Victim-to-Victim Intergenerational Cycles of Child Maltreatment: A Systematic Scoping Review of Theoretical Frameworks
Bibliographic record
Abstract
Objectives: Child maltreatment is a serious problem worldwide associated with numerous developmental and psychological problems that can impede children’s short and long-term functioning. The negative effects of maltreatment may put children on a trajectory where they are likely to experience later abuse and even abuse their own children. While studies have focused primarily on the intergenerational transmission of maltreatment (victim-to-perpetrator cycles), there are studies, albeit fewer, documenting cycles of intergenerational continuity of maltreatment (victim-to-victim cycles; e.g., child sexual abuse). Clear theoretical frameworks are lacking from studies on intergenerational maltreatment. This review aimed to systematically identify theories, theoretical or conceptual frameworks that have been used to explain the victim-to-victim cycles of maltreatment.Methods: Searches were executed in PsychINFO, Medline, and Scopus. Fifteen papers were included in this review.Results: The most common theories used to explain the intergenerational continuity of maltreatment victimization were attachment theory and traumatic stress models. Other identified theories include those from social, developmental, and biological domains. Notably, there were only five papers on the intergenerational continuity of child sexual abuse, highlighting a lack of focus on the theoretical explanations of this issue. Based on the findings, a unified model of victim-to-victim cycles of maltreatment is proposed to guide future studies.Implications: Future research in this area could include testing and comparing theoretical explanations and advancing the current state of the literature by using qualitative and mixed methods.
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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 | 0.017 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.032 | 0.027 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| 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".