We also explored the extent to which gender moderated these associations. Because pornographic sexual scripts often depict men as aggressors and women as targets of aggression, we hypothesized pornography use would increase men’s engagement or interest in aggressor behaviors more so than women’s, while pornography would increase women’s engagement or interest in target behaviors more so than men’s. Finally, because many of the uncommon and/or degrading sexual behaviors portrayed in pornography involve men degrading women, we hypothesized pornography use would increase men’s engagement or interest in uncommon/degrading behaviors more so than women’s.

The current study explored the relations between pornography use and pornography-normative sexual behavior in heterosexual adults. Consistent with social modeling and sexual scripts theories, we hypothesized greater use of pornography would be associated with increased self-reported engagement in sexual practices often reflected in pornography, including anal sex, ass-to-mouth, and verbal and physical aggression (aggressor and target). Although prior studies have shown associations between pornography use and select sexual behaviors commonly found in pornography, in particular anal sex (e.g., Braun-Courville & Rojas, 2009 ), this study extends these findings by exploring additional frequently occurring sexual behaviors such as ass-to-mouth and ejaculation on a woman’s face. We further examine the degree to which pornography use predicts self-reported interest in engaging in pornography-normative sexual behavior in participants who had not yet tried the behaviors. Consistent with sexual script theory, we hypothesized greater use of pornography would be associated with increased interest in engaging in sexual behaviors frequently observed in popular pornography.

Longitudinal studies examining associations between pornography use, attitudes, and sexual behavior suggest media exposure precedes attitude and behavior change. For instance, Peter and Valkenburg (2010) conducted a three-wave panel study over the course of a year, surveying 1,052 Dutch adolescents aged 13–20 years. The study found that exposure to pornography increased subsequent views of sex as instrumental (for physical pleasure only) and that this influence was mediated by perceived realism. The authors argue for the importance of cognitive processing to understand the effects of pornography use on attitudes and sexual behavior. Another three-wave panel study of adolescent boys ( Ward, Vandenbosch, & Eggermont, 2015 ) demonstrated that boys who consumed more sexualizing magazines tended to express more gender stereotypical beliefs about feminine courtship strategies over time. The study also ruled out the possibility that it was the beliefs that drove the media consumption. Wright (2013) found similar attitude changes in a representative sample of 1,276 U.S. adults: Higher pornography use at earlier waves predicted subsequent permissive attitudes about sex, but permissive attitudes did not prospectively predict pornography use. These findings extend to sexual behavior, as well. In the same sample of U.S. adults, Wright (2012) found pornography use predicted, prospectively, casual sex engagement but that casual sex did not predict later pornography use.

In cognitive terms, script adoption may go through systemic processing ( Wright, 2011 ) or automatic processing ( Huesmann, 1998 ). Systematic processing requires a deliberate and careful evaluation of the script messages ( Rubin & Windahl, 1986 ). When this happens, the script content is carefully scrutinized and rationally evaluated. However, systemic processing occurs infrequently because it requires mental energy and time ( Huesmann, 1998 ; Shrum & Lee, 2012 ). The tendency to use automatic processing is especially elevated in a state of arousal. Ariely and Loewenstein (2006) found that when male college students were in a state of sexual arousal induced by self-stimulation (masturbation), they were more likely, as compared to the neutral state, to report a wide range of stimuli and activities sexually appealing and they were more willing to report a desire to engage in morally questionable and risky sexual behaviors, such as having anal sex, spanking a partner, watching someone urinate, and becoming sexually excited by animals or prepubescent girls. Sexual arousal can play a powerful moderating role in the activation and application of the pornographic sexual script and may encourage automatic processing in sexual decision-making that bypasses critical faculty (see Shrum & Lee, 2012 ).

It is important to note that even if viewing the same pornographic content, different individuals may or may not incorporate the pornographic script into their sexual behaviors depending on individual differences (such as gender, moral standards, apathy, or self-regulation) and situational differences (such as time pressure, sexual arousal, or the availability of a sexual partner; Wright, 2011 ). However, some aspects of pornography make the incorporation of the pornographic sexual script more likely to occur than other media-driven scripts. In particular, the sexual arousal, masturbation, and orgasms that frequently accompany pornography viewing make it more likely that the sexual script will be activated and applied ( Bandura, 1986 ; Wright, 2011 ). The pleasure felt by masturbation and orgasm to pornography are rewarding, thereby increasing the likelihood that the behavior will be repeated again in the future. This repeated exposure to pornographic sexual scripts, particularly when coupled with masturbation, is what Wright (2011) hypothesizes leads to increased adoption of the script.

