The Effect of a Virtual Reality-Mediated Gamified Rehabilitation Program on Pain, Disability, Function, and Balance in Knee Osteoarthritis: A Prospective Randomized Controlled Study
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Bibliographic record
Abstract
Background: This prospective randomized controlled study is the first study that evaluates the disease-specific gamification through virtual reality (VR) glasses on pain, disability, functionality, and balance in knee osteoarthritis (OA). Materials and Methods: The demographic data of the patients were recorded. A total of 73 patients were divided into two groups (35 in experimental group and 38 in control group). All patients were evaluated with pain (visual analog scale [VAS]), functionality (Lysholm functional knee score [LFKS], 6 minutes walking test [6MWT]), disability (Western Ontario and McMaster Universities Arthritis Index [WOMAC]), and balance ( Berg Balance Scale [BBS] ) before treatment, after treatment (3th weeks), and 4 weeks after treatment (7th weeks). In the experimental group, plus the conservative treatment, a total of 15 sessions of a disease-specific gamification through VR glasses were applied. Results: VAS and WOMAC scores of the experimental group were lower at the 3th and 7th weeks than those of the control group ( P = 0.005, P = 0.000), ( P = 0.000). LFKS of the experimental group was higher at the 3th and 7th weeks than that of the control group ( P = 0.005, P = 0.013). No difference was found between the groups in terms of 6MWTs ( P > 0.05). BBS score of the experimental group was higher in the 7th week than that of the control group ( P = 0.021). Conclusion: In knee OA, the disease-specific gamification through VR glasses added to the conservative treatment has a positive effect on pain, functionality, and balance. Side effects such as mild nausea, headache that did not last long, require additional treatment. In light of this, disease-specific gamification through VR glasses is effective and safe in knee OA, more studies that reveal the long-term effect on structural healing must be planned.
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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 | 0.030 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it