Predictors for Acceptance of Sexual Aggression Myths Among People Using Cyberporn: Cross-Sectional Study
Background: Background While rape myths acceptance (RMA) has been intensively studied over the past 30 years, there is still a lack of conclusive information on its relationships with a given set of cognitive and behavioral variables. Objective: This study aimed to examine to what extent sexual coercion, compulsive cyberporn use, arousing cyberporn scenes, moral incongruence, impulsivity, and sexual self-esteem can predict the RMA scores among people who use cyberporn. Methods: Methods Overall, 1,584 English speakers from several countries, who used cyberporn at least once during the previous six months (mean age =33.18; 63.13% men; 35.16% women; 1.70% non-binary) completed an online questionnaire. The questionnaire included measures on acceptance of modern myths about sexual aggression, sexual coercion experiences including perpetration and victimization, compulsive cyberporn use, the arousal elicited by cyberporn scenes, moral incongruence, impulsivity, and sexual self-esteem. Multivariate linear regression analyses were applied to analyze the data. Results: Results Among the male participants, RMA scores were significantly predicted by scores of sexual coercion (both perpetration and victimization), compulsive cyberporn use, arousing cyberporn scenes displaying humiliation and groups of males, sexual self-esteem, and moral incongruence. Among the female participants, RMA scores were significantly predicted by the scores of sexual coercion perpetration, compulsive cyberporn use, arousing cyberporn scenes with several females, sexual self-esteem, and age. Age emerged as a distinct factor in women, with older participants more inclined to accept rape myths. Conclusions: Conclusions Multivariate regression models showed complex male and female rape myth endorsement. Findings suggest that gender-sensitive interventions are needed to address the multiple and gender-specific factors that create sexual violence attitudes.