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Record W2009417780 · doi:10.3109/01942638.2010.525601

A Multivariate Model of Determinants of Change in Gross-Motor Abilities and Engagement in Self-Care and Play of Young Children With Cerebral Palsy

2010· article· en· W2009417780 on OpenAlexafffund
Lisa A. Chiarello, Robert J. Palisano, Doreen J. Bartlett, Sarah Westcott McCoy

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2010
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsCerebral palsyPsychological interventionGross motor skillPsychologyRehabilitationOccupational therapyDevelopmental psychologyClinical psychologyGerontologyMotor skillMedicinePsychiatry

Abstract

fetched live from OpenAlex

A multivariate model of determinants of change in gross-motor ability and engagement in self-care and play provides physical and occupational therapists a framework for decisions on interventions and supports for young children with cerebral palsy and their families. Aspects of the child, family ecology, and rehabilitation and community services may influence children's activity and participation. Aspects of the child include primary and secondary impairments, associated and comorbid health conditions, and adaptive behaviors. Literature support for the model is reviewed. A clinical scenario illustrates the use of the model as a framework for practice. The model encourages therapists to broaden the focus of rehabilitation services for young children with CP to include not only development of motor abilities but also comprehensive interventions and supports to enhance participation in daily activities and routines. Therapists are encouraged to consider how child, family, and service factors interact when planning interventions and evaluating outcomes.

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)0.008
metaresearch head score (Gemma)0.015
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 score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.039
GPT teacher head0.325
Teacher spread0.286 · 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

Citations65
Published2010
Admission routes2
Has abstractyes

Explore more

Same venuePhysical & Occupational Therapy In PediatricsSame topicCerebral Palsy and Movement DisordersFrench-language works237,207