ARE SEXUALLY ABUSED CHILDREN AT RISK FOR VICTIMIZATION BY PEERS?
Notice bibliographique
Résumé
Abstract BACKGROUND A few studies suggest that children who suffered maltreatment are more at risk for victimization by peers. However, there is little knowledge about factors that may influence the risk of re-victimization by peers for sexually abused (SA) children. OBJECTIVES Identify if self-blame and post-traumatic stress symptoms (PTSS) are risk factors for SA children victimization by peers. DESIGN/METHODS 376 children (248 girls and 128 boys) between 5 to 14 years of age were recruited within five centers for child and youth SA evaluation. Victimization by peers was measured with the Report Victimization Scale answered by the child, his parent and his teacher. PTSS were measured with the subscale of the Children’s Impact of Traumatic Events Scale (CITES II) and self-blame was measured with three items from the subscale guilt/blame of CITES II. Characteristics of the abuse were abstracted from the medical chart. Description of SA was done according to Russell’s classification: less severe (physical contact over clothing), severe (physical contact without penetration, and without using of force), very severe (attempted or actual penetration). Statistical analysis was done through logistic regression. RESULTS Abuse was very severe in 61% of cases and chronic in 37.4% of cases. Aggressors were family members in 53.3% of cases. Clinical level of peer victimization was reported for 19.2% of children by their own score, 9.2% by parental score and 3.6% by teacher’s score. PTSS were at the clinical level for 53.3% of children Around 60% of the sample reported feelings of blame, as indicated by at least one score of “somewhat true”on one of the three items. The dichotomized analysis (clinical vs subclinical score of victimization by peers) showed that PTSS were positively associated with the child’s peer victimization score (Exp (B) = 1.05, p<.02), and self-blame was positively associated with the parent’s peer victimization score (Exp(B)=1.23, p<.05). Results of a Sobel test revealed that PTSS completely mediated the positive relationship between self-blame and peer victimization (Standard Beta = .37, p<.01). In the final model, self-blame was positively associated with PTSS (Standard Beta = .54, p<.01), while the latter were positively associated with victimization by peers (Standard Beta = .44, p<.01). The final model explained 26.7% of the variance of victimization by peers. CONCLUSION These results suggest that PTSS and self-blame are key targets for intervention in order to diminish the risk of victimization by peers in SA children.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».