Functional Movement Screen Task Scores and Joint Range-of-motion: A Construct Validity Study
Bibliographic record
Abstract
Little is known about the construct validity of the Functional Movement Screen (FMS). We aimed to assess associations between FMS task scores and measures of maximum joint range-of-motion (ROM) among university varsity student-athletes from 4 sports (volleyball, basketball, ice hockey, and soccer). Athletes performed FMS tasks and had their maximum ankle, hip and shoulder ROM measured. Multivariable linear regression was used to estimate associations between FMS task scores and ROM measurements. 101 university student-athletes were recruited (52 W/49 M; mean age 20.4±1.9 years). In general, athletes with higher FMS task scores had greater ROM compared to those with lower task scores. For example, athletes who scored 2 on the FMS squat task had 4° (95% CI, 1° to 7°) more uni-articular ankle dorsiflexion ROM compared with those who scored 1, while those who scored 3 on the FMS squat task had 10° (4° to 17°) more uni-articular ankle dorsiflexion ROM compared with those who scored 1. Large variation in ROM measurements was observed. In sum, substantial overlap in joint ROM between groups of athletes with different FMS task scores weakens the construct validity of the FMS as an indicator of specific joint ROM.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".