Coping patterns among sexually abused children: A latent profile analysis
Bibliographic record
Abstract
Studies have identified the use of coping strategies as a key predictor of psychological outcomes in sexually abused children. However, given contradictory results in past studies, the association between approach strategies and the socio-emotional functioning of child victims remains to be clarified. Moreover, the flexible use of approach and avoidance strategies may be a more potent predictor of outcomes rather than considering these strategies separately. Using a person-centered approach, this study aimed to 1) discern different patterns of coping strategies among sexually abused children and 2) examine whether these patterns are associated with emotion regulation and behavior problems at Time 1 and Time 2 (six months later). A sample of 564 children aged 6 to 12 was recruited in specialized intervention centers following disclosure of sexual abuse. Children self-reported their coping strategies mobilized following sexual abuse. Parents completed measures of emotion regulation and behavior problems of children at two time-points. Three profiles were identified: Low coping (37.77%), High approach and high avoidance (19.86%), and High approach and low avoidance (42.37%). The Low coping profile showed low levels of behavior problems and high emotion regulation. Children assigned to the High approach and high avoidance profile showed more externalized behavior than the two other profiles, and greater levels of emotion dysregulation relative to children assigned to the Low coping profile. This study highlights the complex nature of coping strategies in sexually abused children, revealing that the interplay between approach and avoidance significantly influences their socio-emotional functioning.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".