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Record W2067511016 · doi:10.1519/jsc.0b013e3182576fa6

Normative Data for the Functional Movement Screen in Middle-Aged Adults

2012· article· en· W2067511016 on OpenAlexaff
Fraser T. Perry, Michael S. Koehle

Bibliographic record

VenueThe Journal of Strength and Conditioning Research · 2012
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNormativeBody mass indexPsychologyReference valuesPhysical activityBalance (ability)GerontologyPhysical therapyPhysical medicine and rehabilitationMedicineInternal medicine

Abstract

fetched live from OpenAlex

The functional movement screen (FMS) is an easily administered and noninvasive tool for identifying weaknesses and asymmetry during exercises and daily activity. The clinical utility of FMS is currently limited by its lack of normative reference values. This study aimed to fill this void by providing normative reference values for healthy, middle-aged adults. Furthermore, we hypothesized that FMS would be affected by other factors such as age, body mass index (BMI), exercise participation, and Balance Error Scoring System scores. Six hundred and twenty-two healthy adults were assessed based on their performance on the 7-Point FMS. A higher level of exercise participation was associated with higher FMS scores, whereas higher BMI and age were associated with lower FMS scores. There was a significant difference between individuals with high (>30) and moderate BMIs (F[621] = 33.98, p < 0.0001). The normative reference values presented can be used in clinical practice to identify abnormal scores across a broad age spectrum.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.156
GPT teacher head0.430
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), 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

Citations123
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Strength and Conditioning ResearchSame topicBalance, Gait, and Falls PreventionFrench-language works237,207