Public health

Pornography vs. sexual science: The role of pornography use and dependency in U.S. teenagers’ sexual illiteracy Paul J. Wrighta, Robert S. Tokunagab, Debby Herbenick c and Bryant Paula

aThe Media School, Indiana University, Bloomington, IN, USA; bDepartment of Communication, University of Texas at San Antonio, San Antonio, TX, USA; cCenter for Sexual Health Promotion, School of Public Health, Indiana University, Bloomington, IN, USA

ABSTRACT This study examined U.S. adolescents’ pornography consumption, pornography dependency, and belief in a variety of notions contradicted by basic sexological science. Data were from 595 youth aged 14–18 who participated in a population-based probability survey. Consistent with the sexual script acquisition, activation, application model (3AM) of sexual media socialization, adolescents who had viewed pornography were more likely to hold erroneous sexual beliefs than adolescents who had not viewed pornography. Also consistent with the 3AM, more frequent pornography consumption and higher levels of pornography dependency were independently associated with holding erroneous beliefs about sex among pornography consumers. Counter to theoretical expectations, frequency of pornography consumption did not interact with pornography dependency in the prediction of erroneous sexual beliefs.

ARTICLE HISTORY Received 2 February 2021 Accepted 23 September 2021

KEYWORDS Pornography; socialization; sexual knowledge; adolescents; 3AM

The sexual script acquisition, activation, application model (3AM; Wright, 2011, 2014) has become an important theoretical perspective in research on sexual media and social learning (Laporte et al., 2020; Leonhardt et al., 2019; Ward et al., 2016). Drawing on the 3AM premise that viewers deduce lessons about sexual norms and con- sequences from prevalent depictions in pornography, many studies have tested whether more frequent pornography consumption is associated with an increased likelihood of expressing sexual attitudes and behavioral penchants consistent with pornography’s depiction of sex.

Consumption frequency is an important variable in the 3AM and deserves further research attention. But the 3AM also emphasizes the importance of pornography depen- dency, a distinct concept. Whereas frequency of consumption refers to the regularity with which an individual views pornography, pornography dependency refers to the extent to which a person relies on pornography to learn about sex. Persons who consume porno- graphy frequently may also be dependent on pornography for sexual information, but consumption and dependency are not synonymous according to the 3AM. For instance, according to the model, a person may habitually use pornography for masturbatory

© 2021 National Communication Association

CONTACT Paul J. Wright [email protected] Supplemental data for this article can be accessed at https://doi.org/10.1080/03637751.2021.1987486

COMMUNICATION MONOGRAPHS 2022, VOL. 89, NO. 3, 332–353 https://doi.org/10.1080/03637751.2021.1987486

stimulation (Emmers-Sommer, 2018), but primarily turn elsewhere for pedagogical information about sex (e.g., medical websites, health care workers). Likewise, the model allows for the possibility that pornography may be a person’s primary source of sexual information, even though they only view it on occasion (Wright et al., 2018).

Despite the centrality of pornography dependency to the 3AM, no previous study has tested the role it plays in the acquisition of sexual knowledge. As evidence mounts that the use of pornography is associated with certain adverse health outcomes among ado- lescents (Hornor, 2020; Ward et al., 2016; Wright et al., 2016), scholars have suggested that an important health positive effect may be an increase in accurate knowledge about sex (Peter & Valkenburg, 2016; Short et al., 2012; Watson & Smith, 2012). Remark- ably, despite this being a readily testable and oft-repeated conjecture, a recent mixed- methods systematic review found that “no articles attempted to measure or discuss whether people who access pornography have better (or worse) skills and knowledge about sex and sexual health than those who do not” (Litsou et al., 2021, p. 236). Using data from a population-based probability survey, the present study examined associ- ations between U.S. adolescents’ use of, frequency of exposure to, and dependence on pornography and belief in a variety of notions that are contradicted by basic sexological science.

Pornography and sexual learning

For many years, research on the socializing effects of sexual media tended to be either variable analytic and not tied to any particular theory or based on theories not originally created with sexual media in mind (Ward, 2003). This changed with the development of the 3AM (Wright, 2011). The 3AM is a critical synthesis and integration of a variety of mass communication, information processing, and behavioral theories (e.g., the heuristic processing model of cultivation effects, social cognitive theory, priming, information processing model of aggression, uses and gratifications), as well as conceptual and empirical work not formally tied to any particular theoretical perspective. It posits a mul- tipart sequence for socialization effects and a variety of pathways through which effects can result. Originally articulated in the context of the mainstreammedia’s effect on youth sexuality (e.g., television, movies, music videos), the 3AM has since been applied to youth and pornography (Wright, 2014).

At its core, the model proposes that the socializing effects of sexual media are carried through the acquisition, activation, and application of sexual scripts. Sexual scripts are symbolically imparted guidelines for sexual behavior; they answer questions about whom should be engaging in what types of sexual activities with whom, when, how, under what circumstances, and to what consequence. Accordingly, the sexual scripts people possess have a direct impact on their sexual beliefs and attitudes, which can ulti- mately impact their sexual behavior. Script acquisition refers to the learning of a novel script due to media exposure. Script activation refers to media exposure priming an already acquired script. Script application refers to the use of a script that has been acquired and activated to guide a judgment or behavioral decision (Wright, 2011).

