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Record W7111157129 · doi:10.1017/s0012162207000126

Psychometric properties of the quality of life questionnaire for children with CP

2007· article· en· W7111157129 on OpenAlexaff

Bibliographic record

VenueUWA Profiles and Research Repository (UWA) · 2007
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsQuality of life (healthcare)Internal consistencyCerebral palsyPsychometricsReliability (semiconductor)Health related quality of lifeGross Motor Function Classification SystemCronbach's alpha

Abstract

fetched live from OpenAlex

This paper describes the development and psychometric properties of a condition-specific quality of life instrument for children with cerebral palsy (CP QOL-Child). A sample of 205 primary caregivers of children with CP aged 4 to 12 years (mean 8y 5mo) and 53 children aged 9 to 12 years completed the CP QOL-Child. The children (112 males, 93 females) were sampled across Gross Motor Function Classification System (GMFCS) levels (Level I=18%, II=28%, III=14%, IV=11%, V=27%). Primary caregivers also completed other measures of child health (Child Health Questionnaire; CHQ), QOL (KIDSCREEN), and functioning (GMFCS). Internal consistency ranged from 0.74 to 0.92 for primary caregivers and from 0.80 to 0.90 for child self-report. For primary caregivers, 2-week test-retest reliability ranged from 0.76 to 0.89. The validity of the CP QOL is supported by the pattern of correlations between CP QOL-Child scales with the CHQ, KIDSCREEN, and GMFCS. Preliminary statistics suggest that the child self-report questionnaire has acceptable psychometric properties. The questionnaire can be freely accessed at http://www.deakin.edu.ac/hmnbs/chase/cerebralpalsy/cp_qol_home.php

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)0.002
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 score0.227
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.066
GPT teacher head0.359
Teacher spread0.293 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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