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Record W2040766119 · doi:10.3109/17483107.2010.532285

Responsiveness of the Seated Postural Control Measure and the Level of Sitting Scale in children with neuromotor disorders

2010· article· en· W2040766119 on OpenAlexafffund
Debra A. Field, Lori Roxborough

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2010
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsSunny Hill Health Centre for Children
FundersUniversity of British ColumbiaChild and Family Research Institute
KeywordsSittingPhysical therapyCerebral palsyPsychologyRating scalePhysical medicine and rehabilitationMedicineDevelopmental psychology

Abstract

fetched live from OpenAlex

PURPOSE: Responsiveness of the Seated Postural Control Measure (SPCM) and the Level of Sitting Scale (LSS) was explored for children with neuromotor disorders. Total change scores for alignment (SPCM-A), function (SPCM-F) and sitting ability (LSS) were compared with a criterion change measure, the Global Change Scale (GCS). The a priori hypotheses predicted moderate correlations (r>0.40). METHOD: Both SPCM and LSS were administered twice, 6 months apart. Parents and two therapists rated changes in alignment and function, and indicated importance of those changes on the GCS. Participants (n=114) were divided into two groups: those whose posture was expected to change, (with a range of diagnoses) and those who were expected to remain stable (with a diagnosis of cerebral palsy). Ages ranged from 1 to 18 years. RESULTS: Fair-to-moderate significant correlations (p ≤0.01) were found between SPCM-F and LSS change scores and parents' and therapists' rating of change and importance of change on the GCS. Correlations for SPCM-A change scores were insignificant. The standardised response mean values for SPCM-F and LSS confirmed a minimal clinically important difference. CONCLUSIONS: SPCM-F shows promise as a responsive outcome measure, however; SPCM-A requires further work. LSS may be useful for evaluative purposes, in addition to its role as a classification index.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
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 head0.007
GPT teacher head0.243
Teacher spread0.236 · 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.

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

Citations32
Published2010
Admission routes2
Has abstractyes

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