Frith and Kitzinger (2001) define sexual scripts as “culturally available messages that define what ‘counts’ as sex, how to recognize sexual situations, and what to do in a sexual encounter” (p. 210). Given the inadequate sexual education imparted in both the home and school and an increasingly mainstreamed pornographic culture ( Dines, 2010 ; Paul, 2005 ), pornography has become an important sexual script for many young men and women ( Sun et al., 2016 ).

Social scripting theory argues people follow internalized scripts that provide meaning and direction for social interaction ( Gagnon & Simon, 1973 ; Simon & Gagnon, 1986 ). Scripts can be viewed as “normative clusters which specify the parameters for lines of action in given social contexts” ( Gecas & Libby, 1976 , p. 37). Social scripts tell us, in other words, “what should or should not be happening, how people should or should not behave in response to what is or is not happening and what the outcomes of a particular course of action should be” ( Wright, 2011 , p. 348; see also Huesmann, 1986 ). Scripts are acquired through observation of others as well as through consumption of mass media.

Social learning theory ( Bandura, 1971 ) posits that people are neither ruled by inner impulses nor helpless in the face of environmental forces, pressures, or constraints. Instead, human behavior is best understood in terms of a continuous and reciprocal relationship between cognitive, behavioral, and environmental influences. Although new patterns of behavior can be learned through direct experience, most human behavior is learned vicariously by observing people’s actions and the consequences of those actions ( Bandura, 1986 ). This process often unfolds through observation of others in our immediate environment, but “the extensive modeling in the symbolic environment of the mass media” ( Bandura, 2001 , p. 126) can also have a significant impact as a result of its reach and power in shaping people’s images of reality. Indeed, in the Internet age, “electronic acculturation” can serve as a “major vehicle for sociopolitical change” (p. 127).

Providing a summary of research on pornography and sexual behavior is complicated by disagreements about what pornography is. Definitions of pornography vary tremendously, from being defined by its purpose, such as the Attorney General’s Commission on Pornography (1986) stating pornography is “material predominantly sexually explicit and intended for purposes of sexual arousal” (pp. 228–229) or by its accessibility, such as Barron and Kimmel (2000) defining pornography as “any sexually explicit material to which access was limited, either by signs or physical structure, to adults” (p. 162). Still others focus not on the sexual explicitness per se but on the combination of sexual explicitness and violence or degradation. For instance, Russell (1993) defined pornography as “material that combines sex and/or the exposure of genitals with abuse or degradation in a manner that appears to endorse, condone, or encourage such behavior” (p. 3). Lott (1994) stated pornography shows women being sexually dominated, degraded, humiliated, coerced, and/or beaten. Senn (1993) differentiates pornography from erotica, stating erotica is sexually explicit but not degrading or violent, while pornography combines themes of sexual explicitness with sexism, racism, homophobia, and violence. However, most empirical studies do not differentiate pornography from erotica (e.g., Bridges & Morokoff, 2011 ), despite content analyses showing themes of violence and degradation in pornography are common ( Bridges et al., 2010 ; Sun et al., 2008 ).

This project was part of a collaborative, multisite study of culture and sexual behavior conducted by a consortium of international, cross-disciplinary scholars from the fields of communication, psychology, and sociology. All participating university institutional review boards approved the project. Participants were recruited from Spring 2011 to Spring 2012 through departmental and college-wide e-mail announcements, posted campus flyers, or introductory psychology courses. Interested participants were directed to an online survey posted on SurveyMonkey, a web-based survey service, and each recruitment site had a unique link. Participants first provided consent and then confirmed their eligibility prior to completing the survey. Participation took approximately 30 min. Following survey completion, participants received a full debriefing and were given an opportunity to enter into a raffle to win one of the three cash prizes (one US$100 and two US$60 prizes were awarded via random selection of all interested participants).

