Exergames to improve rehabilitation after knee arthroplasty: a systematic review and grade evidence synthesis
Bibliographic record
Abstract
We aimed to systematically review and synthesise the impact of rehabilitation with games in people after knee arthroplasty. We conducted a systematic review following the Preferred Reporting Items for the declaration of Systematic Reviews (PRISMA – Preferred Reporting Items for Systematic Reviews and Meta-Analysis). The summary of evidence was developed using the Grading of Recommendations, Assessment, Development, and Assessment (GRADE). The review included randomised controlled trials that used characteristics of games in rehabilitation. Eight articles from a total of 1289 identified articles were included after duplicates were removed. In total, 239 participants participated. There were no statistically significant changes between the groups using the exergames and control groups. The level of evidence was rated using GRADE and was very low or moderate. The difference in grouped means was not significant for Knee Flexion, Knee extension, Range of Motion, WOMAC (Western Ontario and McMaster Universities Arthritis Index), AKSS (American Knee Society Score), Self-Efficacy, Five Times Sit-to-Stand Test time, Pain, or Proprioception. The results of the different studies did not find significant changes in the intervention groups with exergames in the physical domains, especially in studies with shorter interventions. Therefore, further investment in future studies on developing and evaluating games is suggested to enhance training during the recovery process.
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 | 0.041 | 0.132 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.019 |
| Bibliometrics | 0.021 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".