Understanding Sexually Victimized Male Adolescents With Sexually Abusive Behaviors: A Narrative Review and Clinical Implications
Bibliographic record
Abstract
A high percentage of adolescents with sexually abusive behaviors have been found to have a history of childhood sexual abuse (CSA). The purpose of this review is to synthesize literature specific to adolescents with sexually abusive behaviors who have histories of CSA. This review will explore characteristics of this subset of adolescents with sexually abusive behaviors, risk factors, etiological theories that aim to explain the pathway from childhood sexual victimization to sexually abusive behavior in adolescence, and the clinical implications of this literature. Using Kiteley and Stogdon's narrative review framework, findings from 66 peer-reviewed articles published between 1990 and 2017 that included male adolescent participants with sexually abusive behaviors were integrated to inform the purpose of this review. The literature presented that different characteristics of CSA experiences, such as a younger age at the time of abuse and a longer period of abuse, were more prevalent among adolescents with sexually abusive behaviors. The CSA experiences of these adolescents could act as triggers for their sexual offenses, and the Trauma Outcome Process Assessment model addresses the importance of processing past trauma in treatment with adolescents with sexually abusive behaviors. This review concludes with clinical recommendations for how the reviewed literature could be applied within trauma-informed interventions with adolescents with sexually abusive behaviors with a history of CSA.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".