Child and parental mental ability and glycaemic control in children with Type 1 diabetes
Bibliographic record
Abstract
AIMS: Many psycho-social factors can affect the glycaemic control of children with Type 1 diabetes, but the influence of the intelligence of the child and their parents has not been reported. METHODS: Seventy-eight children and adolescents with Type 1 diabetes and their mothers performed standardized tests to assess psychometric intelligence. The children were aged (median (range)) 12.0 (5-17) years with duration of diabetes 5.0 (1.0-13.0) years and required an insulin dose of (mean +/- SD) 1.0 +/- 0.3 U/kg per day. The children completed the Wide Range Achievement Test 3 reading test (WRAT3) and Raven's Standard Progressive Matrices (RSPM). A mean annual HbA1c was calculated for each subject (8.6 +/- 1.4%). The mothers performed the National Adult Reading Test (NART) and provided details of the occupation of the main wage-earner in the family from which social class (SC) was derived. RESULTS: The HbA1c of the child correlated with their age (r = 0.26, P = 0.02), SC (Kendall's rank correlation, tau = 0.17, P = 0.03) and with the NART error score of their mother (r = 0.28, P = 0.01), but no correlation was observed with the child's WRAT3 or RSPM score. Stepwise regression revealed that age and NART error score were the strongest independent determinants of glycaemic control (total adjusted r2 = 0.117). CONCLUSIONS: Parental intelligence appears to have a significant influence on the glycaemic control of a child with Type 1 diabetes, accounting for 7.6% of the reliable variance in HbA1c.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".