MétaCan
Menu
Back to cohort

Factor Structure and Internal Validity of the Functional Movement Screen in Adults

2015· article· en· W998241624 on OpenAlexafffundabout
Michael S. Koehle, Boaz Y. Saffer, Nadine M. Sinnen, Martin J. MacInnis

Bibliographic record

VenueThe Journal of Strength and Conditioning Research · 2015
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCronbach's alphaFunctional movementConfirmatory factor analysisSquatExploratory factor analysisInternal consistencyTrunkPopulationPsychologyPhysical therapyPhysical medicine and rehabilitationMedicineStatisticsPsychometricsMathematicsDevelopmental psychologyStructural equation modeling

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.180

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.060
GPT teacher head0.351
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueThe Journal of Strength and Conditioning ResearchSame topicSports injuries and preventionFrench-language works237,207