Interlimb Symmetry Characteristics Among Male and Female Athletes: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: (1) To summarize the literature, (2) determine sex differences, and (3) determine the changes under exercise-induced fatigue, in biomechanical lower-limb interlimb asymmetries in healthy adult male and female athletes, including those with a history of injuries. LITERATURE SEARCH: We searched MEDLINE, Web of Science, EMBASE, and CINAHL databases from inception to March 7, 2025 (PROSPERO; registration number: CRD42023417697). STUDY SELECTION: Studies were included if they assessed lower-limb interlimb biomechanical asymmetry, or compared or reported biomechanical values for both lower limbs in adult male and female athletes. RESULTS: Sixty-four studies (5837 athletes) were included. Forty studies compared sex-specific asymmetries. Fourteen studies reported significant sex differences in healthy athletes in asymmetry in hip abductor strength, explosive power, and kinetic measures commonly in females, as well as in quadriceps and hamstring strength in both males and females, while 11 studies found no sex differences. Five studies investigated asymmetries in healthy athletes with a history of injuries and reported sex differences in explosive power, and no sex differences for balance and knee muscle strength. Asymmetry in explosive power was more commonly noted in female healthy athletes (peak power [Females: 17.21 (0.07) > males: 12.81 (0.06)], P<.05, effect size = 0.33) and healthy athletes with a history of injury (asymmetry (%) [males: 95.4%, P = .003; females: 96.5%, P = .049]). A meta-analysis was not performed due to study heterogeneity. No studies assessed sex-specific asymmetry under exercise-induced fatigue. CONCLUSION: Sex-specific biomechanical lower-limb asymmetry remained inconsistent, with generally no sex differences except asymmetry in explosive power, which was more commonly reported in female athletes. High-quality studies are needed to address these gaps. JOSPT Open 2026;4(1):36-60. Epub 3 December 2025. doi:10.2519/josptopen.2025.0137
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".