University of Southern California, Dworak-Peck School of Social Work, University Park Campus, MRF, MC 0411, Los Angeles CA 90089, United States.
University of Southern California, Department of Preventive Medicine, Keck School of Medicine, 2001 N. Soto St., Los Angeles, CA 90034, United States.
Child Abuse Negl. 2018 Nov;85:209-219. doi: 10.1016/j.chiabu.2018.01.033. Epub 2018 Feb 8.
Maltreated youth are at risk for exposure to online sexual content and high-risk sexual behavior, yet characteristics of their online social networks have not been examined as a potential source of vulnerability. The aims of the current study were: 1) to test indicators of size (number of friends) and fragmentation (number of connections between friends) of maltreated young adults' online networks as predictors of intentional and unintentional exposure to sexual content and offline high-risk sexual behavior and 2) to test maltreatment as a moderator of these associations. Participants were selected from a longitudinal study on the effects of child maltreatment (n = 152; Mean age 21.84 years). Data downloaded from Facebook were used to calculate network variables of size (number of friends), density (connections between friends), average degree (average number of connections for each friend), and percent isolates (those not connected to others in the network). Self-reports of intentional and unintentional exposure to online sexual content and offline high-risk sexual behavior were the outcome variables. Multiple-group path modeling showed that only for the maltreated group having a higher percent of isolates in the network predicted intentional exposure to online sexual content and offline high-risk sexual behavior. An implication of this finding is that the composition of the Facebook network may be used as a risk indicator for individuals with child-welfare documented maltreatment experiences.
受虐青少年面临接触网络色情内容和高危性行为的风险,但他们的网络社交网络特征尚未被视为潜在的脆弱性来源。本研究的目的是:1)测试受虐成年期在线网络的大小(朋友数量)和碎片化(朋友之间的连接数量)指标,以预测有意和无意接触性内容和线下高危性行为的可能性;2)测试虐待作为这些关联的调节因素。参与者从一项关于儿童虐待影响的纵向研究中选取(n=152;平均年龄 21.84 岁)。从 Facebook 下载的数据用于计算网络变量的大小(朋友数量)、密度(朋友之间的连接)、平均度数(每个朋友的平均连接数)和孤立百分比(网络中没有与其他人连接的人)。有意和无意接触网络色情内容和线下高危性行为的自我报告是因变量。多组路径模型显示,只有在网络中孤立百分比较高的受虐组,才预测有意接触网络色情内容和线下高危性行为。这一发现的意义在于,Facebook 网络的组成可能被用作有儿童福利记录的受虐经历的个体的风险指标。