Modifying Spike Jump Landing Biomechanics in Female Adolescent Volleyball Athletes Using Video and Verbal Feedback
Bibliographic record
Abstract
Landing awkwardly from a jump is a common mechanism of injury for the anterior cruciate ligament (ACL) of the knee. Augmented feedback, such as verbal or visual instruction, has been shown to cause an immediate, positive change in landing biomechanics in a laboratory setting. No data exist on the longer term effects of feedback on jump landing biomechanics in a sports-specific setting. The purpose of this study was to explore whether providing video and verbal feedback to adolescent (12-14 years old) female volleyball athletes would improve their landing technique. Trunk and lower extremity kinematic variables were measured in 19 participants before a feedback session was provided to the intervention group (IG). Follow-up kinematic measurements of the IG were taken immediately postintervention, and again after 2 and 4 weeks. Two-way repeated measures analysis of variance (ANOVA) was used to compare the IG with a control group (CG), who received no feedback. The IG (n = 10) demonstrated increased maximal hip and trunk flexion compared with the CG (n = 9) at week 4 (p ≤ 0.05). One-way repeated measures ANOVA was used to determine if changes were evident within the IG over time. Ankle dorsiflexion, right knee and hip flexion, and trunk flexion changed significantly (p ≤ 0.05) over the 4-week period. Augmented feedback appeared to produce a positive change in landing biomechanics in adolescent female volleyball athletes performing a sports-specific skill. Courtside video and verbal feedback may present a relatively simple, cost-effective method of introducing one component of a comprehensive ACL injury prevention program at a young age.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| 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 | 0.001 |
| 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".