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Record W2049629519 · doi:10.3109/17518423.2013.827755

Development and validity of the early clinical assessment of balance for young children with cerebral palsy

2013· article· en· W2049629519 on OpenAlexaff
Sarah Westcott McCoy, Doreen J. Bartlett, Allison Yocum, Lynn Jeffries, Alyssa LaForme Fiss, Lisa A. Chiarello, Robert J. Palisano

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2013
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsWestern University
Fundersnot available
KeywordsCerebral palsyCronbach's alphaConstruct validityPsychologyCeiling effectMovement assessmentInternal consistencyBalance (ability)Physical therapyGross motor skillMotor skillGross Motor Function Classification SystemContent validityPhysical medicine and rehabilitationDevelopmental psychologyPsychometricsMedicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVES: Validity of the Early Clinical Assessment of Balance (ECAB), to monitor postural stability in children with cerebral palsy (CP), was evaluated. METHODS: 410 children with CP, 1.5 to 5 years old, participated. Physical therapists scored children on the Movement Assessment of Infants Automatic Reactions section and Pediatric Balance Scale. Through consensus, researchers selected items from both measures to create the ECAB. Content and construct validity were examined through item correlations, comparison of ECAB scores among motor ability, age and gender groups and correlations with the Gross Motor Function Measure 66 basal and ceiling (GMFM-66-B&C). RESULTS: Internal consistency was high (Cronbach's alpha = 0.92). ECAB differed significantly among motor ability, children <31 months old scored lower than older children, but there was no difference between boys and girls. ECAB and GMFM-66-B&C scores correlated strongly (r = 0.97). CONCLUSION: Validity of the ECAB was supported. Reliability and responsiveness need study.

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)0.005
metaresearch head score (Gemma)0.020
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 score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.302
Teacher spread0.275 · 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

Citations45
Published2013
Admission routes1
Has abstractyes

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