Six questions assessed engagement in degrading and/or uncommon sexual behaviors ( Table 2 ). Items asked about engaging in double penetration, anal sex, ass-to-mouth, oral sex (woman kneeling, man standing), ejaculation on a woman’s face, and name-calling. Each item was answered on the same 6-point scale described above. Responses were recoded into two sets of variables, tried ( yes/no ) and would like ( yes/no ), and then percentage scores were created by dividing the sum of tried and would like items by the number of items the participants had answered (of the total degrading/uncommon items and of the total untried items, respectively). Higher scores indicated greater engagement in or interest in trying degrading/uncommon sexual behaviors. Cronbach’s α coefficients were .64 for the Tried Scale and .69 for the Interest Scale.

Seven questions assessed being the target of mild aggression during sex ( Table 2 ). Items asked about being spanked, slapped, choked, or tied up by a partner; having one’s hair pulled by a partner; and role-playing being raped. Each item was answered on the same 6-point scale described above for aggressor behaviors. Responses to these 7 items were also recoded into two sets of variables, tried ( yes/no ) and would like ( yes/no ), and then percentage scores were created by dividing the sum of tried and would like (or interest in ) items by the number of items the participants had answered (of the total target items and of the total untried items, respectively). Higher scores indicate greater engagement in or interest in trying the different types of behaviors. Cronbach’s α coefficients for target behaviors were .73 for the Tried Scale and .71 for the Interest Scale.

For the hypothesis tests, we created two scores from the sum of the dichotomously coded variables tried and would like. For instance, a participant who had tried none of these behaviors obtained a sum score of 0, while a participant who had tried all seven of them obtained a sum score of 7. This sum score was then divided by the number of items that the participant had answered, yielding a proportion (or percentage) score. To illustrate, a participant who had tried six behaviors but only answered 6 of the 7 items obtained a percentage score of 100, identical to that of someone who had tried seven of the seven answered questions. Higher scores therefore indicated greater engagement in various aggressor behaviors during sex. Cronbach’s α for the 7-Item Tried Scale was .71. A similar score was created for the would like (or interest in ) recoded items. A ratio was calculated with the total sum of would like items as the numerator and total sum of have not tried items as the denominator. Scores indicated the percentage of untried behaviors that the participant reported they would like to try at some point in the future. Scores could range from 0% to 100%, with higher scores indicating greater interest in trying the different types of behaviors. Cronbach’s α for the Interest Scale was .67.

Seven questions assessed engagement in mild aggression during sex ( Table 2 ). Items asked about spanking, pulling hair, slapping a partner, choking, tying up a partner, and role-playing rape. Each item was answered on a 6-point scale: 1 ( tried it and liked it ), 2 ( tried it and not sure if I liked it ), 3 ( tried it and did not like it ), 4 ( have not tried it but would like to ), 5 ( have not tried it and do not want to ), and 6 ( I do not know what this means ). Responses were recoded into two dichotomous variables. The first indicated if the participant had ever tried the behavior (Responses 1–3 were coded as yes , while Responses 4–5 were coded as no ). Respondents who indicated they did not know what the question was asking were coded as missing data on that variable. Second, responses for the subgroup of participants who had not engaged in the behavior were coded to indicate if the participant had an interest in trying the behavior (Response 4 was coded as yes , Response 5 was coded as no ).

In addition to assessing frequency of use, for descriptive purposes, we asked participants to indicate what kind of pornography they consumed most often (magazines or books, video on demand or pay per view, cable television channels such as Playboy , pornographic digital video disks, and the Internet). We also asked the respondents their age at first exposure to pornography and the age at which they first used pornography for masturbation.

Two questions assessed participants’ average frequency of pornography use: one specified pornography use for masturbation and the other specified pornography use but not for masturbation. The authors did not assess reasons for pornography use other than masturbation in the current study; however, prior work indicates people frequently report use because of boredom, curiosity, stress reduction, and as part of sexual activity with a partner ( Bridges & Morokoff, 2011 ). The items were answered on an 8-point Likert-type scale (0 = never , 1 = less than once a year , 2 = a few times a year , 3 = once a month , 4 = a few times a month , 5 = 1–2 days a week , 6 = 3–5 days a week , and 7 = daily or almost daily ). The 2 items were summed to yield a total frequency of pornography use score.

