The effects of prenatal maternal stress on children's cognitive development: Project Ice Storm
Bibliographic record
Abstract
There exists considerable research on the effects of prenatal maternal stress on offspring. Animal studies, using random assignment to experimental and control groups, demonstrate the noxious effects of prenatal maternal stress on physical, behavioural and cognitive development. The generalizability of these results to humans is problematic given that cognitive attributions moderate reactions to stressors. In humans, researchers have relied upon maternal anxiety or exposure to life events as proxies for the stressors used with animals. Yet, the associations between maternal anxiety or potentially non-independent life events and problems in infants are confounded by genetic transmission of temperament from mother to child. We summarize the literature on prenatal maternal stress and infant cognitive development, leading to the conclusion that the human literature lacks the ability to separate the effects of the objective exposure to a stressor and the mother's subjective reaction. We then describe our prospective Project Ice Storm in which we are following 150 children who were exposed in utero to a natural disaster. We demonstrate significant effects of the objective severity of exposure on cognitive and language development at age two years with important moderating effects of the timing during pregnancy. The implications of our findings are discussed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".