Infant Behavior and Competence Following Prenatal Exposure to a Natural Disaster: The <scp>QF</scp>2011 Queensland Flood Study
Bibliographic record
Abstract
This study utilized a natural disaster to investigate the effects of prenatal maternal stress (PNMS) arising from exposure to a severe flood on maternally reported infant social-emotional and behavioral outcomes at 16 months, along with potential moderation by infant sex and gestational timing of flood exposure. Women pregnant during the Queensland floods in January 2011 completed measures of flood-related objective hardship and posttraumatic stress (PTS). At 16 months postpartum, mothers completed measures describing depressive symptoms and infant social-emotional and behavioral problems (n = 123) and competence (n = 125). Greater maternal PTS symptoms were associated with reduced infant competence. A sex difference in infant behavioral problems emerged at higher levels of maternal objective hardship and PTS; boys had significantly more behavioral problems than girls. Additionally, greater PTS was associated with more behavioral problems in boys; however, this effect was attenuated by adjustment for maternal depressive symptoms. No main effects or interactions with gestational timing were found. Findings highlight specificity in the relationships between PNMS components and infant outcomes and demonstrate that the effects of PNMS exposure on behavior may be evident as early as infancy. Implications for the support of families exposed to a natural disaster during pregnancy 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".