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Record W2004317557 · doi:10.1155/2010/940101

The Quality of Life of a Multidiagnosis Group of Special Needs Children: Associations and Costs

2010· article· en· W2004317557 on OpenAlexaffabout
Sandy Thurston, Louise Paul, Patricia Loney, Maria Wong, Gina Browne

Bibliographic record

VenueInternational Journal of Pediatrics · 2010
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsMcMaster UniversityOntario HIV Treatment Network
Fundersnot available
KeywordsPsychosocialMedicineQuality of life (healthcare)GerontologyQuality (philosophy)PediatricsDemographyPsychiatryNursing

Abstract

fetched live from OpenAlex

Purpose. To determine the quality of life, associations, and costs of a multidiagnosis group of special needs children. Methods. In this cross-sectional survey families were identified from the Children's Treatment Network, a Canadian multisector program for children with special needs. Families were eligible if the child was aged 2-19 years, resided in Simcoe/York, and if there were multiple child/family needs. Quality of life was measured using the PedsQL (n = 429). Results. Quality of life scores were lower in this group compared to published healthy and single disorder groups of children. Quality of life scores decreased with advancing age. Child psychosocial well-being was more strongly associated with child/family variables compared to physical well-being. Health Utilization costs were higher in children with greater physical challenges. Conclusions. Further research is needed in other complex needs child samples to confirm the decrease in quality of life found in these children into adolescence. Investigations into the interactions of child and family variables are needed.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.336
Teacher spread0.315 · 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

Citations14
Published2010
Admission routes2
Has abstractyes

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