatment of KOA, therapeutic exercise, a weight loss programme for overweight patients, and a physical therapy programme. Participants were followed for 3 months. The Visual Analog Scale for Pain (VAS-p), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and knee Kellgren-Lawrence OA grading were measured before and after the intervention. Additionally, the Morisky adherence questionnaire and the WHO Multidimensional Framework for factors affecting adherence were assessed. RESULTS: One fifty four participants with KOA were randomly allocated into intervention and control groups. A low level of adherence was detected in both groups (68.8% in the intervention group vs. 84.4% in the control group). Patients who followed the interventional programme were more adherent. Adherence to therapy was associated with a reduction in the Visual Analog Scale for Pain (VAS-p) (p = 0.016) and improved function as measured by WOMAC (p = 0.018). Factors primarily associated with patient non-adherence included unemployment (67.8%), low income (59.3%), no previous response to therapy (58.5%), less frequent follow-up visits (55.1%), lack of insurance (66.9%), difficult access to services (59.3%), and high cost of services (55.1%). CONCLUSION: Adherence to treatment in OA patients is a significant concern and a common problem, appearing to be associated more with socioeconomic factors than with pain and function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".