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Record W2133514702 · doi:10.1093/ptj/80.6.598

A Multivariate Model of Determinants of Motor Change for Children With Cerebral Palsy

2000· article· en· W2133514702 on OpenAlexaff
Doreen J. Bartlett, Robert J. Palisano

Bibliographic record

VenuePhysical Therapy · 2000
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcMaster UniversityWestern University
Fundersnot available
KeywordsCerebral palsyMultivariate statisticsPsychological interventionIntervention (counseling)PsychologyMultivariate analysisGross Motor Function Classification SystemConceptual modelVariety (cybernetics)Developmental psychologyConceptual frameworkMotor skillPhysical medicine and rehabilitationClinical psychologyMedicineComputer scienceArtificial intelligenceMachine learningPsychiatrySociologySocial science

Abstract

fetched live from OpenAlex

The purpose of this article is to describe the development of a theory- and data-based model of determinants of motor change for children with cerebral palsy. The dimensions of human functioning proposed by the World Health Organization, general systems theory, theories of human ecology, and a philosophical approach incorporating family-centered care provide the conceptual framework for the model. The model focuses on relationships among child characteristics (eg, primary and secondary impairments, personality), family ecology (eg, dynamics of family function), and health care services (eg, availability, access, intervention options). Clarification of the complex multivariate and interactive relationships among the multiple child and family determinants, using statistical methods such as structural equation modeling, is necessary before determining how physical therapy intervention can optimize motor outcomes of children with cerebral palsy. We propose that the development and testing of multivariate models is also useful in physical therapy research and in the management of complex chronic conditions other than cerebral palsy. Testing of similar models could provide physical therapists with support for: (1) prognostic discussions with clients and their families, (2) establishment of realistic and attainable goals, and (3) interventions to enhance outcomes for individual clients with a variety of prognostic attributes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.342

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 head0.048
GPT teacher head0.311
Teacher spread0.263 · 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

Citations122
Published2000
Admission routes1
Has abstractyes

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