Disrupted Parental Behaviors in Maltreating and High-Risk Families: The Roles of Maternal Childhood Maltreatment, Psychological Distress, and Child Gender
Bibliographic record
Abstract
BACKGROUND: Maltreating parents and those at high-risk of maltreating their children are likely to display disrupted behaviors during parent-child interactions. Identifying risk factors associated with these behaviors can support tailored assessments and interventions in applied settings. OBJECTIVE: This study examines potential intervening factors linking maternal childhood maltreatment to disrupted parental behaviors, focusing on the indirect role of maternal psychological distress and the moderating role of child gender. PARTICIPANTS AND SETTING: The sample included 88 mothers and their children (12 to 72 months) recruited through child protection or community services due to substantiated CPS maltreatment reports or a high potential for maltreatment. METHOD: Mothers completed questionnaires and participated in a filmed interaction with their child. Disrupted parental behaviors were coded using the AMBIANCE-Brief. RESULTS: Regression analyses showed that parental psychological distress was linked with increased disrupted behaviors, and that mothers exhibited more of these behaviors with their daughters than sons. There was no direct effect of maternal childhood maltreatment on disrupted behaviors, but childhood maltreatment was indirectly related with these behaviors through maternal psychological distress. The interaction between childhood maltreatment and child gender was not significant. CONCLUSIONS: Targeting parental psychological distress may help reduce disrupted parental behaviors. Child gender may evoke different maternal responses to child needs and distress.The relevance of both trauma- and gender-sensitive intervention approaches with high-risk mothers is highlighted. Findings support the clinical utility of the AMBIANCE-Brief.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".