Disclosure of sexual abuse, and personal and familial factors as predictors of post-traumatic stress disorder symptoms in school-aged girls
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to analyze predictive factors of post-traumatic stress disorder (PTSD) symptoms in school-aged girls. METHODS: A group (n=67) of seven- to 12 year-old girls consulting a paediatric hospital following disclosure of sexual abuse were compared with a group (n=67) of nonabused girls. The girls answered questionnaires related to PTSD, coping, sense of hope, self-esteem, sibling relationships and perceived social support. Mothers answered questionnaires related to family relationships, family violence, perceived support given and psychological distress. RESULTS: The mean +/- SD age of the girls was 9+/-1.5 years. In the sexual abuse group, single-parent families were more frequent (53.7% versus 32.3%; P<0.01), mothers were less educated (10.8% versus 13.1%; P<0.0001) and socioeconomic level was lower (36.8% versus 47.9%; P<0.0001). A history of sexual abuse in childhood was reported by 50% of mothers of sexually abused children and 37% of mothers of the comparison group children. A higher prevalence of PTSD clinical scores was found for the girls reporting sexual abuse (46.3% versus 18.5%; P<0.001). Regression analyses controlling for parental education level and family structure revealed that group membership (sexual abuse group versus comparison group) was predictive of the level of PTSD symptoms. In addition, the mother's level of support, the child's perception of parental support and the child's reliance on avoidance coping predicted PTSD symptoms. Sense of hope and the child witnessing interparental physical violence were marginally associated with the level of PTSD symptoms. CONCLUSIONS: PTSD was common in the present study's sample of sexually abused girls. Because predictive factors relate to both child-related variables and familial context, interventions for this population should target not only the child, but also the family.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".