The Role of Rape-Supportive Attitudes, Alcohol, and Sexual Arousal in Sexual (Mis)Perception: An Experimental Study

Abstract

While sexual misperception does not irrevocably lead to sexual aggression, it remains a significant risk factor. The present study investigated the effects of rape-supportive attitudes, alcohol, and sexual arousal on sexual perception. We used a 2 × 2 between-participants factorial design to randomly assign 135 men from the general population to a condition with or without alcohol (blood alcohol concentration target of .08%) and to a condition with or without sexual arousal. Participants were asked to listen to an audiotape depicting a sexual interaction between a man and woman and to indicate if and when they believed the woman was no longer interested in having sex. Results, obtained through survival analyses, indicate that the effects of rape-supportive attitudes on sexual misperception are moderated by alcohol consumption. Alcohol appears to be an important situational factor for activating men’s implicit theories. Our study sheds new light on the role of knowledge structures in sexual perception: It identifies when, as well as suggesting how, rape-supportive attitudes may disturb sexual perception and ultimately lead to sexual misperception.

Notes

¹ For social information processing models, social behaviors—including sexually aggressive behaviors—are the result of a sequence of “on-line mental operations (i.e., cognitive processes that are ‘in the moment’ and occur in real time)” (Fontaine, 2008, p. 18), from the encoding of social cues to the enactment of behavioral responses.

² Participants were asked to watch a set of 17 videos and to judge a woman’s behavior, including her attractiveness and level of friendliness. All participants were exposed to the same experimental stimuli. Complementary analyses indicated that this first task did not influence the response latency reported in this article.

³ T tests are reported under the assumption of equal variances not assumed.

⁴ While survival analyses are more suitable for time-to-an-event data, ordinary linear regression models may be applicable only when there are few censored data (Jahn-Eimermacher, Lasarzik, & Raber, 2011).