Maternal symptoms of depression and sensitivity mediate the relation between maternal history of early adversity and her child temperament: The inheritance of circumstance
Bibliographic record
Abstract
We examined maternal depression and maternal sensitivity as mediators of the association between maternal childhood adversity and her child's temperament in 239 mother-child dyads from a longitudinal, birth cohort study. We used an integrated measure of maternal childhood adversity that included the Childhood Trauma Questionnaire and the Parental Bonding Index. Maternal depression was assessed with the Edinburgh Postnatal Depression Scale at 6 months postpartum. Maternal sensitivity was assessed with the Ainsworth maternal sensitivity scales at 6 months. A measure of "negative emotionality/behavioral dysregulation" was derived from the Early Childhood Behaviour Questionnaire administered at 36 months. Bootstrapping-based mediation analyses revealed that maternal depression mediated the effect of maternal childhood adversity on offspring negative emotionality/behavioral dysregulation (95% confidence interval [0.026, 0.144]). We also found a serial, indirect effect of maternal childhood adversity on child negative emotionality/behavioral mediated first by maternal depression and then by maternal sensitivity (95% confidence interval [0.031, 0.156]). Results suggest the intergenerational transmission of the effects of maternal childhood adversity to the offspring occurs through a two-step, serial pathway, involving maternal depression and maternal sensitivity.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".