Validity and inter-rater reliability of medio-lateral knee motion observed during a single-limb mini squat
Bibliographic record
Abstract
BACKGROUND: Muscle function may influence the risk of knee injury and outcomes following injury. Clinical tests, such as a single-limb mini squat, resemble conditions of daily life and are easy to administer. Fewer squats per 30 seconds indicate poorer function. However, the quality of movement, such as the medio-lateral knee motion may also be important. The aim was to validate an observational clinical test of assessing the medio-lateral knee motion, using a three-dimensional (3-D) motion analysis system. In addition, the inter-rater reliability was evaluated. METHODS: Twenty-five (17 women) non-injured participants (mean age 25.6 years, range 18-37) were included. Visual analysis of the medio-lateral knee motion, scored as knee-over-foot or knee-medial-to-foot by two raters, and 3-D kinematic data were collected simultaneously during a single-limb mini squat. Frontal plane 2-D peak tibial, thigh, and knee varus-valgus angles, and 3-D peak hip internal-external rotation, and knee varus-valgus angles were calculated. RESULTS: Ten subjects were scored as having a knee-medial-to-foot position and 15 subjects a knee-over-foot position assessed by visual inspection. In 2-D, the peak tibial angle (mean 89.0 (SE 0.7) vs mean 86.3 (SE 0.4) degrees, p = 0.001) and peak thigh angle (mean 77.4 (SE 1.0) vs mean 81.2 (SE 0.5) degrees, p = 0.001) with respect to the horizontal, indicated that the knee was more medially placed than the ankle and thigh, respectively. Thus, the knee was in more valgus (mean 11.6 (SE 1.5) vs 5.0 (SE 0.8) degrees, p < 0.001) in subjects with the knee-medial-to-foot than in those with a knee-over-foot position. In 3-D, the hip was more internally rotated in those with a knee-medial-to-foot than in those with a knee-over-foot position (mean 10.6 (SE 2.1) vs 4.8 (SE 1.8) degrees, p = 0.049), but there was no difference in knee valgus (mean 6.1 (SE 1.8) vs mean 5.0 (SE 1.2) degrees, p = 0.589). The kappa value and percent agreement, respectively, was >0.90 and 96 between raters. CONCLUSIONS: Medio-lateral motion of the knee can reliably be assessed during a single-leg mini-squat. The test is valid in 2-D, while the actual movement, in 3-D, is mainly exhibited as increased internal hip rotation. The single-limb mini squat is feasible and easy to administer in the clinical setting and in research to address lower extremity movement quality.
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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 | 0.014 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".