Studies are increasingly utilizing the 3AM to hypothesize that exposure to pornogra- phy is a predictor of sexual outlooks and predilections consistent with pornography’s presentation of sex. Recent meta-analyses have supported this hypothesis in the contexts

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of sexual aggression, condom use, and impersonal sexual attitudes and behaviors (Toku- naga et al., 2019, 2020; Wright et al., 2016). Although 3AM informed studies such as these have generated important insights into mediated sexual socialization processes and effects (Grubbs et al., 2019), the outcome variables studied to date have not been amen- able to the question of whether using pornography is associated with being more or less likely to hold beliefs that are inconsistent with human sexuality research. Adolescents who view pornography may be less likely to use condoms and more likely to see sex as a recreational pursuit, for example, but whether or not to use condoms and philoso- phical views on the nature of sexuality involve subjective evaluations for which there is no “right” or “wrong” answer. The present study addressed this gap in the pornography lit- erature by testing sexual beliefs that are contrary to the findings of sexological studies.1

Erroneous sexual messages in popular pornography

Pornography scholars have observed a number of recurrent messages about sex in popular, commonly consumed pornography (Ainsworth-Masiello & Evans, 2019; Bridges et al., 2010; Dawson et al., 2020; Dines, 2010; Klaassen & Peter, 2015; Rothman et al., 2020). The following messages, in particular, have been noted: women have orgasms relatively easily through vaginal intercourse; it is common for women to “squirt” fluids when they have orgasms; men must have large penises to satisfy their part- ners; men are able to engage in sustained thrusting without climaxing in order to prolong intercourse for an extended period of time; most women enjoy anal sex; men prefer mul- tiple nonexclusive sexual encounters to a committed relationship and enjoy romantic sex much less than women do; rough sex is common (e.g., sex involving gagging, spanking, and insults), whereas more gentle sex is comparatively rare (e.g., sex involving kissing, hugging, and complements).

Each of these messages is incorrect according to basic human sexuality research. Most women do not experience orgasms easily through vaginal intercourse (Herbenick et al., 2018; Shirazi et al., 2018). Few women “squirt” when orgasming (Pastor, 2013; Pastor & Chimel, 2017; Salama et al., 2015). Sexual satisfaction during sex with men is not depen- dent on penis size (Lever et al., 2006; Stulhofer, 2006). Intercourse involving males does not usually last very long prior to ejaculation (Miller & Byers, 2004). Most women do not enjoy anal sex (Herbenick et al., 2017). Men are much more likely to have monogamous sex than sex with casual partners (Levine et al., 2018) and enjoy romantic sex as much as women do (Herbenick et al., 2017). Finally, affectionate sex is more common and pre- ferred than rough sex (Herbenick et al., 2017). In sum, pornography sends many fantas- tical messages about sex that are factually incorrect.

Present study

The first aim of the present study was to address an important theoretical gap in the por- nography literature. The 3AM identifies a number of content (e.g., message simplicity and functionality), audience (e.g., identification with and perceived similarity to actors in pornography), and situational (e.g., time pressure to make decisions and heightened sexual arousal) factors that make the acquisition, activation, and application of sexual scripts following sexual media exposure more likely (Wright et al., 2019, 2020, 2021).

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One important factor put forth by the model that remains untested, however, is depen- dency on pornography for sexual learning.

From a 3AM perspective, pornography dependency functions as a predictor of sexual socialization effects in and of itself (Wright, 2011), as well as a contributory moderator (Holbert & Park, 2020) of the effects of frequent consumption (Wright, 2014). Pornogra- phy dependency functions as a predictor of sexual socialization because persons who are more dependent on pornography for sexual learning are theorized to be more likely to ascribe to pornography’s presentation of sociosexual reality than persons who are less dependent on pornography for sexual learning, even though their rates of consumption are similar. Pornography dependency functions as a contributory moderator of the effects of frequent consumption because the socializing effects of repetitive exposure to pornography’s sexual messages on pornography-consistent beliefs are theorized to be enhanced when dependency is high. To rephrase in statistical terms, the 3AM predicts the main effects of pornography dependency and pornography consumption frequency on pornography-consistent beliefs, as well as an interaction between the two such that the positive association between consumption frequency and beliefs grows in magnitude as dependency increases (see Online Supplemental Figure 1 for a conceptual illustration). The present study tested these central 3AM tenets via its first three hypotheses:

H1: Pornography dependency predicts adolescents’ erroneous beliefs about sex.

H2: Pornography consumption frequency predicts adolescents’ erroneous beliefs about sex.

H3: Pornography consumption frequency interacts with pornography dependency to predict adolescents’ erroneous beliefs about sex, such that the positive association between con- sumption frequency and beliefs grows in magnitude as dependency increases.

The present study also addressed several methodological questions and debates in the literature related to the measurement of pornography exposure. Several review articles have questioned the predictiveness of dichotomous pornography exposure measures (i.e., measures that classify participants according to whether or not they have viewed pornography) (Kohut et al., 2020; Short et al., 2012). However, at the culmination of their review article, Harkness et al. (2015) lamented that “the majority of reviewed studies did not compare indicators of sexual risk behaviors to a control population of nonpornography users” and said this practice “is recommended for future work” (p. 11). Comparing those who have seen pornography to those who have not is especially important in research on adolescents, given that many have not viewed pornography (Peter & Valkenburg, 2016). Because the 3AM states that pornography consumers and nonconsumers should differ in their sexual beliefs, a fourth hypothesis was advanced:

H4: Adolescents who have seen pornography are more likely to hold erroneous beliefs about sex than adolescents who have not seen pornography.

Most studies of pornography and sexual socialization have used general, content non- specific consumption measures (Grubbs et al., 2019; Kohut et al., 2020; Ortiz & Thomp- son, 2017; Peter & Valkenburg, 2016). However, consumption measures that do not assess specific content elements have come under heavy criticism in recent years (Kohut et al., 2020; Ortiz & Thompson, 2017; Short et al., 2012). This perspective argues that there are vast dissimilarities in messages about sex across various

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pornographic media and content nonspecific measures will, consequently, be unpredic- tive. Kohut et al. (2020), for example, wrote that the “manner and context” of porno- graphic presentations “differ tremendously from stimulus to stimulus” (p. 733). They stated that there is “substantial variation” in the messages pornography sends about sex (p. 733) and called for the use of content-specific measures. The content nonspecific measures used in prior studies are seen by Kohut et al. (2020) as part of what has made the study of pornography use (in their opinion) a “shaky science resting on poor measurement foundations” (p. 722). Likewise, Ortiz and Thompson (2017) argued that it is “nearly impossible” to draw conclusions from the consumption measures used to date because they “fail to consider the specific type of pornography being consumed” (p. 9).