Most participants (85.1%) reported having had prior dyadic sexual experiences, including being naked, touching genitals, engaging in oral sex, or having sexual intercourse (vaginal or anal). More specifically, only 12.0% of participants reported never having engaged in sexual intercourse. Of the remaining respondents who reported having engaged in sexual intercourse, 9.6% had done so prior to the age of 16, 45.7% first had sex between 16 and 18 years of age, and the remaining 17.4% first had sex at 19 years of age or later (data were missing for 15.2% of participants). Most sexually experienced respondents (87.9% of those who responded) reported three or fewer sexual partners in the past year.

Participant demographics are provided in Table 1 . Most (88.0%) respondents indicated they attended a college or university. Most (88.9%) respondents were White and 76.0% lived in a city or suburb. Average age was 22.55 years ( SD = 7.95). The majority (65% or greater) of male and female guardians of these participants had completed a college degree. Participants were primarily Protestant/Christian (32.8%) and Catholic (31.4%); 15.3% of participants were not religious. Participants reported an average level of importance of their religious faith ( M = 3.75, SD = 1.73, scale from 1 = not at all important to 6 = very important ). Many (41.2%) reported agreeing or strongly agreeing that religious faith was important to them. Half of the participants (49.8%) were not in a relationship.

As part of a larger, multinational study, we recruited a convenience sample of 1,883 men and women residing in the United States who consented to participate in our survey. Participants who did not answer a question assessing sexual orientation ( n = 20) or indicated being gay or lesbian ( n = 22), bisexual ( n = 46), or other sexual orientation ( n = 5) were excluded from the study. Fifteen percent ( n = 285) of the participants did not indicate their gender and were excluded from the study. Of the remaining 1,606 participants, 38.6% were men ( n = 620) and 61.4% were women ( n = 986).

In women, the strongest correlation was between pornography use and engagement in target sexual behaviors ( r = .209, p < .001), followed by aggressor ( r = .175, p < .001) and degrading/uncommon ( r = .143, p < .001). Again, however, Fisher’s Z tests revealed these correlations were all statistically equivalent (all p values > .05). In contrast, pornography use in women was most strongly associated with an interest in engaging in degrading or uncommon sexual behaviors ( r = .300, p < .001), followed by target ( r = .258, p < .001) and finally aggressor ( r = .202, p < .001) behaviors. The correlation between pornography use and interest in degrading/uncommon behaviors was significantly larger than the correlation between pornography use and aggressor behaviors, Z = 2.09, p = .037. All other correlations were statistically equivalent ( p values > .05).

We conducted post hoc analyses to compare correlations between pornography use and the sexual behavior questions by gender. In particular, we asked whether the increases in engaging or desiring sexual behavior associated with increased pornography use were similar across the three categories (aggressor, target, and degrading/uncommon behaviors) for men and women. In men, correlations between pornography use and engagement in sexual behaviors were strongest for aggressor ( r = .210, p < .001), followed by target ( r = .202, p < .001) and degrading/uncommon ( r = .145, p < .001). However, Fisher’s Z tests revealed these correlations were all statistically equivalent (all p values > .05). The same pattern was obtained in the correlations between pornography use and interest in engaging in various sexual behaviors (aggressor: r = .277, p < .001; target: r = .253, p < .001; degrading/uncommon: r = .233, p < .001). These three correlations were also not significantly different from one another (all p values for Fisher’s Z tests > .05).

A hierarchical multiple regression analysis was used to determine whether the percentage of degrading/uncommon sexual behaviors participants reported wanting to try could be predicted from gender (Step 1), frequency of pornography use (Step 2), and their interaction (Step 3). Preliminary analyses revealed no violations of linearity, multicollinearity, and normal distribution of residuals. The first step was significant, F (1, 1382) = 241.85, p < .001, explaining 14.9% of the variance in interest in trying degrading and uncommon sexual behaviors. At Step 1, male gender significantly predicted the criterion, β = −.39. The second step significantly incremented model fit, Δ F (1, 1381) = 128.30, p < .001, explaining an additional 7.2% of the variance. At Step 2, greater pornography use was associated with increased interest in trying degrading or uncommon sexual behaviors, β = .32. The interaction, entered at Step 3, did not significantly increment model fit, Δ F (1, 1380) = 0.26, p = .612, Δ R 2 = .00, interaction β = .02.

