Family‐centred care and health‐related quality of life of patients in paediatric neurosciences
Bibliographic record
Abstract
BACKGROUND: Little is known about the influence of contextual factors such as health services characteristics on health-related quality of life (HRQL) for children with a neurological condition. To address this gap, we conducted an exploratory study of the relationship between family-centred care (FCC) and HRQL outcomes in children from neurosciences clinics in a large acute care hospital. METHODS: A total of 187 family caregivers completed questionnaires regarding their socio-demographic status, the severity of their children's condition (FIM), perceptions of their children's HRQL (PedsQL 4.0) and their experiences of FCC (MPOC-20). Hierarchical regression analyses explored the hypothesis that FCC is a significant predictor of children's HRQL, independent of illness severity. RESULTS: Illness severity and FCC jointly explained one-third of the variance in children's total HRQL. When FCC was controlled for illness severity, it remained a significant predictor of physical, psychosocial and total HRQL scores. CONCLUSIONS: This study provides evidence that the level of FCC is positively related to paediatric HRQL independent of neurological illness severity. The implication is that the uptake of FCC practices by service providers can positively impact the quality of life of children with neurological disorders.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".