OBJECTIVE: Technology-based coercive behavior (TBC) represents an emerging public health problem. This study contributes to the literature by identifying prospective individual-, social-, and community-level predictors of TBC. METHOD: Data were collected from 800 males who participated in a prospective study on attitudes and behaviors regarding relationships with women. Variables across multiple ecological layers were used to predict TBC. RESULTS: Bivariate analyses indicated that 16 of the 17 risk variables significantly predicted TBC including anger, impulsivity, sexual compulsivity, hostility towards women, rape supportive beliefs, high-risk drinking, childhood sexual abuse, interparental conflict, peer pressure to engage in sex, peer approval of forced sex, number of sexual partners, perceived negative sanctions for sexual aggression, exposure to pornography, and participation in varsity sports, student government, and religious groups. Multivariate regression analyses indicated five variables uniquely accounted for TBC behaviors, including rape supportive beliefs, peer approval of forced sex, number of sexual partners, exposure to pornography, and participation in student government. CONCLUSIONS: Our findings that TBC can be prospectively predicted by these risk factors suggest that computer-based technology interventions focusing on these factors through social network ads that promote reflection on healthy social and romantic relationship behaviors and attitudes could help prevent and reduce TBC.
OBJECTIVE: Technology-based coercive behavior (TBC) represents an emerging public health problem. This study contributes to the literature by identifying prospective individual-, social-, and community-level predictors of TBC. METHOD: Data were collected from 800 males who participated in a prospective study on attitudes and behaviors regarding relationships with women. Variables across multiple ecological layers were used to predict TBC. RESULTS: Bivariate analyses indicated that 16 of the 17 risk variables significantly predicted TBC including anger, impulsivity, sexual compulsivity, hostility towards women, rape supportive beliefs, high-risk drinking, childhood sexual abuse, interparental conflict, peer pressure to engage in sex, peer approval of forced sex, number of sexual partners, perceived negative sanctions for sexual aggression, exposure to pornography, and participation in varsity sports, student government, and religious groups. Multivariate regression analyses indicated five variables uniquely accounted for TBC behaviors, including rape supportive beliefs, peer approval of forced sex, number of sexual partners, exposure to pornography, and participation in student government. CONCLUSIONS: Our findings that TBC can be prospectively predicted by these risk factors suggest that computer-based technology interventions focusing on these factors through social network ads that promote reflection on healthy social and romantic relationship behaviors and attitudes could help prevent and reduce TBC.
Entities:
Keywords:
cyber aggression; prospective design; sexual aggression; sexual coercion; technology-based sexual coercion