This article details a study that sought to identify risk factors for online childhood sexual abuse, and compare their relevance and strength in predicting offline sexual abuse.
As technology has become increasingly integrated into the everyday lives of young people and social interactions have moved online, so too have the opportunities for child sexual abuse. However, the risk factors for online sexual abuse, and their similarities or differences with those of offline sexual abuse have not been clarified, making it difficult to design prevention strategies. Using a nationally representative online survey panel of young adults ages 18 to 28, the current study sought to identify risk factors for online childhood sexual abuse and compare their relevance and strength in predicting offline sexual abuse. The 2,639 participants, ages 18 to 28, were sampled from the Ipsos KnowledgePanel and were asked questions about 11 different kinds of technology-facilitated online sexual abuse that occurred in childhood, follow-up questions about their dynamics and offenders, and a variety of potential risk factors. Results indicated that: (1) being cisgender female, nonheterosexual, and having parents with less than a high school education emerged as important demographic predictors of online child sexual abuse (OCSA); and (2) early offline sexual abuse was the strongest predictor of OCSA, when considering both its direct and indirect effects through online risky behavior. Findings suggest that prevention programs directed at reducing risk of sexual abuse, in general, are likely to be effective against online sexual abuse, provided they also incorporate efforts to educate youth on the need to avoid risky online behaviors. (Published Abstract Provided)
- Federal Prisoner Statistics Collected Under the First Step Act, 2023
- “I’m a security professional, a counselor, a leader, and sometimes a father figure”: Transformative social emotional learning through the eyes of school security professionals
- CARESim: An integrated agent-based simulation environment for crime and risk evaluation (CARE)