Maternal caregiving moderates relations between maternal childhood maltreatment and infant cortisol regulation
Bibliographic record
Abstract
BACKGROUND: Children of maltreated mothers are at increased risk for adverse physical and psychological health. Both prenatal and postnatal alterations in offspring biological stress systems have been proposed as mechanisms contributing to such transmission. The aim of the current study was to assess whether maternal postnatal care of the infant moderated any effect of maternal childhood maltreatment on infant cortisol output during a mild stressor at 4 months of age. METHODS: Participants included 181 mother-infant dyads, screened at recruitment to result in 57.4% reporting one or more forms of childhood maltreatment. Mothers were assessed for quality of caregiving, and infants were assessed for infant salivary cortisol output during the Still-Face Paradigm at infant age 4 months. Maternal childhood maltreatment was assessed using the Maltreatment and Abuse Chronology of Exposure (MACE) self-report scales. RESULTS: Greater severity of maternal childhood neglect interacted with higher levels of maternal disoriented caregiving to predict higher infant cortisol output over the course of the Still-Face Paradigm. In contrast, maternal childhood abuse interacted with higher levels of maternal negative-intrusion to predict lower infant cortisol output. Greater maternal role confusion was linked to greater infant cortisol output regardless of maternal maltreatment history. CONCLUSIONS: Maternal caregiving may moderate the effects of risk factors existing prior to the infant's birth. Disoriented caregiving in the context of maternal childhood neglect and negative-intrusive behavior in the context of maternal childhood abuse were associated with opposite directions of effect on infant stress hormone output. The results suggest that interventions addressing risks from both prenatal and postnatal periods may be most effective in mitigating intergenerational effects of maltreatment.
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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 | 0.002 |
| 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".