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Record W83228000 · doi:10.3233/prm-2008-00035

Physical function for children and youth with cerebral palsy: Item bank development for computer adaptive testing

2008· article· en· W83228000 on OpenAlexaff
Carole A. Tucker, Stephen M. Haley, Helene M. Dumas, Maria A. Fragala-Pinkham, Kyle Watson, George E. Gorton, Kathleen Montpetit, Nathalie Bilodeau

Bibliographic record

VenueJournal of Pediatric Rehabilitation Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsShriners Hospitals for Children - Canada
Fundersnot available
KeywordsComputerized adaptive testingCerebral palsyItem bankItem response theoryCognitionConceptual frameworkCognitive skillTest (biology)PsychologyPhysical medicine and rehabilitationPatient-Reported Outcomes Measurement Information SystemAdaptive functioningDomain (mathematical analysis)Adaptive behaviorPhysical therapyDevelopmental psychologyPsychometricsMedicinePsychiatry

Abstract

fetched live from OpenAlex

The purposes of this paper are to: 1) present a conceptual framework that supports development of a computer adaptive test (CAT) outcome measure of physical functioning for children with cerebral palsy; 2) illustrate the development and refinement of an item bank for use in the CAT; and 3) describe the intended application of these newly developed items in a CAT platform. Improvement in physical functioning is one of the most important developmental and rehabilitative outcomes for children with cerebral palsy (CP). Computer adaptive testing technology provides means to improve outcome measures. We adopted a conceptual framework appropriate to support a CAT of physical functioning consisting of 4 sub-domains: lower extremity skills, upper extremity skills, physical activity, and global physical health. Review of existing tests and measures of physical function, expert clinician review, and cognitive testing were used to identify, develop and refine sets of items (item banks) that reflect the breadth of each sub-domain. These item banks will be used to develop contemporary parent-report instruments by application of Item Response Theory (IRT) analyses, leading to a CAT outcome measure. Such CAT approaches can efficiently assess broad areas of physical functioning across a wide age-range and levels of severity of 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)0.001
metaresearch head score (Gemma)0.001
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 score0.038
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.025
GPT teacher head0.257
Teacher spread0.232 · 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

Citations14
Published2008
Admission routes1
Has abstractyes

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