School Satisfaction Predicts Quality of Life for Children With Severe Developmental Disabilities and Their Families
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".