A hierarchical multiple regression analysis was used to determine whether the percentage of target sexual behaviors participants reported liking could be predicted from gender (Step 1), frequency of pornography use (Step 2), and their interaction (Step 3). Preliminary analyses revealed no violations of linearity, multicollinearity, and normal distribution of residuals. The first step was significant, F (1, 1373) = 4.04, p = .045, but explained only 0.3% of the variance in interest in engaging in target behaviors. At Step 1, male gender was a significant predictor, β = −.05. The second step significantly incremented model fit, Δ F (1, 1372) = 124.48, p < .001, explaining an additional 8.3% of the variance. At Step 2, greater pornography use was associated with increased interest in trying target sexual behaviors, β = .35. The interaction, entered at Step 3, significantly incremented model fit, Δ F (1, 1371) = 4.08, p = .044, Δ R 2 = .03, interaction β = .08.

A hierarchical multiple regression analysis was used to determine whether the percentage of aggressor sexual behaviors participants reported wanting to try could be predicted from gender (Step 1), frequency of pornography use (Step 2), and their interaction (Step 3). Preliminary analyses revealed no violations of linearity, multicollinearity, and normal distribution of residuals. The first step was significant, F (1, 1375) = 37.29, p < .001, explaining 2.6% of the variance in interest in trying aggressor behaviors. At Step 1, male gender was a significant predictor, β = −.16. The second step significantly incremented model fit, Δ F (1, 1374) = 101.84, p < .001, explaining an additional 6.7% of the variance. At Step 2, greater pornography use was associated with increased interest in trying aggressor sexual behaviors, β = .31. The interaction, entered at Step 3, did not significantly increment model fit, Δ F (1, 1373) = 3.03, p = .082, Δ R 2 = .02, interaction β = −.07.

Hierarchical multiple regression analyses were used to determine whether interest in engaging in a greater variety of aggressor, target, and degrading/uncommon sexual behaviors could be predicted from gender (Step 1), frequency of pornography use (Step 2), and their interaction (Step 3). 2 All analyses revealed no violations of assumptions of linearity, multicollinearity, and normal distribution of residuals. Results appear in Table 6 and are summarized below.

Descriptive statistics for interest in engaging in specific aggressor, target, and degrading/uncommon sexual behaviors are provided in Table 5 . Data are limited to those participants who reported having no prior experience with the specific behavior in the past. χ 2 analyses with a Bonferroni correction (α value set at ≤.001) revealed significant gender differences for interest in trying five of the seven aggressor behaviors, two of the seven target behaviors, and all of the seven uncommon and/or degrading sexual behaviors. The most common aggressor behaviors both men (44.3%) and women (36.5%) wanted to try was tying up a partner, while the least common was choking a partner during sex (men = 5.7%; women = 2.0%). Men were more likely than women to have interest in trying all but two of the aggressor behaviors (the exceptions were pulling a partner’s hair during sex and tying up a partner). The most common target behaviors both men (42.2%) and women (40.6%) wanted to try was being tied up by a partner, while the least common for men was being choked by a partner during sex (5.5%) and for women was having their face slapped (2.6%). Men were significantly more likely than women to want to role-play being forced into sex and have their face slapped during sex. The most common degrading/uncommon sexual behavior both men (81.8%) and women (39.4%) reported wanting to try was engaging in fellatio with the man standing and the woman kneeling, while the least common for men was interest in calling a partner names (13.1%) and for women was interest in ass-to-mouth (0.5%). Men were significantly more likely than women to want to try all of the degrading/uncommon sexual behaviors, including ejaculating on a woman’s face or mouth, engaging in double penetration, having anal sex, engaging in ass-to-mouth, and calling a partner names.

The first step was significant, F (1, 1384) = 3.88, p = .049, but explained only 0.3% of the variance in degrading/uncommon behaviors. At Step 1, male gender significantly predicted engagement in degrading or uncommon sexual behaviors, β = −.05. The second step significantly incremented model fit, Δ F (1, 1383) = 29.03, p < .001, explaining an additional 2.0% of the variance. At Step 2, greater pornography use was associated with increased engagement in degrading/uncommon behaviors, β = .17. The interaction, entered at Step 3, did not significantly increment model fit, Δ F (1, 1382) = 0.14, p = .712, Δ R 2 = .000, interaction β = .02.