An alternative perspective acknowledges the hypothetical discoverability of widely discrepant pornographic scripts, but posits that the scope, scale, and influence of the largest and most powerful pornography production and distribution companies leads to the predominance (and emulation) of the particular scripts they have found to be profitable (Bridges et al., 2010; Jensen & Dines, 1998; Sun et al., 2008). For instance, at the conclusion of their content analysis that failed to find differences in the fundamental nature of the sexual scripts of pornographic videos directed by either men or women, Sun et al. (2008) wrote that “market pressures” have led female directors to “create a porno- graphic world that is remarkably similar to that of their male counterparts” (p. 322). From this perspective, content nonspecific measures are adept at predicting sexual socia- lization outcomes because the more people consume pornography, the more likely they are to be exposed to the predominate patterns (particularly in the era of algorithmic rec- ommendations and sponsored content). To rephrase in the context of the present study, this perspective would argue that the more frequently adolescents consume pornography, the more likely they are to be exposed to the specific categories of common, industry- typical content that promulgate erroneous sexual beliefs, and the more likely they will be to adopt those beliefs.

In sum, the former perspective argues that pornography is so diverse and multifaceted that general, content nonspecific consumption measures lack predictive utility. Conver- sely, the latter perspective argues that general, content nonspecific consumption measures are predictive because certain fantastical sexual messages predominate the por- nography landscape. The more people consume pornography, the more likely it is that they are exposed to those messages. Because the findings of several recent meta-analyses have implied that recurrent pornography consumption is associated with an increased likelihood of exposure to common sexual scripts in pornography (Tokunaga et al., 2019, 2020; Wright et al., 2016), the present study adopted the latter perspective and posed the following hypothesis:

H5: The association between frequency of consumption and erroneous beliefs about sex is mediated by increased exposure to fantastical pornographic categories.2

Finally, Peter and Valkenburg (2016) concluded that insufficient attention has been paid to the characteristics of adolescents that increase or decrease their likelihood of learning from pornography. Based on their recommendations, as well as Kohut et al.’s (2020) more recent review of research on pornography use, the present study evaluated the potential moderating impact of sexual experience and intentionality of pornography

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exposure in addition to pornography dependency. It is important to note that, though potentially correlated, intentionality of exposure is not isomorphic with pornography dependency. Pornography dependency refers to a reliance on pornography for sexual learning, but sexual learning is just one of many reasons for intentional pornography exposure (e.g., sexual arousal, masturbation, curiosity, boredom, relational enhancement, stress relief, etc.; see Grubbs et al., 2019, for a review).

Peter and Valkenburg (2009) suggested that the effects of pornography on youth may dissipate as they become more sexually experienced. If sexual experience results in youth perceiving pornography’s presentation of sex as unrealistic, they should be less impacted than youth who lack sexual experience (Wright et al., 2020). A study of Croatian youth found, however, that sexual experience and perceptions of pornography’s realism were uncorrelated over time (Wright & Stulhofer, 2019). Researchers have also suggested that it is important to distinguish between intentional and unintentional pornography exposure. Specifically, Peter and Valkenburg (2016) suggested that effects are more likely for intentional than unintentional exposure. Kohut et al. (2020) noted, however, that the hypothesis of differential impacts by exposure intent “has yet to be demon- strated” (p. 731). In sum, the impact of pornography on youth sexuality may be moder- ated by sexual experience and intentionality of pornography exposure, but conflicting opinions and insufficient data preclude the positing of directional hypotheses. Therefore, the following two research questions are proposed:

RQ1: Are the associations between the pornography variables and erroneous sexual beliefs moderated by intentionality of pornography exposure?

RQ2: Are the associations between the pornography variables and erroneous sexual beliefs moderated by sexual experience?

Method

Procedure and participants

The data for the present paper came from The National Survey of Pornography Use, Relationships, and Sexual Socialization (NSPRSS), a population-based probability survey of Americans aged 14–60 (Herbenick et al., 2020). Study measures and protocols were reviewed and approved by the institutional review board at the first author’s insti- tution. Research funding was provided by The Harnisch Foundation, Artemis Rising Foundation, The Fledgling Fund, and Embrey Family Foundation, among others (see acknowledgments). Participants were sampled from KnowledgePanel®, a probability- based online panel designed to be nationally representative of non-institutionalized, English-speaking Americans. Individuals in the U.S. are randomly selected to be invited into the panel; those without access to the internet are provided with access if they wish to join the panel.

The target population consisted of adults aged 18–60, as well as an oversample of adults and their 14- to 18-year old son or daughter. Post-stratification statistical weights were used to correct for nonresponse or under- or over-coverage. Adults were recruited directly from KnowledgePanel, whereas adolescents were recruited through their participating parents. Parents were assured that their children would only be

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asked sexuality-related questions correspondent to their level of sexual experience. For instance, only those who reported having already been exposed to pornography were asked more detailed questions about their pornography consumption. Parents were asked to provide their adolescent respondents with total privacy while taking the survey and all participants were told that the researchers would have no access to their names or other identifiers.

The NSPRSS adolescent sub-sample included 614 youth. Of these, 595 responded to the sexual belief items and were the focus of the present analysis.3 They spanned 48 states, ranged in age from 14 to 18, and were 15.96 years old on average (SD = 1.39). White youth (coded 0) comprised 55.40% of the sample, whereas 44.60% were youth of color (coded 1). Female youth (coded 0) comprised 50.70% of the sample, whereas 49.30% were male youth (coded 1). Heterosexual youth (coded 0) comprised 94.50% of the sample, whereas 5.50% were sexually diverse (i.e., LGB+, coded 1). Correlations between these variables and the focal measures are presented in Table 1.

