Maternal mental health predicts risk of developmental problems at 3 years of age: follow up of a community based trial
Bibliographic record
Abstract
BACKGROUND: Undetected and untreated developmental problems can have a significant economic and social impact on society. Intervention to ameliorate potential developmental problems requires early identification of children at risk of future learning and behaviour difficulties. The objective of this study was to estimate the prevalence of risk for developmental problems among preschool children born to medically low risk women and identify factors that influence outcomes. METHODS: Mothers who had participated in a prenatal trial were followed up three years post partum to answer a telephone questionnaire. Questions were related to child health and development, child care, medical care, mother's lifestyle, well-being, and parenting style. The main outcome measure was risk for developmental problems using the Parents' Evaluation of Developmental Status (PEDS). RESULTS: Of 791 children, 11% were screened by the PEDS to be at high risk for developmental problems at age three. Of these, 43% had previously been referred for assessment. Children most likely to have been referred were those born preterm. Risk factors for delay included: male gender, history of ear infections, a low income environment, and a mother with poor emotional health and a history of abuse. A child with these risk factors was predicted to have a 53% chance of screening at high risk for developmental problems. This predicted probability was reduced to 19% if the child had a mother with good emotional health and no history of abuse. CONCLUSION: Over 10% of children were identified as high risk for developmental problems by the screening, and more than half of those had not received a specialist referral. Risk factors for problems included prenatal and perinatal maternal and child factors. Assessment of maternal health and effective screening of child development may increase detection of children at high risk who would benefit from early intervention. TRIAL REGISTRATION: Current Controlled Trials ISRCTN64070727.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".