Associations of Parental Distress and Behavior with School Readiness in Children Born Very Preterm
Bibliographic record
Abstract
OBJECTIVE: Children born very preterm (VPT; gestational age [GA] <31 weeks) have robust school readiness difficulties relative to children born full-term (FT; GA ≥37 weeks). This study examined whether four aspects of parental well-being and behavior-distress, harshness, responsiveness and positive control, and cognitive stimulation-were linked to school readiness in a sample of children born VPT <31 weeks GA and whether these characteristics similarly impact VPT and FT children. METHODS: Parents of 4-year-olds born VPT (n = 55) and FT (n = 38) reported on parental distress, behavior, and cognitive stimulation. Children's cognition, executive function, motor skills, preacademic abilities, and behavior were assessed via neuropsychological tests and parent-report questionnaires. RESULTS: For both groups of children, higher psychological distress and harshness were associated with more behavior problems, and more cognitive stimulation was associated with higher scores on tests of cognitive, motor, and preacademic abilities. More parental distress was associated with lower cognitive ability only for children born VPT and more harshness was associated with lower preacademic skills only for children born FT. CONCLUSIONS: Identifying modifiable family factors associated with school readiness in children born VPT is essential for informing family-based interventions to improve school readiness in this population. Findings suggest that distress, harshness, and cognitive stimulation may be reasonable targets for interventions to improve school readiness in children born VPT.
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.
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 | 0.000 |
| 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) | 0.001 | 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".