Measures

The present study’s focal measures are described below. Descriptive statistics are reported, including skewness and kurtosis for nonbinary variables (with absolutes values > than 2 considered a signal for transformation). McDonald’s omegas were com- puted using the macro developed by Hayes and Coutts (2020).

Erroneous sexual beliefs To assess erroneous sexual beliefs, participants were asked to evaluate the veracity of the following statements: Penis size is very important to a man’s ability to satisfy his partner; Most women squirt lots of fluid when they have an orgasm; Most women would enjoy receiving anal sex; Most people prefer rough sex to gentle sex; On average, sexual inter- course usually lasts for about 30 min; Women enjoy romantic sex much more than men do; Most men would rather have sex with lots of people than be in an exclusive relation- ship; Most women easily have orgasms during intercourse. Affirmative responses (i.e., selecting “true”) to each statement were coded 1; nonaffirmative responses (e.g., selecting “false”) were coded 0.

The indices from a CFA using weighted least squares estimation indicated that remov- ing the anal sex and ease of orgasm indicators would result in a conventionally acceptable degree of model fit, χ2(9) = 10.53, p = .31, CFI > .99, RMSEA = .02 90% CI [.00, .05], SRMR = .05. When responses were summed to form a trimmed index using the remain- ing six items, descriptive statistics were: McDonald’s ω = .76; M = 1.18, SD = 1.49; skew- ness = 1.11; kurtosis = 0.21.4

Pornography exposure Participants were asked whether they had ever viewed pornography (0 = No, 1 = Yes). Participants were told that by “pornography” the survey meant “sexually explicit pictures, videos, or livestreams showing clearly exposed genitals, or, in which people are clearly shown having sex, such as oral sex, vaginal sex, or anal sex.” Whereas 48.60% of youth had viewed pornography, 51.40% had not.

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Table 1. Zero-order correlations. Variable 1 2 3 4 5 6 7 8 9 10 11

1. Sexual beliefs – 2. Porn exposure .29** – 3. Porn frequency .22** n/a – 4. Porn categories .31** n/a .47** – 5. Porn dependency .30** .39** .46** .57** – 6. Porn intentionality .02 n/a .27** .19** .17** – 7. Age .22** .13** .10 .23** .15** .04 – 8. Person of color .06 .02 .05 .03 .05 .00 .01 – 9. Male .09* .20** .11 .20** .26** .21** –.02 –.02 – 10. Sexually diverse .01 .21** .08 .15* .10** –.05 .11** .04 –.14** – 11. Sexually experienced .36** .24** .29** .39** .31** .09 .39** .05 –.02 .22** –

Note: Correlations between porn frequency, porn categories, porn intentionality and porn exposure are not applicable (n/a) because porn exposure was a constant. *p < .05. **p < .01.

C O M M U N IC A TIO

N M O N O G RA

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Frequency of pornography consumption Participants who had seen pornography were asked about their frequency of consump- tion in the past year (1 = never, 5 = every day) across a range of channels and mediums (free porn websites, paid porn websites, social media, smartphone, tablet or computer). The indices from a CFA using maximum likelihood estimation indicated that removing the free porn websites indicator would result in a conventionally acceptable degree of model fit, χ2(2) = 4.71, p = .10, CFI > .99, RMSEA = .07 90% CI [.00, .15], SRMR = .03. When responses were averaged to form a trimmed index using the remaining four items, descriptive statistics were: McDonald’s ω = .82; M = 1.58, SD = 0.79; skewness = 1.41; kurtosis = 1.04.

Exposure to pornographic categories Participants who had seen pornography were also asked about their exposure to specific categories known to commonly depict actors and activities that are uncommon among real-world persons and their sexual activities. The categories (0 = Have not seen, 1 = Have seen) were: gangbang (i.e., multiple different people having sex with one person after another), facial ejaculation (i.e., a male ejaculating on a person’s face), double-pen- etration (i.e., two or more penises or objects in one person’s vagina and/or anus at the same time), rough oral sex (i.e., a male forces or aggressively thrusts his penis in and out of a person’s mouth), amateur (i.e., “regular” people who are ostensibly not pro- fessional models or actors), BDSM (i.e., bondage/ domination), coercion (i.e., someone seems to be persuaded or forced to do something sexually they are unsure if they want to do or don’t want to do), and simulated rape.

The indices from a CFA using weighted least squares estimation indicated that remov- ing the gangbang and simulated rape indicators would result in a conventionally accep- table degree of model fit, χ2(9) = 14.01, p = .12, CFI = .96, RMSEA = .04 90% CI [.00, .08], SRMR = .04. When responses were summed to form a trimmed index using the remain- ing six items, descriptive statistics were: McDonald’s ω = .82; M = 1.69, SD = 1.85; skew- ness = 1.11; kurtosis = 0.08.

Pornography dependency Participants were asked where they had learned the most about sexual intercourse, oral sex, different sexual positions, women’s sexual anatomy, how to talk to a partner about sex, and sexual pleasure and orgasm. These are important domains of sexual knowledge. Participants who indicated they had learned more from pornography than any other source (e.g., parents, school, health classes) were coded 1 for each topic. Those who had learned the most from a source other than pornography were coded 0 for each topic.

The indices from a CFA using weighted least squares estimation indicated that remov- ing the oral sex and sex talk indicators would result in a conventionally acceptable degree of model fit, χ2(2) = 6.38, p = .04, CFI = .93, RMSEA = .03 90% CI [.00, .05], SRMR = .09. When responses were summed to form a trimmed index using the remaining four items, descriptive statistics were: McDonald’s ω = .83; M = 0.37, SD = 0.89; skewness = 2.55; kurtosis = 5.87. Due to the skewness and kurtosis values > 2 for this variable, a binary version was also created to assess the robustness of the results generated by the interval version (0 = pornography was not indicated as the primary source for any topic [82.10%], 1 = pornography was indicated as a primary source for at least one topic [17.90%]).

