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Record W2784055750 · doi:10.1111/jir.12460

The quality of life of children with severe developmental disabilities

2018· article· en· W2784055750 on OpenAlexafffund
Bongiwe Ncube, Adrienne Perry, Jonathan A. Weiss

Bibliographic record

VenueJournal of Intellectual Disability Research · 2018
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsYork University
FundersCanadian Institutes of Health Research
KeywordsHappinessQuality of life (healthcare)Psychological interventionFriendshipPsychologyLife satisfactionClinical psychologyDistressDevelopmental psychologyMedicinePediatricsPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Research examining the quality of life (QoL) of children with severe developmental disabilities (SDD) is limited. The present study examines parent perceptions of child QoL in children with SDD compared with typically developing (TD) children and then examines predictors of QoL for the SDD group. METHOD: Parents of 246 children with SDD (aged 4 to 19 years) and 210 TD children (aged 4 to 18 years) responded to an online survey. QoL was measured using a composite variable composed of the child's happiness, achievement of potential and friendship quality. RESULTS: Children with DD had lower QoL ratings than TD children. In children with DD, higher QoL was related to younger age, higher adaptive skills, lower maladaptive behaviour, lower parent psychological distress and higher satisfaction with the child's education. CONCLUSIONS: Interventions to promote positive outcomes for children with SDD should target both characteristics of the individual and the environment.

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)0.001
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.176
GPT teacher head0.448
Teacher spread0.272 · 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

Citations34
Published2018
Admission routes2
Has abstractyes

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