The first step was significant, F (1, 1391) = 37.10, p < .001, and explained 2.6% of the variance in target behaviors. At Step 1, female gender significantly predicted engagement in target sexual behaviors, β = .16. The second step significantly incremented model fit, Δ F (1, 1390) = 59.83, p < .001, explaining an additional 4.0% of the variance. At Step 2, greater pornography use for masturbation was associated with increased engagement in target behaviors, β = .24. The interaction, entered at Step 3, did not significantly increment model fit, Δ F (1, 1389) = 1.74, p = .188, Δ R 2 = .001, interaction β = .05.

The first step was significant, F (1, 1390) = 72.63, p < .001, and explained 5.0% of the variance in aggressor behaviors. At Step 1, male gender significantly predicted engagement in aggressor sexual behaviors, β = −.22. The second step significantly incremented model fit, Δ F (1, 1389) = 54.47, p < .001, explaining an additional 3.6% of the variance. At Step 2, greater pornography use was associated with increased engagement in aggressor behaviors, β = .23. The interaction, entered at Step 3, did not significantly increment model fit, Δ F (1, 1388) = 0.51, p = .473, Δ R 2 = .0, interaction β = −.03.

Hierarchical multiple regression analyses were used to determine whether engagement in a greater variety of aggressor, target, and degrading/uncommon sexual behaviors could be predicted from gender (Step 1), frequency of pornography use (Step 2), and their interaction (Step 3). 1 All analyses revealed no violations of assumptions of linearity, multicollinearity, and normal distribution of residuals. Results appear in Table 4 and are summarized below.

Descriptive statistics for frequency of engaging in specific aggressor, target, and degrading/uncommon sexual behaviors are provided in Table 2 . χ 2 analyses with a Bonferroni correction (α value set at ≤ .001) revealed significant gender differences for engagement in six of the seven aggressor behaviors, three of the seven target behaviors, and two of the six uncommon and/or degrading sexual behaviors. The most common aggressor behaviors reported by both men (73.0%) and women (43.6%) was spanking a partner lightly, while the least common was slapping a partner’s face during sex (men = 7.1%; women = 2.9%). Men were more likely than women to have tried all but one of the aggressor behaviors (the exception was pulling a partner’s hair during sex). The most common target behaviors reported by men (47.0%) and women (65.4%) were having been spanked lightly, while the least common was having one’s face slapped during sex (men = 8.1%; women = 3.6%). Women were significantly more likely than men to have been spanked lightly or had their hair pulled by a partner during sex, while men were significantly more likely to have had their face slapped by a partner during sex. The most common degrading/uncommon sexual behavior reported by both men (70.6%) and women (64.7%) was having engaged in fellatio, with the man standing and the woman kneeling, while the least common was engaging in double penetration (men = 2.9%; women = 1.2%). Men were significantly more likely than women to have engaged in ass-to-mouth and called their partner names during sex.

In women, the average frequency of pornography use for masturbation was 1.35 ( SD = 1.88), indicating a frequency that was once per year, and the average frequency of pornography use without masturbation was 0.50 ( SD = 1.15), or less than once per year. The modal frequency of pornography use for and without masturbation was never (60.0% and 79.2% of women, respectively). A total of 55.0% of women reported “never” using pornography.

Prior to evaluating the study hypotheses, we explored the frequency of pornography use for masturbation in men and women. Descriptive statistics for pornography use are displayed in Table 3 . Men reported significantly higher frequency of pornography use, both with and without masturbation, compared to women. In men, the average frequency of pornography use for masturbation was 4.14 ( SD = 2.15), indicating a frequency that was a few times per month, and the average frequency of pornography use without masturbation was 1.41 ( SD = 1.88), or a few times per year. The modal frequency of pornography use for masturbation use was 1–2 days per week (25.9% of male participants), while the modal frequency of pornography use without masturbation was never (53.7% of men). A total of 12.3% of men reported “never” using pornography.

