Assessment of muscle strength in para-athletes: A systematic review of observational studies
Bibliographic record
Abstract
Accurate and reliable evaluation of muscle strength in para-athletes is essential for monitoring the effectiveness of strength training and/or rehabilitation programmes, and sport classification. Our aim is to synthesise evidence related to assessing muscle strength in para-athletes. Four databases were searched from January 1990 to July 2021 for observational studies focusing on strength assessment. Independent screening, data extraction, and quality assessment were performed in duplicate. A total of 1764 potential studies were identified. Thirty met the inclusion criteria and were included in the review. The mean age of participants was 30.7 years (standard deviation [SD]: 2.4). The majority were men (88%) participating in wheelchair sports, including basketball, rugby, and tennis (23/30: 76%). Overall quality varied, with more than half of the studies failing to identify strategies for dealing with confounding variables. Despite manual muscle testing being a standard component of para-sport classification systems, evidence examining strength characteristics in para-athletes is derived primarily from isometric and isokinetic testing. In studies that included comparative strength data, findings were mixed. Some studies found strength values were similar to or lower than able-bodied athletic controls. However, an important observation was that others reported higher shoulder strength in para-athletes taking part in wheelchair sports than both able-bodied and disabled non-athletes. Studies need to develop accessible, standardised strength testing methods that account for training influence and establish normative strength values in para-athletes. There is also a need for additional studies that include female para-athletes and para-athletes with greater functional impairments.
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How this classification was reachedexpand
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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".