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Intentionality of pornography exposure The majority of youth who had seen pornography were not seeking it the first time they saw it (82.40%, coded 0), whereas 17.60% were seeking pornography the first time they saw it (coded 1).

Sexual experience The majority of youth (77.30%) were not sexually experienced (i.e., had not engaged in oral, vaginal, or anal sex; coded 0), whereas 22.70% were sexually experienced (coded 1).

Analytic approach

The main effect predictions ofH1,H2, andH4 were tested with Pearson r and hierarchical multiple regression analyses. The interactions proposed in H3, RQ1, and RQ2 were tested with hierarchical multiple regression analyses. Simple-slope tests and interaction plotting were used to interpret significant interactions. To test H5, the intervening paths of the indirect effect and subsequently the direct effect were estimated using path analysis. The mediation was tested using a 10,000 bootstrap resampling procedure to estimate the bias corrected 95% confidence interval around the indirect effect. SPSS and SAS were the statistical packages employed.

Results are reported for both the original and transformed versions of the pornogra- phy dependency measure, which was dichotomized due to skewness and kurtosis. Additionally, robustness checks were executed to probe whether gender,5 sexual orien- tation, ethnicity, and age were potential confounds. These are conventionally suggested covariates in pornography effects research (Peter & Valkenburg, 2011; Wright, 2020; but see Wright, 2021, for a critical review of the conventional approach). Because males are more likely to consume pornography than females and sometimes differ in their sexual beliefs, gender may confound pornography/sexual belief associations. Similarly, because some data have suggested that sexually diverse persons are more likely to use to pornography than heterosexual persons and differ in certain sexual beliefs, sexual orientation may confound pornography/sexual belief associations. Like- wise, differences in pornography use and approaches to sexuality between white persons and persons of color suggest that ethnicity may confound pornography con- sumption/sexual belief associations. Finally, developmental differences due to aging may affect both youths’ use of pornography and sexual beliefs, suggesting that age is also a potential confound.

Results

H1 predicted that pornography dependency would predict adolescents’ erroneous beliefs about sex. It was supported. The more dependent adolescents were on pornography for sexual learning, the more erroneous sexual beliefs they held (r = .30, p < .01). As shown in Table 2, this association maintained after adjusting for age, ethnicity, gender, sexual orientation, and pornography consumption frequency (b* = .18, p < .01). Results with the dichotomized version of the pornography dependency variable also supported H1

(b* = .17, p < .01).

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H2 predicted that pornography consumption frequency would predict adolescents’ erroneous beliefs about sex. H2 was supported. The more frequently adolescents con- sumed pornography, the more erroneous sexual beliefs they held (r = .22, p < .01). As shown in Table 2, this association maintained after adjusting for age, ethnicity, gender, sexual orientation, and pornography dependency (b* = .18, p < .01).

H3 predicted that pornography consumption frequency would interact with pornogra- phy dependency to predict adolescents’ erroneous beliefs about sex, such that the con- sumption frequency/erroneous beliefs association would be larger when pornography dependency was higher and smaller when pornography dependency was lower. H3 was not supported. As shown in Table 3, the interaction between pornography consumption frequency and pornography dependency was not significant (b* = –.09, p = .59). Results with the dichotomized version of the pornography dependency variable were also not significant (b* = –.11, p = .56).

Table 2. Pornography main effects.

Porn exposure model Porn dependency and porn

frequency model

Porn dependency (dichotomous) and porn

frequency model

Predictors ΔR2 b b* sp2 ΔR2 b b* sp2 ΔR2 b b* sp2

Step 1 .05** .05** .05** Age .25** .20 .040 .22** .17 .027 .22** .17 .027 Person of color .17 .05 .003 .50* .13 .018 .50* .13 .018 Male .31* .09 .008 .06 .02 .000 .06 .02 .000 Sexually diverse .00 .00 .000 –.60 –.10 .009 –.60 –.10 .009 Step 2 .07** .09** .08** Porn exposure .93** .27 .066 Porn dependency .30** .18 .025 Porn dependency (dichotomous)

.66** .17 .021

Porn frequency .42** .18 .024 .43** .18 .026 R2 Total .12** .14** .13**

Notes: Porn exposure model includes all adolescents. Porn dependency and porn frequency models include adolescents who had seen pornography. b = unstandardized regression coefficient. b* = standardized regression coefficient. sp2 = squared semipartial correlation. Pornography exposure is a constant in models with pornography dependency and por- nography frequency.

*p < .05. **p < .01.

Table 3. Pornography frequency × pornography dependency interaction effects. Predictors ΔR2 b b* sp2

Step 1 .09** Porn frequency .29** .14 .016 Porn dependency .28** .20 .032 Step 2 .00 Porn frequency × porn dependency –.05 –.09 .001 R2 Total .09** Step 1 .08** Porn frequency .32** .16 .012 Porn dependency (dichotomous) .57** .17 .023 Step 2 .00 Porn frequency × porn dependency (dichotomous) –.15 –.11 .001 R2 Total .08**

Notes: b = unstandardized regression coefficient. b* = standardized regression coefficient. sp2 = squared semipartial cor- relation.

**p < .01.

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H4, which predicted that adolescents who had seen pornography would be more likely to hold erroneous beliefs about sex than adolescents who had not seen pornography, was supported. Adolescents who had seen pornography were more likely to hold erroneous beliefs about sex than adolescents who had not seen pornography (r = .29, p < .01). As shown in Table 2, this association maintained after adjusting for age, ethnicity, gender, and sexual orientation (b* = .27, p < .01).

