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Record W2085526001 · doi:10.3109/01942630903454930

Reliability of the Functional Mobility Scale for Children with Cerebral Palsy

2010· article· en· W2085526001 on OpenAlexaff
Adrienne Harvey, Meg E. Morris, H. Kerr Graham, Rory Wolfe, Richard Baker

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2010
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsPopulation Health Research Institute
Fundersnot available
KeywordsCerebral palsyGross Motor Function Classification SystemFunctional movementMedicinePhysical therapyKappaReliability (semiconductor)Gross motor skillPhysical medicine and rehabilitationMotor skillMathematicsPsychiatry

Abstract

fetched live from OpenAlex

This study examined inter-rater reliability of the Functional Mobility Scale (FMS) for children with cerebral palsy (CP) and the presence of rater bias. A consecutive sample of 118 children with CP, 2-18 years old (mean 10.3 years, SD 3.6), was recruited from a hospital setting. Children were classified using the gross motor function classification system (GMFCS) with 13 in Level I, 49 in Level II, 44 in Level III, and 12 in Level IV. Each child was independently scored on the FMS by two raters. Raters were randomly assigned from a sample of 44 orthopaedic surgeons, hospital-based physiotherapists, and community-based physiotherapists. Quadratic weighted kappa coefficients for mobility ratings varied from 0.86 to 0.92 for the three distances, indicating substantial chance corrected agreement. Levels of agreement were similar when administering the scale in person and by telephone, suggesting that the FMS can be administered by either method. There was a tendency for surgeons to rate mobility higher than physiotherapists, however, only one of the comparisons was statistically significant. The FMS is a reliable tool that can be used by clinicians to assess mobility in children with CP.

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)0.000
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 score0.004
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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

Citations109
Published2010
Admission routes1
Has abstractyes

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