Disrupted caregiving behavior as a mediator of the relation between disrupted prenatal maternal representations and toddler social–emotional functioning
Bibliographic record
Abstract
Abstract The development of maternal representations of the child during pregnancy guides a mother’s thoughts, feelings, and behavior toward her child. The association between prenatal representations, particularly those that are disrupted, and toddler social-emotional functioning is not well understood. The present study examined associations between disrupted prenatal representations and toddler social-emotional functioning and to test disrupted maternal behavior as a mediator of this association. Data were drawn from 109 women from a larger prospective longitudinal study ( N =120) of women and their young children. Prenatal disrupted maternal representations were assessed using the Working Model of the Child Interview disrupted coding scheme, while disrupted maternal behavior was coded 12-months postpartum from mother-infant interactions. Mother-reported toddler social-emotional functioning was assessed at ages 12 and 24 months. Disrupted prenatal representations significantly predicted poorer toddler social-emotional functioning at 24 months, controlling for functioning at 12 months. Further, disrupted maternal behavior mediated the relation between disrupted prenatal representations and toddler social-emotional problems. Screening for disrupted representations during pregnancy is needed to facilitate referrals to early intervention and decrease the likelihood of toddler social-emotional problems.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".