High Rates of School Readiness Difficulties at 5 Years of Age in Very Preterm Infants Compared with Term Controls
Bibliographic record
Abstract
OBJECTIVE: School readiness is best understood as a framework for assessing profiles of strengths and vulnerabilities of the preschool-age child. Very preterm (VPT) children are at high risk of difficulties in school, and understanding their school readiness skills has the potential to aid successful transition into school. The aim of this study was to determine the school readiness skills of a cohort of VPT children, compared with term controls. METHODS: VPT children (gestational age <30 wk or birth weights <1250 g) and term controls were enrolled from a tertiary maternity hospital, Melbourne, Australia into a prospective cohort study. At age 5 years, school readiness skills were evaluated using a combination of parent questionnaires and direct assessments. The 5 domains of school readiness assessed were health and physical development, social-emotional skills, approaches to learning, communication skills, and cognitive skills. RESULTS: VPT children had standard scores ~½ to 1 SD below those of the term controls in all domains of school readiness, and these differences were not greatly affected by adjustment for social risk differences. Overall, 44% of the VPT group had vulnerabilities in more than 1 domain of school readiness, compared with only 16% of the term controls. CONCLUSIONS: VPT children are more likely than term controls to have significant vulnerabilities in multiple domains of school readiness, and these differences are mostly independent of social risk.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".