Chronic illnesses in Canadian children: what is the effect of illness on academic achievement, and anxiety and emotional disorders?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Survival rates of children with a chronic illness is at an all-time high. Up to 98% of children suffering from a chronic illness, which may have been considered fatal in the past, now reach early adulthood. It is estimated that as many as 30% of school-aged children are affected by a chronic illness. For this population of children, the prevalence of educational and psychological problems is nearly double in comparison with the general population. METHODS: This study investigated the educational and psychological effects of childhood chronic illness among 1512 Canadian children (ages 10-15 years). This was a retrospective analysis using data from the National Longitudinal Survey of Children and Youth, taking a cross-sectional look at the relationships between childhood chronic illnesses, performance on a Mathematics Computation Exercise (MCE) and ratings on an Anxiety and Emotional Disorder (AED) scale. RESULTS: When AED ratings and educational handicaps were controlled for, children identified with chronic illnesses still had weaker performance on the MCE. Chronic illness did not appear to have a relationship with children's AED ratings. The regression analysis indicated that community type and illness were the strongest predictors of MCE scores. CONCLUSIONS: The core research implications of this study concern measurement issues that need to be addressed in future large-scale studies. Clinical implications of this research concern the need for co-ordinated services between the home, hospital and school settings so that services and programmes focus on the ecology of the child who is ill.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it