Examining the feasibility, acceptability and preliminary efficacy of an Immersive Virtual Reality-Assisted Lower Limb Strength Training for Knee Osteoarthritis (VRiKnee): A Mixed-Method Pilot Randomized Controlled Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND . OBJECTIVE To study the feasibility, acceptability and preliminary efficacy of an immersive virtual reality (VRiKnee) assisted lower limbs exercise for knee osteoarthritis (OA). METHODS A convergent parallel mixed-method study was conducted in 30 participants with knee OA. After 1:1 randomization, the VRiKnee group (n=15) were assigned to perform repetitive concentric quadriceps and isometric vastus medialis oblique exercise in an immersive environment using head-mount display (HMD) for 12 weeks. The control group (n=15) completed the same exercises without VRiKnee. VRiKnee participants were interviewed at week 12 to study their acceptability and user experience. Quantitative data included feasibility outcomes such as recruitment, dropout and exercise adherence rates, and effectiveness outcomes such as the Numeral Rating Scale, Western Ontario and McMaster University Osteoarthritis Index (100 points) pain and function subscales and objective physical activity measured by metabolic equivalents (METs) using ActivPAL accelerometer. Qualitative data were analyzed by thematic analysis, followed by integration with quantitative data using joint displays. RESULTS The recruitment rate was 100%, with enrollment of 30 participants in 7.57 weeks. The median age was 63.5 (IQR 61.8-66.3) years, with 76.7% female. The dropout rate was 13.3% in VRiKnee and 6.7% in control. Median exercise adherence for VRiKnee and control groups was 77.22% and 62.08%, respectively, with adherence reduction over the study period. No statistically significant differences were observed in primary and secondary outcomes, though positive trends were observed in pain and function. Cybersickness was reported by 5 participants (33.3%) in the VRiKnee group. In the qualitative analysis, 4 themes, 11 subthemes and 16 quotes were generated, identifying facilitators and barriers with practical suggestions to enhance the usability of VRiKnee. CONCLUSIONS VRiKnee demonstrated feasibility, acceptability and potential efficacy in managing knee OA. Future trials of larger sample sizes and better VR designs will confirm its role in clinical practice. CLINICALTRIAL Chinese Clinical Trial Registry (CHiCTR2100046313)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".