H5 predicted that the association between frequency of pornography consumption and erroneous beliefs about sex would be mediated by exposure to specific categories of pornography known to commonly depict actors and activities that are uncommon among real-world persons and their sexual activities. This hypothesis was supported. The more frequently adolescents consumed pornography, the more categories of fantas- tical pornography to which they were exposed (b* = .47, p < .01). Additionally, the more categories of fantastical pornography they were exposed to, the more they adhered to erroneous beliefs about sex (b* = .31, p < .01). The association between pornography con- sumption frequency and erroneous sexual beliefs was mediated by exposure to more fan- tastical pornographic categories (indirect effect: b = .26, bootstrap SE = .11, 95% CI: .09, .50). The direct effect between pornography consumption frequency and erroneous sexual beliefs was not significant (b* = .10, p = .11). The variance accounted for in erro- neous sexual beliefs was 9.80%.

This pattern of associations maintained after adjusting for age, ethnicity, gender, and sexual orientation. The more frequently adolescents consumed pornography, the more categories of fantastical pornography to which they were exposed (b* = .42, p < .01). Additionally, the more categories of fantastical pornography they were exposed to, the more they adhered to erroneous beliefs about sex (b* = .32, p < .01). The association between pornography consumption frequency and erroneous sexual beliefs was mediated by exposure to more fantastical pornographic categories (indirect effect: b = .23, boot- strap SE = 0.10., 95% CI: .08, .45). The direct effect between pornography consumption frequency and erroneous sexual beliefs was not significant (b* = .10, p = .10). The var- iance accounted for in erroneous sexual beliefs was 14.36%.

RQ1 asked if the pornography/erroneous sexual belief associations were moderated by intentionality of pornography exposure. The associations between erroneous beliefs and pornography consumption frequency, pornographic categories, and pornography depen- dency were not moderated by intentionality of pornography exposure (pornography exposure x intentionality was not a testable interaction because pornography exposure is a constant across those who have seen pornography, whether intentionally or uninten- tionally). In other words, results were consistent regarding the associations between por- nography variables and erroneous sexual beliefs regardless of intentionality of pornography exposure. The details of these null results are reported in Online Sup- plemental Table 1.

RQ2 asked if the pornography/erroneous sexual belief associations were moderated by sexual experience. The associations were indistinguishable across sexual experience for pornography exposure, pornography consumption frequency, and pornographic cat- egories. The details of these null results are reported in Online Supplemental Table 2.

The only significant interaction was between pornography dependency and sexual experience. As indicated by the negative interaction terms in Table 4, the pornography dependency/erroneous sexual beliefs association was stronger for sexually inexperienced

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youth regardless of the version of the pornography dependency variable examined. Figure 1 displays the interaction using the continuous pornography dependency variable; simple-slope tests indicated that the positive pornography dependency/sexual beliefs association was significant for sexually inexperienced youth (b = .70, p < .01), but not for sexually experienced youth (b = .06, p = .53). However, as shown in Table 4, the con- sistently large main effect association between sexual experience and erroneous sexual beliefs suggests that the reason why the pornography dependency/sexual beliefs associ- ation is stronger for sexually inexperienced youth is because sexually experienced youth are already likely to hold erroneous sexual beliefs (i.e., a ceiling effect dynamic).

Post hoc analysis

Given the positive correlation between pornography dependency and sexual experience, and the positive correlation between sexual experience and erroneous sexual beliefs (see

Table 4. Pornography dependency × sexual experience interaction effects. Predictors ΔR2 b b* sp2

Step 1 .16** Porn dependency .36** .22 .042 Sexually experienced 1.01** .28 .072 Step 2 .03** Porn dependency × sexually experienced –.64** –.31 .033 R2 total .19** Step 1 .17** Porn dependency (dichotomous) .86** .22 .045 Sexually experienced 1.02** .29 .076 Step 2 .01** Porn dependency (dichotomous) × sexually experienced −1.03** –.19 .015 R2 Total .18**

Notes: b = unstandardized regression coefficient. b* = standardized regression coefficient. sp2 = squared semipartial cor- relation.

**p < .01.

Figure 1. Interaction between pornography dependency and sexual experience on erroneous sexual beliefs.

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Table 1), it may be the case that youth who are dependent on pornography for sexual learning are more likely to precociously enact scripts for sex they have seen in pornogra- phy, which then reinforces the erroneous sexual beliefs they learned from pornography in the first place (pornography dependency → sexual experience → erroneous sexual beliefs). This would explain both the association between pornography dependency and sexual experience, and the ceiling effect for the relationship between pornography dependency and erroneous sexual beliefs among sexually experienced youth. A sup- plemental mediation test was conducted to test the plausibility of this learning, behavior, reinforcement dynamic. Because sexual experience was a binary variable, the mediator link was the logit function while the outcome link remained the identity function (see VanderWeele, 2015). Analysis indicated that the indirect effect was significant (indirect effect: b = 0.12, bootstrap SE = 0.03, 95% CI: 0.06, 0.20). Youth who are dependent on pornography for sexual learning are more likely to hold erroneous sexual beliefs, and this association is mediated by their early sexual experience. Results were parallel when the binary pornography dependency measure was used as the predictor (indirect effect: b = 0.26, bootstrap SE = 0.27, 95% CI: 0.15, 0.43).

Discussion

The present study used data from a population-based probability survey to examine associations between U.S. adolescents’ use of, frequency of exposure to, and dependence on pornography and belief in a variety of notions that are contradicted by basic sexolo- gical science. According to the 3AM of sexual media socialization (Wright, 2011, 2014), pornography dependency should predict adolescents’ erroneous sexual beliefs in and of itself and also enhance the effects of frequent consumption (i.e., act as a contributory moderator of consumption frequency effects, Holbert & Park, 2020). From a 3AM per- spective, pornography dependency should function as a standalone predictor because persons who are more dependent on pornography for sexual learning should (on average) have different sexual beliefs than persons who are less dependent on pornogra- phy for sexual learning, even though they consume pornography at a similar rate. Additionally, a 3AM perspective would predict an interaction between pornography con- sumption frequency and pornography dependency, such that the magnitude of the relationship between consumption frequency and change in sexual beliefs is enhanced as dependency increases.

