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Record W4407046701 · doi:10.1111/jar.70013

School Satisfaction Predicts Quality of Life for Children With Severe Developmental Disabilities and Their Families

2025· article· en· W4407046701 on OpenAlexafffund
Sarah E. Bjornson, Adrienne Perry

Bibliographic record

VenueJournal of Applied Research in Intellectual Disabilities · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsYork University
FundersCanadian Institutes of Health ResearchYork University
KeywordsPsychologyMultilevel modelDevelopmental psychologyQuality of life (healthcare)Clinical psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Children with severe developmental disabilities are frequently excluded from research, and little is known about their quality of life (QoL). Using a mixed-methods approach, this study examined relationships between school factors and QoL for these children and their families. METHOD: 171 parents of children with severe developmental disabilities completed questionnaires. Hierarchical regression analyses were performed examining predictors of child and family QoL. Of the 171 parents, 123 responded to an open-ended question about their children's school experiences, and responses were analysed qualitatively. RESULTS: Significant predictors of QoL included challenging behaviours, diagnoses, parent self-efficacy, social support and (importantly) school satisfaction. Seven themes related to school experiences were identified qualitatively. CONCLUSION: Many factors contribute to QoL. School has a significant influence on children and their parents and families. Different children have different strengths and difficulties, and school systems need to work with parents to optimise outcomes.

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)0.005
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.099
GPT teacher head0.392
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.

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

Citations2
Published2025
Admission routes2
Has abstractyes

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