Developmental origins of infant emotion regulation: Mediation by temperamental negativity and moderation by maternal sensitivity.
Bibliographic record
Abstract
Emotion regulation is essential to cognitive, social, and emotional development and difficulties with emotion regulation portend future socioemotional, academic, and behavioral difficulties. There is growing awareness that many developmental outcomes previously thought to begin their development in the postnatal period have their origins in the prenatal period. Thus, there is a need to integrate evidence of prenatal influences within established postnatal factors, such as infant temperament and maternal sensitivity. In the current study, prenatal depression, pregnancy anxiety, and diurnal cortisol patterns (i.e., the cortisol awakening response (CAR) and diurnal slope) were assessed in 254 relatively low-risk mother-infant pairs (primarily White, middle-class) in early (M = 15 weeks) and late pregnancy (M = 33 weeks). Mothers reported on infant temperamental negativity (Infant Behavior Questionnaire-Revised) at 3 months. At 6 months, maternal sensitivity (Parent Child Interaction Teaching Scale) and infant emotion regulation behavior (Laboratory Temperament Assessment Battery) were assessed. Greater pregnancy anxiety in early pregnancy and a blunted CAR in late pregnancy predicted higher infant temperamental negativity at 3 months, and those infants with higher temperamental negativity used fewer attentional regulation strategies and more avoidance (i.e., escape behavior) at 6 months. Furthermore, this indirect effect was moderated by maternal sensitivity whereby infants with elevated negativity demonstrated maladaptive emotion regulation at below average levels of maternal sensitivity. These findings suggest that the development of infant emotion regulation is influenced by the ways that prenatal exposures shape infant temperament and is further modified by postnatal caregiving. (PsycINFO Database Record
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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 | 0.000 | 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".