In alignment with the 3AM’s specification of pornography dependency as a phenom- enon distinct from pornography consumption frequency, the association between depen- dency and erroneous sexual beliefs maintained after controlling for consumption frequency. Contrary to the 3AM’s identification of pornography dependency as a mod- erator of consumption frequency, consuming pornography more regularly was associ- ated with an increased likelihood of holding erroneous sexual beliefs regardless of adolescents’ level of pornography dependency.

Pragmatically, these results suggest that pornography consumption frequency and dependency independently increase adolescents’ sexual illiteracy. Intervention efforts designed to ameliorate pornographic misinformation (such as pornography literacy edu- cation, e.g., Rothman et al., 2020) need to address both how often youth consume por- nography and how much they depend on it for sexual information. Theoretically, these

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results support the 3AM’s identification of pornography dependency as an important ingredient in pornographic socialization, but suggest a reconsideration of the model’s postulate about the moderating impact of pornography dependency on consumption fre- quency (at least among adolescents). It could be the case that consistent exposure to por- nography’s version of sociosexuality reality affects adolescents similarly regardless of their reliance on other sources of sexual social influence. Replications are needed before this 3AM postulate is modified, however, given that the present study represents the first test of the role of pornography dependency and evaluated a very particular set of sexual beliefs.

In addition to its theoretical goals, the present study had two methodological goals. The first methodological goal was to test whether, in the entire sample, pornography use or nonuse predicted erroneous sexual beliefs. Consumer/nonconsumer measures have been used in many prior studies but have also been critiqued as unpredictive (Hark- ness et al., 2015). Given that many adolescents do not consume pornography, it seems important to compare those who do with those who do not. Following the results of a recent meta-analysis on pornography and satisfaction that found theoretically expected results from dichotomous assessments (Wright et al., 2017), the results of the present study suggest that it is time to reconsider the rote dismissal of consumer/nonconsumers measures (especially among adolescents). Of course, a dose–response conceptualization of pornography effects indicates the merit of assessing additional variability in exposure. But consumer/nonconsumers indices have provided important information in previous studies and should continue to be utilized, where appropriate, and evaluated on a case- by-case basis, rather than summarily dismissed.

The study’s second methodological goal was to test the predictiveness of a content nonspecific frequency of consumption measure among youth who indicated that they had seen pornography. Like binary measures of exposure, general measures of exposure frequency have been used regularly in the pornography literature. They have been cri- tiqued, however, on the basis that pornography is so diverse in its presentation of sex that researchers must assess exposure to specific content elements in order to find the associations they anticipate.

A counter to this position is that market forces and industry norms have created a situation where exposure to a diversity of pornographic scripts is more a hypothetical possibility than a consumption reality for most frequent pornography consumers. This perspective relies on content analyses to establish the primary patterns in pornographic media. According to this perspective, the more frequently people consume pornography, the more they encounter the predominate patterns, and the more predictable their sexual beliefs become.

The results of the present study support the latter approach. Specifically, mediation results were consistent with the position that the reason why consumption frequency measures are predictive is because recurrent consumption is associated with an increased likelihood of exposure to predominate pornographic sexual scripts. This is not to say that content-specific measures are unimportant and should not be utilized. It is to say, however, that findings from prior works using content nonspecific measures should be taken seriously, and that there are validity arguments for their continued use. Content-specific measures, for example, rely on participants’ interpretation of porno- graphic content and survey questions regarding it, as well as accurate recall of the

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types of content they consume. The current results suggest there may be instances where it is preferable to rely on findings from content analyses when making inferences about themes in commonly consumed pornography and avoid susceptibility to participants’ response biases and recall errors.

An additional aim of the present effort was to respond to calls for contingency testing in research on pornography and adolescents (Peter & Valkenburg, 2016). Following the recommendations of recent narrative review articles (e.g., Kohut et al., 2020; Peter & Valkenburg, 2016), the present study evaluated the potential moderating impact of inten- tionality of pornography exposure and sexual experience. Intentionality of pornography exposure was not a moderating factor, suggesting that observation is the key component in sexual media scripting processes, rather than intentionality of observation.

The nature of the correlations among the variables involved in the interaction between pornography dependency and sexual experience imply that facilitating and reinforcing effects may be operable. The association between pornography dependency and erro- neous sexual beliefs was stronger for sexually inexperienced youth, but sexually experi- enced youth were more likely to already hold erroneous sexual beliefs. Further, precocious sexual experience was correlated with dependency on pornography for sexual learning, and path analysis indicated that the association between pornography dependency and erroneous sexual beliefs was mediated by early sexual experience. Taken together, these correlations are inconsistent with the notion that youth discard the erroneous sexual beliefs they have learned from pornography as they gain experience with sex. Rather, they suggest that adolescents who are dependent on pornography for sexual learning are more likely to precociously enact sexual scripts they have observed in pornography, which reinforces the erroneous sexual beliefs they acquired from porno- graphy in the first place and lessons the measurable impact of subsequent pornography consumption.

Limitations and future directions

Subsequent research can improve or expand on the present study in several ways. First, although the present study did test a range of sexual beliefs shown to be false through basic human sexuality research, it did not test all possible sexual beliefs. It is possible that pornography consumption does increase accurate sexual knowledge in domains that were not investigated. Additionally, although sexual beliefs are known to predict sexual behavior, it is important that subsequent studies explore whether and how adoles- cents’ erroneous sexual beliefs are linked to their sexual practices (particularly those that may be injurious to themselves or others).

