Cost Analysis of a Home-Based Virtual Reality Rehabilitation to Improve Upper Limb Function in Stroke Survivors
Bibliographic record
Abstract
Loss of arm function occurs in up to 85% of stroke survivors. Home-based telerehabilitation is a viable approach for upper limb training post-stroke when rehabilitation services are not available. Method: A costing analysis of a telerehabilitation program was conducted under several scenarios, alongside a single-blind two-arm randomized controlled trial with participants randomly allocated to control (N=25) or intervention group (N=26). Detailed analysis of the cost for two different scenarios for providing telerehabilitation were conducted. The fixed costs of the telerehabilitation are an important determinant of the total costs of the program. The detailed breakdown of the costs allows for costs of future proposed telerehabilitation programs to be easily estimated. The costs analysis found that a program supplying all required technology costs between CAD$475 per patient and CAD$482 per patient, while a program supplying only a camera would have total costs between CAD$242 per patient and $245 per patient. The findings of this study support the potential implementation of telerehabilitation for stroke survivors for improving accessibility to rehabilitation services. This cost-analysis study will facilitate the implementation and future research on cost-effectiveness of such interventions.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".