Discussion

Our study asked whether pornography use is associated with greater engagement in sexual behaviors frequently represented in pornographic films (Bridges et al., 2010). Furthermore, given that not all participants may have had a sexual partner with whom to try these behaviors, we explored whether pornography use related to interest in trying these sexual behaviors if an opportunity to do so arose. Utilizing sexual script theory (Simon & Gagnon, 1986; Wright, 2011), we hypothesized a positive association between pornography use and the two variables. We also examined whether frequency of engagement in or interest in trying the diverse categories of sexual behaviors (aggressor, target of aggression, and degrading and/or uncommon behaviors) would differ by gender. Because sexual scripts in pornography frequently portray female degradation (Gorman et al., 2010) and male-to-female violence (Bridges et al., 2010), we hypothesized gender would moderate the relations between pornography use and sexual behaviors.

Sexual Scripts and Behavior Overall, we found broad support for sexual script theory. Multivariate analyses demonstrated significant associations between higher pornography use and higher engagement in all three types of sexual behaviors: aggressor, target, and degrading/uncommon. The standardized regression weights in our hierarchical regressions and our post hoc analyses showed associations between pornography use and sexual behaviors were comparable in magnitude across the various categories or types. When compared to the data from Bridges et al. (2010) analysis of aggressive behavior in pornography, we found many behaviors frequently portrayed in popular pornography were less common among the sample in general. For instance, Bridges et al. found 41% of pornographic scenes depicted slapping a partner in the face during sex, but only 7% of men and 3% of women in the current study endorsed this behavior. Similarly, Bridges et al. found 28% of pornographic scenes depicted choking, compared to 16% of men and 4% of women who reported choking a partner during sex. On the other hand, other aggressive behaviors were fairly comparable in prevalence in both pornography and in the actual behavior of participants. For instance, Bridges et al. found 75% of scenes in popular pornographic films depicted spanking, compared to 73% of men and 44% of women in the current study who reported spanking a partner (and 47% of men and 65% of women who reported being spanked by a partner). Some behaviors were more commonly reported by our participants than were portrayed in pornography, including bondage/confining (present in <7% of pornographic scenes but reported by approximately 20% of our sample) and hairpulling (present in 37% of pornographic scenes but reported by over 50% of our sample). Examining sexual behaviors specifically, most of the behaviors coded in this study were more common in pornographic scenes coded by Bridges et al. (2000) than in participants’ self-reports. Engaging in double penetration, present in 19% of pornography scenes, was reported by fewer than 3% of our participants. Anal sex, present in 56% of pornography scenes, was reported by less than 30% of our participants. Ass-to-mouth was present in 41% of pornographic scenes but only attempted by 7% of male and 2% of female participants. On the other hand, men’s ejaculation on a woman’s face, present in 62% of pornography scenes, was comparable in participants’ sexual behaviors (67% of men and 62% of women). We also found significant associations between higher pornography use and higher desire to engage in all three types of sexual behaviors (aggressor, target, and degrading/uncommon) among participants who had not yet tried these. Taken together, results suggest higher pornography use is associated with higher engagement in or interest in trying sexual behavior consistent with pornographic scripts. Although our data are cross-sectional, our findings support scholars who suggest pornography can be a source of sexual education or can expand the sexual repertoire of users (e.g., Weinberg et al., 2010). Those participants who reported greater pornography use did indeed report engaging in (or interest in trying) a greater variety of sexual behaviors. Because we did not assess other sexual or intimate behaviors that are infrequently present in pornography, such as kissing, hugging, or caressing, we are unable to determine whether pornography use is associated with a greater expansion of all types of sexual behaviors or is limited to only those that are frequently portrayed in pornographic media. However, in previous research with men, we found significant associations between pornography use and lower enjoyment of sexually intimate behaviors such as kissing and caressing (Sun et al., 2016). If indeed pornography expands sexual behavior, but only to behaviors that are aggressive or uncommon/degrading, it would be important to ask what are the mental health implications for users and the public health implications for communities.