Second, the present study measured dependency on pornography for sexual learning, but did not assess why some youth were more dependent than others. Was it because their parents were reluctant to communicate? Was it because their schools did not include comprehensive sex education programs that included a component on pornogra- phy? It is theoretically and practically important to know that pornography dependency is correlated with erroneous sexual beliefs. But it is also important to know why youth become dependent on pornography for sexual learning.

Third, although meta-analyses on other sexual outcomes do not suggest large cultural differences (Tokunaga et al., 2019, 2020; Wright et al., 2016), there may be differential

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sexual knowledge effects due to more substantial sex education programs in some countries. In other words, although pornographic sexual socialization effects may be similar cross-culturally when subjective sexual beliefs are examined, they may be attenu- ated for objective knowledge assessments in countries where school-based sex education programs are more comprehensive. Thus, the present study should be replicated in other countries.

Fourth, in addition to assessing whether adolescents’ first pornography exposure was sought, subsequent studies could assess the proportion of adolescents’ current pornogra- phy exposure that is intentional or unintentional and test that as a moderator. Although it seems most likely that exposure is primarily intentional as adolescents’ age, this should be tested empirically.

Finally, additional content analyses are needed to evaluate the prevalence of erroneous sexual messages across various genres of popular pornography. Extant content analyses and scholarly observations indicate that the erroneous sexual messages evaluated in the present study are common, but additional research is needed to assess their exact preva- lence and to identify whether their recurrence differs across various genres of pornogra- phy. If future content analyses do find marked prevalence differences across genres, this would help to inform the development of exposure questions in subsequent survey studies. Relatedly, subsequent survey studies should consider developing indices of exposure to pornographic categories that more clearly demarcate between genres of por- nography (e.g., amateur, BDSM) and types of sexual behaviors that could appear in mul- tiple genres (e.g., rough oral sex, facial ejaculation). The items in the pornographic categories measure employed in the present study were selected following their use in recent research, as well as pornography scholars’ identification of each with actors and activities that are uncommon among real-world persons and their sexual activities. However, a clearer demarcation of pornographic genres and pornographic behaviors could make responding easier for participants and reduce the number of items necessary to produce valid and reliable responses.6

Conclusion

This study examined U.S. adolescents’ pornography use, dependency, and belief in a variety of notions contradicted by basic sexological science. Consistent with the 3AM of sexual media socialization, adolescents who had viewed pornography were more likely to hold erroneous sexual beliefs than adolescents who had not viewed pornogra- phy. Also consistent with the 3AM, more frequent pornography consumption and higher levels of pornography dependency were independently associated with holding erroneous beliefs about sex among pornography consumers. Counter to the 3AM, however, frequency of pornography consumption did not interact with pornography dependency in the prediction of erroneous sexual beliefs. Although direct and conceptual replications are needed before this 3AM postulate is formally modified, this result suggests that frequent consumption may impact adolescents similarly irrespective of their dependence on alternative sources of information about sex.

The association between consuming pornography more frequently and erroneous sexual beliefs was mediated by exposure to specific pornographic categories, support- ing the methodological position that use frequency indices are predictive because

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recurrent pornography consumption increases the likelihood of exposure to sexual scripts that predominate the pornography landscape. Additionally, associations between pornography and erroneous sexual beliefs were unmoderated by intentional- ity of pornography exposure. This suggests that social learning from pornography takes place regardless of whether youth seek it out or happen upon it. Finally, the present study suggested that adolescents who are dependent on pornography for sexual information are more likely to precociously enact sexual scripts they have learned from pornography than adolescents who are less dependent on pornography for sexual information. This early enactment of pornographic scripts, in turn, may reinforce the erroneous sexual beliefs they initially acquired from pornography. Although effect sizes were small to moderate, they were consistent with effect sizes in the field of communication science in general (Rains et al., 2018) and similar to, or larger than, pornography effect sizes in other domains (e.g., Tokunaga et al., 2019, 2020; Wright et al., 2016, 2017). Consequently, the practical significance of mod- erate effect sizes increases when the behavioral domain under investigation (i.e., ado- lescent sexuality) is socially and personally consequential (Flay et al., 2005; McCartney & Rosenthal, 2000).

Notes

1. The question of whether pornography contributes to erroneous beliefs about sex is pertinent to the discipline of communication more broadly, given the centrality of the mass media exposure/erroneous social beliefs association to cultivation theory and research (Chia & Lee, 2008; Gerbner et al., 1994; Green, 2006).

2. This mediational approach was adopted in the present study because of the differing per- spectives presented in this subsection. But it would not be unreasonable for future work to probe whether the association between more frequent pornography consumption and erroneous beliefs about sex is moderated by more or less exposure to specific categories of pornography.

3. Previous studies have focused on the sexual satisfaction, sexual risk behavior, and sexual aggression of the sexually experienced adolescents in the dataset.

4. Although CFAs were used to determine the final constitution of the multiple-itemmeasures, it is important to note that the results for each hypothesis test and research question were parallel when conducted with the original measures (i.e., analyses with the non-trimmed, complete item indices generated the same conclusions as the analyses with the indices trimmed per the results of the CFAs).

5. Gender was not incorporated as an a priori moderator in the present study due to the goal of focusing on more specific, less global, contingency factors. Post-hoc analyses of gender as a potential moderator of the pornography/erroneous belief associations yielded null interactions.

6. For subsequent researchers’ reference, the correlations between erroneous sexual beliefs and each individual pornography category were as follows: gangbang (r = .16, p < .01), facial eja- culation (r = .24, p < .01), double-penetration (r = .24, p < .01), rough oral sex (r = .31, p < .01), amateur (r = .27, p < .01), BDSM (r = .14, p < .05), coercion (r = .13, p < .05), and simulated rape (r = .06, p = .31).

ORCID

Debby Herbenick http://orcid.org/0000-0002-0352-2248

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