Fluctuating emotional states before and during child sexual abuse and rape: a file review analysis of males in mandated care in The Netherlands
Bibliographic record
Abstract
Purpose The purpose of this study is to examine emotional states preceding and during sexual crimes in a Dutch sample of adult male patients who were admitted to mandated clinical care. Design/methodology/approach Emotional states preceding child sexual abuse (CSA) (n = 63) and rape against adults (n = 60) were compared using the Mode Observation Scale. Findings CSA and rape were equally preceded by feelings of vulnerability, undifferentiated anger and loneliness and characterised by callous unemotionality. Emotional manipulation was more dominant in the events leading up to CSA, whereas an exaggerated sense of self-worth was more dominant in the event preceding rape. Substance-related detachment was more common preceding rape but was equally common during both types of crimes. Controlled anger was more common in rape. Practical implications CSA and rape crimes are predominantly characterised by similar emotional states of persons who were admitted to mandated clinical care. This informs the development of more effective therapeutic interventions and support services tailored to the emotional profiles of patients, potentially improving rehabilitation or treatment outcomes. Scientifically, the results of this study provide a compelling foundation for further research into the psychological mechanisms underpinning sexual violence. Originality/value While previous research has often focused on these crimes in isolation, this study bridges a critical gap by examining the emotional commonalities between them. This study challenges the conventional understanding that treats these forms of sexual violence as entirely distinct, proposing instead that they may share underlying emotional dynamics.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".