Factors affecting the association between maternal adverse childhood experiences and preschool children’s behavioural problems: a systematic review of mediators and moderators
Bibliographic record
Abstract
Background Adverse childhood experiences (ACEs) are pernicious events (e.g., physical abuse) that occur before 18 years of age within the household. Mothers’ ACEs are associated intergenerationally with their preschool children’s (two-to-five-year-old) behavioural problems, impacting lifelong mental health trajectories. Mediators (e.g., mental health) may explain how mothers’ ACEs exert their influence on children's behavioural development whereas moderators (e.g., child sex) may affect the strength and direction of the association, revealing potential points of intervention. Therefore, this study aimed to: (1) identify mediators and moderators of this association; and (2) describe and compare moderation and mediation outcomes. Methods This review (#CRD42022307214) extracted data from peer-reviewed literature formally analyzing at least one moderating or mediating variable of the association between maternal ACEs and preschool children’s behavioural problems using MEDLINE, Embase, APA PsycINFO, Cochrane Central Register of Controlled Trials, CINAHL, SCOPUS, and Web of Science databases (n = 7). Validity was assessed using the Joanna Briggs Institute checklists. Results Thirteen full-text studies with moderate-to-high validity were identified. Most studies examined mediating variables, with unanimous support for mediation through maternal depression. The mediating roles of adult attachment styles and anxiety were conflicting. No studies examined environmental factors (e.g., neurotoxins). Conclusions Mothers’ depression is a significant contributor to children’s behavioural problems in the context of ACEs and should be a target of early intervention to prevent lifelong challenges. Future research should focus on examining more moderating variables and consider the roles of environmental factors. More research is needed on the moderating and mediating roles of genes.
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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 | 0.012 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".