Factor Structure and Internal Validity of the Functional Movement Screen in Adults
Bibliographic record
Abstract
The factor structure and internal consistency of the Functional Movement Screen (FMS) have not been examined in a general healthcare population. Replicating the factor structure of the FMS is important because it illustrates the interdependence between each of the subtests, enabling the strength and conditioning professional to better interpret and act on an individual's FMS score. Anthropometric data and FMS scores were collected from 1,113 clients of a multidisciplinary healthcare clinic in Vancouver, BC The mean (SD) ages were 53.4 (11.1) for men (n = 656) and 49.3 (12.3) for women (n = 457). The mean FMS Summary Score was 13.7 (2.9) and was significantly negatively correlated with both age (r = -0.25; p < 0.001) and body mass index (r = -0.37; p < 0.001). The internal consistency of the FMS scale, which was assessed with both ordinal and Cronbach's alpha, was 0.73 and 0.64, respectively. Polychoric correlations between individual movements ranged from 0.03 to 0.59. Exploratory and confirmatory factor analyses (CFA) revealed that the FMS showed 2 main factors, a basic movement factor (shoulder mobility and active straight leg raise) and a complex movement factor (squat, hurdle step, inline lunge, and the trunk stability push-up). Rotary stability loaded onto both factors in the CFA, and its exclusion from the model had little effect. The findings of this study broadly replicated the intended factor structure of the FMS, as the individual movements aligned well with the intended factors.
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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 | 0.010 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".