Maternal history of childhood maltreatment and later parenting behavior: A meta-analysis
Bibliographic record
Abstract
Exposure to maltreatment during childhood (CM) can have deleterious effects throughout the life span of an individual. A parent's history of child maltreatment can also impact his or her own parenting behavior. Theoretically, parents who experienced maltreatment as children may have fewer resources to cope with the challenges of childrearing and may adopt more problematic parenting behaviors. However, empirical studies examining the association between CM and later parenting behavior have yielded mixed results. The aim of this study is to conduct a meta-analysis of studies that have examined the association between exposure to CM and the subsequent parenting outcomes of mothers of 0- to 6-year-old children. A secondary aim is to examine the potential impact of both conceptual and methodological moderators. A total of 32 studies (27 samples, 41 effect sizes, 17,932 participants) were retained for analysis. Results revealed that there is a small but statistically significant association between maternal exposure to CM and parenting behavior (r = -.13, p < .05). Moderator analyses revealed that effect sizes were larger when parenting measures involved relationship-based or negative, potentially abusive behaviors, when samples had a greater number of boys compared to girls, and when studies were older versus more recent. Results are discussed as they relate to the intergenerational transmission of maltreatment and abuse.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.018 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".