Maternal antenatal mood and child development: an exploratory study of treatment effects on child outcomes up to 5 years
Bibliographic record
Abstract
Effective treatment of maternal antenatal depression may ameliorate adverse neurodevelopmental outcomes in offspring. We performed two follow-up rounds of children at age 2 and age 5 whose mothers had received either specialized cognitive-behavioural therapy or routine care for depression while pregnant. Of the original cohort of 54 women, renewed consent was given by 28 women for 2-year follow-up and by 24 women for 5-year follow-up. Child assessments at the 2-year follow-up included the Parenting Stress Index (PSI), Bayley Scales of Infant Development (BSID-III) and the Child Behaviour Checklist (CBCL). The 5-year follow-up included the Wechsler Preschool and Primary Scales of Intelligence (WPPSI-III) and again the CBCL. Treatment during pregnancy showed significant benefits for children's development at age 2, but not at age 5. At 2 years, intervention effects were found with lower scores on the PSI Total score, Parent Domain and Child domain (d=1.44, 1.47, 0.96 respectively). A non-significant trend favoured the intervention group on most subscales of the CBCL and the BSID-III (most notably motor development: d =0.52). In contrast, at 5-year follow-up, no intervention effects were found. Also, irrespective of treatment allocation, higher depression or anxiety during pregnancy was associated with higher CBCL and lower WPPSI-III scores at 5 years. This is one of the first controlled studies to evaluate the long-term effect of antenatal depression treatment on infant neurodevelopmental outcomes, showing some benefit. Nevertheless, caution should be taken interpreting the results because of a small sample size, and larger studies are warranted.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".