Childhood sexual abuse and attachment insecurity: Associations with child psychological difficulties.
Bibliographic record
Abstract
Childhood sexual abuse (CSA) is considered an important public health concern that can derail the developmental course of children. Given that children rely upon their attachment figures when they experience upsetting events, attachment organization may play a critical role in predicting victims' adaptation to CSA. To date, no studies have delineated the unique and interactive contributions of these two risk factors in the prediction of psychopathology. The aims of this study were to examine attachment in CSA victims and a comparison group and to assess the contributions of each risk factor to child psychological difficulties. Participants included 111 children aged 7-13, of whom 43 were CSA victims. Children completed an attachment interview and reported on their depressive symptoms. Their mothers reported on children's externalizing symptoms, internalizing symptoms, dissociation, and sexualized behavior. Our key findings showed that child victims of CSA were more likely to be classified as having insecure and disorganized attachment. Further, insecure attachment was the primary factor associated with higher self-reported depressive symptoms in all children and that CSA was associated with more parent-reported child externalizing problems, sexualizing problems, and dissociation. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".