Reliability of anaerobic and aerobic mobility performance tests used in wheelchair rugby, wheelchair basketball and wheelchair tennis: A systematic review
Bibliographic record
Abstract
Background Understanding the reliability and validity of field-based mobility and performance tests used within the wheelchair sports of basketball (WCB), rugby (WCR) and tennis (WCT) can assist in understanding an athletes’ physiological state, training effects, and/or assist with optimising their wheelchair-user interface.Purpose To examine, evaluate and synthesize current aerobic and anaerobic field-based mobility and performance tests used in WCB, WCR and WCT.Methods A systematic search was performed according to PRISMA guidelines. Studies were included if they investigated performance tests in WCB, WCR and WCT and reported reliability.Results Twenty-one studies covering 45 mobility/performance tests were included (anaerobic, n = 35; aerobic, n = 10), with agility and repeated sprints (n = 13) being the most common, followed by linear-sprints (n = 11). Repeated sprint ability (n = 2) and submaximal field-tests (n = 2) were the least frequent. Intra-class correlations among all tests ranged from 0.62 to 0.99, with agility and repeated sprints being 0.65–0.98, followed by values of 0.62–0.99 for linear-sprint, 0.96–0.99 for repeated sprints and 0.85–0.97 for submaximal field-tests.Conclusion The most frequently measured performance tests were anaerobic tests focusing on agility and repeated sprints. Given the low number of aerobic tests in WCB, WCR and WCT, future research should focus on reliable and valid ways to measure and track performance.
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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 | 0.018 | 0.104 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".