Quality of Life and its Determinants in Preschool Children with Down Syndrome
Bibliographic record
Abstract
Objective: Children with Down syndrome (DS) show a delay in cognitive and motor development and have various concomitant health problems. We compared Health-Related Quality of Life (HRQoL) in preschool children with DS with a reference group, and investigated child-related factors (i.e., developmental quotient, adaptive function, health problems, problem behaviour), and maternal level of education on HRQoL. Method: In a cohort of 55 children with DS, HRQoL was measured with the TNO-AZL preschool children Quality of Life Questionnaire (TAPQoL). Data from a reference group were used for comparison. Developmental Quotient (DQ) was assessed with the Bayley Scales of Infant Development II, adaptive function with the Pediatric Evaluation of Disability Inventory, health problems were derived from the medical file, and behavioural problems were measured with the Child Behaviour Checklist. Results: Children with DS (N=55; mean age 41.7 months) scored significantly lower on the TAPQoL domains lung and stomach problems, motor function and communication compared to the reference group. DQ had a significant negative correlation with the domains lung problems and liveliness. Children with DS with respiratory or gastro-intestinal problems showed significant lower scores on lung problems and communication. Problem behavior had a significant negative correlation with the domains sleeping, appetite and social function. A low level of maternal education correlated negatively with positive mood. Adaptive function and congenital heart defect (CHD) did not significantly correlate with HRQoL. Conclusion: Preschool children with DS show a lower HRQoL on particular domains of functioning compared to a normative sample. HRQoL of children with DS is correlated to DQ, respiratory and gastro-intestinal health problems, problem behaviour and maternal education, but not to CHD and adaptive function.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".