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Quality of life and health‐related quality of life of adolescents with cerebral palsy

2007· article· en· W2057641000 on OpenAlexafffund
Peter Rosenbaum, Michael H. Livingston, Robert J. Palisano, Barbara Galuppi, Dianne J Russell

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2007
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchOntario Ministry of Health and Long-Term Care
KeywordsCerebral palsyQuality of life (healthcare)Health Utilities IndexProxy (statistics)Gross Motor Function Classification SystemPsychologyRespondentAnalysis of varianceGerontologyDemographyMedicinePhysical therapyHealth related quality of lifeInternal medicineStatisticsDiseaseMathematics

Abstract

fetched live from OpenAlex

This study assessed quality of life (QOL) and health-related quality of life (HRQOL) of 203 adolescents with cerebral palsy (111 males, 92 females; mean age 16y [SD 1y 9mo]). Participants were classified using the Gross Motor Function Classification System (GMFCS), as Level I (n=60), Level II (n=33), Level III (n=28), Level IV (n=50), or Level V (n=32). QOL was assessed by self (66.5%) or by proxy (33.5%) with the Quality of Life Instrument for People With Developmental Disabilities, which asks about the importance and satisfaction associated with the QOL domains of Being, Belonging, and Becoming; HRQOL was captured through proxy reports with the Health Utilities Index, Mark 3 (HUI3), which characterizes health in terms of eight attributes, each having five or six ordered levels of function. GMFCS level was not a source of variation for QOL domain scores but was significantly associated with the eight HRQOL attributes and overall HUI3 utility scores (p<0.05). Some QOL domain scores varied significantly by type of respondent (self vs proxy; p<0.05). Overall HUI3 utility values were significantly but weakly correlated with QOL Instrument scores for Being (r=0.37), Belonging (r=0.17), Becoming (r=0.20), and Overall QOL (r=0.28), and thus explain up to 14% of the variance (r(2)). These findings suggest that although QOL and HRQOL are somewhat related conceptually, they are different constructs and need to be considered as separate dimensions of the lives of people with functional limitations.

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)0.001
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 score0.008
Threshold uncertainty score0.831

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.039
GPT teacher head0.312
Teacher spread0.273 · 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

Citations158
Published2007
Admission routes2
Has abstractyes

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