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Record W2150620088 · doi:10.3109/01942638.2010.489543

Development and Pilot Testing of the Challenge Module: A Proposed Adjunct to the Gross Motor Function Measure for High-Functioning Children with Cerebral Palsy

2010· article· en· W2150620088 on OpenAlexafffund
Ashlea Wilson, Abi Kavanaugh, Rosemarie Moher, Megan McInroy, Neena Gupta, Nancy M. Salbach, F. Virginia Wright

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2010
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsRasch modelCerebral palsyGross motor skillAdjunctPhysical medicine and rehabilitationMotor functionPsychologyPhysical therapyGross Motor Function Classification SystemMotor skillTest (biology)AudiologyMedicineDevelopmental psychology

Abstract

fetched live from OpenAlex

The aim was to develop a Challenge Module (CM) as a proposed adjunct to the Gross Motor Function Measure for children with cerebral palsy who have high-level motor function. Items were generated in a physiotherapist (PT) focus group. Item reduction was based on PTs' ratings of item importance and safety via online surveys. The proposed CM items were pilot-tested with children in Gross Motor Function Classification System Level I. The focus group identified 35 items for consideration. The first item-reduction survey (n = 86 PT respondents) resulted in 20 items. A second survey yielded two additional items. Seven pilot-test participants (6-14 years) had a CM total mean score of 74.5% (SD = 19.4). Three easy items were subsequently removed and two items combined. Of seven additional items suggested by the children during testing, two were accepted in a third item-reduction survey. The final result was a 20-item CM to evaluate advanced motor skills. The CM requires refinement through Rasch scaling and formal validation.

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 score0.046
Threshold uncertainty score0.365

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 head0.039
GPT teacher head0.274
Teacher spread0.235 · 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

Citations39
Published2010
Admission routes2
Has abstractyes

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