Gender Differences in Sexual Behavior Engagement In bivariate analyses, men were significantly more likely to have tried aggressor sexual behaviors frequently portrayed in pornography, including spanking a partner, slapping or choking a partner, tying a partner up, and role-playing the scenario of forcing a partner into sex. On the other hand, women were more likely to have been targets of aggression, especially spanking lightly and hairpulling. The only target behavior more frequently reported by men than women was being slapped in the face during sex. On the whole, men were more likely to have engaged in behaviors representing female degradation, including ass-to-mouth and calling their female partners names. In general, aggression against male partners by women was rare. Fewer than 10% of women reported engaging in each individual act of aggressive, with three exceptions. The exceptions included spanking a partner lightly (reported by nearly 44% of women), pulling a partner’s hair (nearly 52%), and tying up a partner (over 16%). In contrast, more than 10% of men reported engaging in each individual aggressive act save one: Only 7% of men reported having slapped a partner’s face during sex. The same gender disparity was evident in engagement in degrading/uncommon sexual acts. When examined individually, over 25% of men reported engagement in each of the degrading/uncommon behaviors with two exceptions: very few men (less than 3%) had engaged in double penetration of a woman with another man and only 7% had tried ass-to-mouth. For women, engagement in degrading/uncommon sexual behaviors was relatively rare, with two exceptions: Most female participants reported fellatio while kneeling in front of a standing male partner (nearly 65%) and most (over 62%) reported having a male partner ejaculate on their mouth or face. The opposite gender pattern was found for target behaviors. Here, all but two target behaviors (being spanked lightly and having one’s hair pulled) were reported by fewer than 20% of male participants. In contrast, more than 20% of female participants had tried four of the seven target behaviors (exceptions were role-playing being forced into sex, having one’s face slapped during sex, and being choked during sex). Multivariate analyses confirmed these gender differences in engagement across the three categories of sexual behavior: aggressor, target, and degrading/uncommon. Even when controlling for pornography use, men were significantly more likely to have engaged in a greater variety of aggressor and degrading/uncommon behaviors compared to women, while women were significantly more likely to have engaged in target behaviors compared to men. The gendered nature of our findings is interesting, although we lacked information about whether behaviors were done to express sexual agency and fulfill personal desire or, at least in part, because of perceived pressure or to acquiesce to a partner’s request. Tolman (1994) and others describe women’s lack of agency in sexual encounters, especially when those encounters are dictated by heterosexual male-focused scripts. As Tolman and Bridges and Morokoff (2011) report, young women may be motivated to engage in certain sexual behaviors primarily as a means to please a sexual partner or to view themselves from the perspective of their male partners, rather than because of a personal desire for the behavior. In fact, Tolman argues that adopting this male-centric perspective can rob young women of their ability to recognize their own feelings and sexual desires. Similarly, Walsh, Ward, Caruthers, and Merriwether (2011) find significantly more women (14%) than men (2%) report engaging in intercourse with a partner for the first time because of pressure from their partner. Thus, examining participants’ desire to engage in sexual behavior can provide additional insight.

Gender Differences in Desire to Engage in Sexual Behavior In bivariate analyses examining desire to engage in different types of sexual behavior, men were significantly more likely to report a desire to engage in all three types of behaviors. Significant differences between men and women were found for five of the seven aggressor behaviors, two of the seven target behaviors, and all of the degrading/uncommon behaviors. However, it is notable that similar proportions of men and women reported the desire to try five of the seven target behaviors. On the whole, participants who had not yet tried the different categories of behaviors did not express a strong desire to do so. The two exceptions were fellatio (which nearly 82% of men but less than 40% of women wanted to try) and ejaculating in women’s faces or mouths (which nearly 60% of men but fewer than 13% of women wanted to try). Multivariate analyses found men were significantly more likely to want to try all three categories of sexual behaviors compared to women, even after controlling for pornography use.

Pornography Use and Sexual Behavior: No Evidence of Gender Moderation We did not find significant interactions between gender and pornography use when predicting categories of sexual behavior, regardless of whether we assessed behaviors the participant reported having done in the past or behaviors the participant had not done but had interest in doing. Because pornographic sexual scripts are gendered, with women frequently being portrayed in more submissive roles, we expected pornography use would interact with gender such that behaviors that followed the gendered pornographic script would be exaggerated in men (for aggressor and degrading/uncommon behaviors) or in women (for target behaviors). The fact that bivariate analyses suggested clear differences in both engagement and interest in engaging in many behaviors, but there was no interaction between pornography use and gender, suggests pornography use does not exaggerate the gender differences already reflected in men’s and women’s sexual behavior. However, since we found positive associations between pornography use and sexual behaviors, and since significantly more men than women reported using pornography (nearly 87% of men and 40% of women in our sample), men are more likely to show or have an interest in engaging in sexual behavior that comports with the pornographic script.