Gender Differences in Behavioral Problems in Child Victims of Sexual Abuse: Contribution of Self-Blame of the Parent and Child
Bibliographic record
Abstract
The consequences associated with child sexual abuse are well known. However, factors exacerbating child behavior problems following sexual abuse (SA) deserve further attention. Self-blame following the abuse has been identified as a predictor of negative outcomes in adult survivors, however there is limited evidence regarding the impact of self-blame on consequences in child victims of sexual abuse. This study assessed behavioral problems in a sample of sexually abused children and tested the mediating role of children's internal blame attributions in the association between the parent's self-blame and the internalizing and externalizing difficulties of the child. A sample of 1066 sexually abused children between 6 and 12 years of age and their non-offending caregiver completed self-report questionnaires. Parents completed questionnaires related to the child's behavior following the SA and their own feelings of self-blame regarding the SA. Children completed a questionnaire assessing their level of self-blame. Results showed that parents' self-blame was associated with a higher level of self-blame in the child which, in turn, was linked to more child internalizing and externalizing behavior problems. In addition, parents' self-blame was directly associated with a higher level of internalizing difficulties in children. These findings underscore the importance of considering the non-offending parent's self-blame in interventions aiming the recovery of child victims of SA.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".