THE FUNCTIONAL MOVEMENT TEST 9+ IS A POOR SCREENING TEST FOR LOWER EXTREMITY INJURIES IN PROFESSIONAL MALE FOOTBALL
Bibliographic record
Abstract
Background The Nine Plus screening battery test (9+) is a series of 11 tests, used to assess limitations in fundamental movement patterns assumed to predispose athletes for injury. Objective To examine the association of the 9+ with lower extremity injuries, and to identify the optimal cut-off point for risk screening. Design Prospective cohort study. Setting Professional football league. Participants Male professional football players in Qatar. Interventions The 9+ test was performed prior to the 2013 and 2014 seasons. Time-loss injuries and exposure in training and matches were registered prospectively by club medical staff during 2 consecutive seasons. Univariate and multivariate regression analyses were used to calculate odds ratios (ORs), risk ratios (RR) and 95% confidence intervals (CIs). Receiver operating characteristics (ROC) curves were calculated to determine sensitivity and specificity, and identify the optimal cut-off point for risk assessment. Main Outcome Measurement Lower extremity injuries. Results In total, 363 players completed the 9+ and had injury and exposure registration. There were 527 injuries among 204 players (56.2%) during the 2 seasons; injuries to the thigh were most frequent. There was no association between 9+ total score and the risk of lower extremity injuries (OR, 1.02; 95% CI, 0.98–1.06;P=0.44), even when adjusted for exposure (RR, 1.04; 95% CI, 0.98–1.12;P=0.21) or other factors in a multivariate analysis (OR, 1.04; 95% CI, 0.97–1.06; P=0.60). ROC curve analysis revealed an area under the curve of 0.48 for lower extremity injury. No optimal cut-off point to distinguish between injured and non-injured players could be determined. Conclusions The 9+ total score was not associated with lower extremity injury. The 9+ total score was no better than chance for classifying injured and non-injured players. Therefore, the 9+ test cannot be recommended as a screening tool in this population.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".