Relationship Between Knee Walking Kinematics and Muscle Flexibility in Runners
Bibliographic record
Abstract
CONTEXT: Decreased flexibility in muscles and joints of lower extremities is commonly observed in runners. Understanding the effect of decreased flexibility on knee walking kinematics in runners is important because, over time, altered gait patterns can make runners vulnerable to overuse injuries or degenerative pathologies. OBJECTIVES: To compare hamstring and iliotibial-band (ITB) flexibility and knee kinematics in runners and nonrunners. DESIGN: A descriptive, comparative laboratory study. SETTING: Hamstring and ITB flexibility were measured with the active knee-extension test and the modified Ober test, respectively, in both groups of participants. Three-dimensional (3D) walking kinematic data were then recorded at the knee using a motiontracking system. PARTICIPANTS: 18 runners and 16 nonrunners. MAIN OUTCOME MEASURES: Knee-extension angle (hamstring flexibility) and hip-adduction angle (ITB flexibility). Knee kinematic parameters of interest included knee angle at initial contact, peak knee angles, and knee-angle range in all planes of movement. RESULTS: The runners had a significantly less flexible ITB than the nonrunners (hip adduction [-] and adduction [+] angles, 3.1° ± 5.6° vs -.4° ± 4.5°; P < .001). The runners demonstrated a greater mean tibial external-rotation angle at initial contact (7.3° ± 5.8° vs 2.0° ± 4.0°; P = .01) and a smaller mean peak tibial internal-rotation angle (-1.6° ± 3.0° vs -4.2° ± 3.2°; P = .04) than the nonrunners. CONCLUSION: This study provides new insight into the relationship between muscle flexibility and 3D knee kinematics in runners. This supports the premise that there is an association between muscle flexibility and transverse-plane knee kinematics in this population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".