A model of well‐being for children with neurodevelopmental disorders: Parental perceptions of functioning, services, and support
Bibliographic record
Abstract
BACKGROUND: Both child function and supports and services have been found to impact the well-being of parents of children with neurodevelopmental disorders (NDD). The relationship between function and services and the well-being of children with NDD is less well-understood and is important to clarify in order to effect program and service change. METHODS: The current project assessed whether child function as well as the adequacy of formal supports and services provided to children and their families were predictive of child well-being. Well-being was assessed using a measure of quality of life developed for use with children with NDD. Data from 234 parents were analysed using structural equation modelling. RESULTS: Each predictor was found to load significantly on the overall outcome variable of well-being. Parent concerns about child function were significantly related to child well-being; parents who reported more concerns about their children's functioning reported lower levels of child well-being. Unmet needs for formal supports and services were also significantly related to child well-being; parents who reported that more of their children's and family's service needs were unmet reported lower child well-being. An indirect relationship was also found between child function and child well-being. When parents reported that their formal support needs were adequately met, their children's functional difficulties had a lower impact on parent perceptions of their children's overall well-being. CONCLUSIONS: Taken together, the results of the current study enrich our understanding of well-being for children with NDD. Discussion focuses on the service implications for children with NDD and their families.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".