Patterns of continuity and discontinuity of childhood maltreatment across generations: A meta-analysis
Bibliographic record
Abstract
Empirical tests of the "cycle of maltreatment" hypothesis have typically focused on the presence or absence of child maltreatment across generations. However, this narrow focus does not account for diverse intergenerational pathways of maltreatment. This systematic review and meta-analysis synthesizes data to determine the distribution of cycle maintainers, breakers, initiators, and unaffected families (i.e., controls). Of the 65 independent studies (80 samples), 30 examined intergenerational cycles of maltreatment broadly, while 27 reported data for physical abuse, 17 sexual abuse, 5 neglect, and 1 emotional abuse specifically. For maltreatment, 17.1% (95%CI: 12.1%, 22.1%) were cycle maintainers, 23.6% (95%CI: 18.0%, 29.2%) were cycle breakers, 11.4% (95%CI: 7.8%, 15.1%) were cycle initiators and 47.8% (95%CI: 39.7%, 55.9%) controls. Thus, although a parent's maltreatment history is a risk factor, results suggest that a greater proportion of parents break the cycle of maltreatment versus maintain it. Moderator analyses showed that study design, assessment methods, and demographic characteristics influence maltreatment transmission rates. Intergenerational patterns of physical, sexual, and emotional abuse and neglect are also detailed. Our findings underscore the complexity of intergenerational maltreatment, highlighting the need to explore not only its maintenance but also the protective factors that help break cycles and the risk factors that drive its initiation.
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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 | 0.019 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.056 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".