Der Artikel "Webcam child sexual abuse". Eine neue Facette der Begutachtung von Internetsexualdelinquenz von Fanny de Tribolet-Hardy, Andreas Hill und Elmar Habermeyer wurde ursprünglich am 2. Juli 2020 ohne "Open Access" online auf der Internetplattform des Verlags publiziert. Die Autoren haben …
ZusammenfassungDie forensische Psychiatrie sieht sich mit einem neuen Phänomen der Internetsexualdelinquenz konfrontiert, dem "webcam child sexual abuse" (WCSA), der mittels des Internets erfolgenden Anstiftung zur sexuellen Ausbeutung von Minderjährigen. Der Begriff umfasst jegliche Form sexueller Ausbeutung von Minderjährigen per Internet-Livestream, wobei das Spektrum der übertragenen Handlungen vom Posieren bis hin zu sexuell-sadistischen Übergriffen reicht. Während Schätzungen des Kinderhilfswerkes Terre des Hommes seit 2009 auf eine hohe Prävalenz solcher Handlungen verweisen, stieg die Zahl der Verurteilungen wegen WCSA erst in den letzten Jahren an. Die Anonymität des Internets und das weitgehende Fehlen von Datenspuren erschweren nicht nur die Überführung der Täter, sondern bergen auch Herausforderungen für die forensisch-psychiatrische Begutachtung. Anhand von WCSA-Fällen in der hiesigen Gutachtenstelle erfolgen Überlegungen zur kriminologischen Einordnung der Tathandlungen sowie zu Herausforderungen im Rahmen des Begutachtungsprozesses. Mithilfe einer idealtypischen Kasuistik werden Hypothesen zur Fallkonzeption gebildet und daraus Empfehlungen für die diagnostische Einordnung, Beurteilung der Einsichts- und Steuerungsfähigkeit, Prognose und Behandlung abgeleitet.
This study investigates characteristics differentiating sexually motivated murderers targeting child victims (CV; n = 35) from those with only adult victims (AV; n = 100). In the initial phase, psychiatric court reports were evaluated using standardized instruments (SCID-II, PCL-R, HCR-20, SVR-20, Static-99). In the second phase, data on duration of detention and reconviction rates were obtained from German federal criminal records. The CV group showed more often diagnostic criteria of pedophilia (43% vs. 4%) and less often alcohol abuse and drug dependency (31% vs. 55%), sexual dysfunctions (9% vs. 29%) and narcissistic personality disorder (0% vs. 13%). No significant differences were found regarding PCL-R and total risk assessment scores. Child victim perpetrators were more likely to have committed acts of sexual child abuse before the sexual homicide (46% vs. 16%) but were less likely to have committed rape or sexual assault (17% vs. 42%) or caused bodily injury (26% vs. 50%). The CV group was detained more frequently in forensic psychiatric hospitals (59% vs. 26%), but the two groups showed the same rates of release and reconviction for sexual (22% for both groups), nonsexual violent (CV 25% vs. AV 15%) and nonviolent offenses (CV 63% vs. AV 59%). Although well-known differences between nonhomicidal sexual child abusers and rapists were replicated in this study on sexual homicide perpetrators, the groups showed more similarities than differences. The high prevalence of violence and antisocial personality disorder in both groups seem to be important risk factors for committing a (sexual) homicide and might have outweighed other differences.
Forensic psychiatric populations commonly contain a subset of persons with schizophrenia spectrum disorders (SSD) who have committed sex offenses. A comprehensive delineation of the features that distinguish persons with SSD who have committed sex offenses from persons with SSD who have committed violent non-sex offenses could be relevant to the development of differentiated risk assessment, risk management and treatment approaches. This analysis included the patient records of 296 men with SSD convicted of at least one sex and/or violent offense who were admitted to the Centre for Inpatient Forensic Therapy at the University Hospital of Psychiatry Zurich between 1982 and 2016. Using supervised machine learning, data on 461 variables retrospectively collected from the records were compared with respect to their relative importance in differentiating between men who had committed sex offenses and men who had committed violent non-sex offenses. The final machine learning model was able to differentiate between the two types of offenders with a balanced accuracy of 71.5% (95% CI = [60.7, 82.1]) and an AUC of .80 (95% CI = [.67, .93]). The main distinguishing features included sexual behaviours and interests, psychopathological symptoms and characteristics of the index offense. Results suggest that when assessing and treating persons with SSD who have committed sex offenses, it appears to be relevant to not only address the core symptoms of the disorder, but to also take into account general risk factors for sexual recidivism, such as atypical sexual interests and sexual preoccupation.
