Relationship Between Functional Movement Screen, Lower Quarter Y-Balance Test and Physical Performance Tests in Athletes
Bibliographic record
Abstract
Context: The Functional Movement Screen (FMS) and lower quarter Y-Balance Test (LQ-YBT) are examples of functional screening tools used to identify physical dysfunction or functional asymmetries. Limitations in flexibility, agility and power may also have negative consequences on performance in fundamental movements in sport. Due to the time constraints of physical therapists and athletic trainers providing care towards athletes during rehabilitation and treatment hours, it is not possible to perform multiple screening tests/tools prior to an athletic season to determine if athletes have poor mobility and fundamental movements that may alter sport performance. Understanding associations between movement performance and global screening tools (FMS and LQ-YBT) could provide a foundation for prevention programs and performance enhancement for athletes. Therefore, this study was performed to identify how FMS composite score and LQ-YBT relate to the measures of physical performance (flexibility, agility, and jump) in athletes. Settings and Design: A Cross-sectional study conducted on university athletes. Methods and Material: Demographic and Anthropometric data of 50 athletes (32 males,18 females) in the age group of 18 – 30 years were collected at the beginning of the test after obtaining informed consent. The seven FMS tasks, LQ-YBT, Sit and Reach Test, ProAgility Test and Standing Long Jump were performed sequentially in the order. A total of 3 trials were performed in each test and the average of three trials were recorded for statistical analysis. Statistical analysis used: Pearson correlation was used to assess the association between FMS C.S, LQ-YBT and other physical performance measures and p < 0.05 was utilized for statistical significance. Results: FMS CS and LQ-YBT showed significant positive correlation with standing long jump performance (p<0.05) but not with agility. LQ-YBT correlated significantly with sit and reach test (p<0.05). Conclusions: In athletes, the observed significant correlation between the FMS composite score (FMS CS) and the Lower Quarter Y Balance Test (LQ-YBT) with standing long jump performance suggests their potential utility in predicting jump capabilities. However, their lack of correlation with agility indicates limited applicability in that domain. Notably, the LQ-YBT's significant correlation with the sit and reach test underscores its potential as an indicator of flexibility. Key message: Utilizing the FMS or LQ-YBT autonomously or in pair might help sports medicine and strength and conditioning experts in their capacity to recognize people with an expanded gamble of injury during sports participation through distinguishing proof of physical or functional movement deficiencies. Keywords Agility, Flexibility, Functional Asymmetries, Power, Quality of Movement
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".