The effect of prenatal maternal stress on the development of attention problems in five-year-old children /
Bibliographic record
Abstract
Research indicates a relationship between prenatal maternal stress (PNMS) and attention levels in children. Studies with non-human primates suggest that both exposure to PNMS and the timing of a stressor during pregnancy are associated with greater attention problems in offspring; however, this has not been sufficiently tested in humans because of methodological constraints. We explored the relationship between objective and subjective measures of PNMS for 85 women who were pregnant during the 1998 Quebec Ice Storm and attention levels in their 5.5 year-old children, while controlling for socioeconomic status, child's sex, and maternal state anxiety. As a group, children in the study displayed significantly less attentive behaviour compared to a standardized norm. Boys in this group were significantly less attentive than girls. Objective PNMS exposure during 1st trimester correlated positively with attention problems in the children, accounting for 15.2% of the variance in attention levels as rated by Kindergarten teachers. In a behavioural task to detect sustained attention difficulties and Attention Deficit-Hyperactivity Disorder (ADHD) symptoms, children exposed during the 3rd trimester obtained significantly worse scores compared to children exposed in other trimesters. However, in this case, objective and subjective PNMS appeared to act as protective factors, raising the possibility of the presence of another unknown mechanism that negatively affected the attention variables.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".