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. Author manuscript; available in PMC: 2026 Mar 12.
Published in final edited form as: Arch Sex Behav. 2025 Dec 12;55(1):29–39. doi: 10.1007/s10508-025-03297-x

Adolescents’ Pornography Exposure, Sexually Dominant Behavior, and Partnered Sexual Satisfaction: Replication in a U.S. Probability Sample

Paul J Wright 1, Debby Herbenick 2, Robert S Tokunaga 3
PMCID: PMC12977981  NIHMSID: NIHMS2142000  PMID: 41388119

Abstract

The World Association for Sexual Health has identified sexual satisfaction as an integral component of sexual health. Pornography is one of the most popular categories of digital media and has been theorized as impactful to partnered sexual satisfaction. The objective of the present study is to attempt to replicate Wright, Herbenick, Paul, and Tokunaga (2021). Wright et al. (2021) (N = 91) found that adolescents with greater pornography exposure were more likely to engage in sexually dominant behavior, engagement in sexually dominant behavior was associated with lower levels of partnered sexual satisfaction, and the indirect effect of greater pornography exposure on lower sexual satisfaction through sexual dominance was significant. Data for the present replication (N = 59) were from Wave 8 of the National Survey of Sexual Health and Behavior (NSSHB), an ongoing, multi-decade, United States (U.S.) nationally representative probability study focused on understanding sexual health and behavior. As in the original study, greater pornography exposure was associated with significantly higher levels of sexually dominant behavior and higher levels of sexually dominant behavior were associated with significantly lower levels of partnered sexual satisfaction. The indirect effect of greater pornography exposure on lower partnered sexual satisfaction through sexual dominance was in the same direction as the original study and overlapped with the 95% confidence interval for the original study’s indirect effect, but was not statistically significant. In sum, findings from Wright et al. (2021) and the present study are suggestive of a mediational linkage between these variables, but larger samples and longitudinal designs are required to rigorously substantiate this hypothesis.

Keywords: pornography, sexual satisfaction, sexual health, dominance, 3AM, replication

BRIEF REPORT

Pornography continues to be one of the most popular categories of digital media (Wright, Gruszczynski, & Woodworth, 2025; Wright, Tokunaga, & Herbenick, 2023a). The purpose of the present investigation is to attempt to replicate a study of United States (U.S.) adolescents’ pornography exposure, dominant sexual behavior, and sexual satisfaction (Wright, Herbenick, Paul, & Tokunaga, 2021). In this study, Wright, Herbenick, Paul, and Tokunaga (2021) posited that adolescents with greater exposure to sexually dominant behavior in pornography (e.g., videos showing sexual practices such as aggressive fellatio, coercion, and bondage) would be more likely to themselves engage in sexually dominant behavior (i.e., to choke, spank, or call a partner names) in comparison to adolescents with lesser exposure to sexually dominant behavior in pornography.

This supposition was based on the sexual script acquisition, activation, application model (3AM: Wright, 2011, 2014, 2020), which posits that recurrent exposure to specific sexual behaviors in sexual media increases the probability that viewers will model those behaviors (a process the 3AM calls a “specific scripting” effect: Wright, Herbenick, & Tokunaga, 2023b; Wright, Paul, & Herbenick, 2021; Wright, Sun, Steffen, & Tokunaga, 2015). The 3AM is a critical synthesis and integration of multiple mass communication, information processing, and behavioral theories, as well as conceptual and empirical work not formally tied to any particular theoretical perspective (e.g., Bandura, 2001; Gerbner et al., 1994; Hetsroni, 2008; Huesmann, 1986, 1998; Malamuth, 1996; McGuire, 1969; Roskos-Ewoldsen et al., 2009; Rubin, 2002; Shrum, 2009; Ward, 2003; Wyer & Radvansky, 1999; Zajonc, 1968). While the 3AM posits a multipart sequence for socialization effects and a variety of pathways through which effects can result, its core premise is 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 (Gagnon & Simon, 1973; Laws & Schwartz, 1977; but see Wright, Tokunaga, & Herbenick, 2025). Accordingly, the sexual scripts people possess have a direct impact on their sexual beliefs and attitudes, which can ultimately 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 behavioral decision. The 3AM predicts that sexual media exposure is most likely to lead to behavioral enactment when sexual scripts are both recurrent and portrayed as normative and rewarded. A number of studies suggest that sexually dominant behaviors are depicted as common and pleasurable in popular pornography (Bridges et al., 2010; Fritz et al., 2020; Fritz & Paul, 2017; Gorman et al., 2010; Hald & Stulhofer, 2016; Klaassen & Peter, 2015; Kulibert et al., 2021; Seida & Shor, 2021; Sun et al., 2008; Vannier et al., 2014; Vera-Gray et al., 2021).

Wright, Herbenick, Paul, and Tokunaga (2021) further posited that youth who engaged in more sexually dominant behaviors would express lower levels of partnered sexual satisfaction than youth who engaged in fewer sexually dominant behaviors. This supposition was based on research suggesting that partnered sexual satisfaction is enhanced by tender, warm, and intimate behavior during sex (Campbell et al., 2024; Fisher et al., 2015; Herbenick et al., 2017; Herbenick et al., 2019).

In sum, Wright, Herbenick, Paul, and Tokunaga (2021) theorized that adolescents with greater exposure to sexually dominant behaviors in pornography would be more likely to enact sexually dominant behaviors, creating emotional distance between themselves and their partner,1 resulting in lower levels of partnered sexual satisfaction (pornography exposure → sexually dominant behavior → lower sexual satisfaction). Path analytic and indirect effect results were consistent with these hypotheses. Pornography exposure was positively associated with sexual dominance, and sexual dominance was associated with lower levels of partnered sexual satisfaction. Further, the indirect effect of pornography exposure on lower sexual satisfaction through increased sexual dominance was significant.

It is important to assess whether the findings of Wright, Herbenick, Paul, and Tokunaga (2021) replicate, for several reasons. First, the World Association for Sexual Health (WAS) has identified sexual satisfaction as an integral component of sexual health (World Association for Sexual Health, 2019; see also Coleman et al., 2021). Second, multiple scholars have suggested that sexual satisfaction is essential to sexual health across the life course, including adolescence (Hensel & Fortenberry, 2013; Sladden et al., 2021; Tolman & McClelland, 2011; Ventegodt et al., 2005). Third, very few studies have been conducted on adolescents’ pornography exposure and sexual satisfaction. The first meta-analysis inclusive of pornography and sexual satisfaction data (Wright, Tokunaga, Kraus, & Klann, 2017) located only two studies focusing on adolescents and a recent meta-analysis focusing on potential gender differences in the association (Wright & Tokunaga, 2025) did not include any studies with adolescent samples. Fourth, we are aware of no other research evaluating the possibility that the modeling of sexually dominant behavior in pornography could underlie (a portion) of the association found in prior studies between more frequent pornography exposure and lower sexual satisfaction (Grubbs et al., 2019; Wright, Tokunaga, Kraus, & Klann, 2017). Fifth, research on potential mediating mechanisms in the higher pornography exposure, lower sexual satisfaction relationship continues to be rare, regardless of the potential mediator (Leonhardt et al., 2019; Wright, Tokunaga, & Herbenick, 2023c). Sixth, recent years have seen repeated pleas for replication studies across the social and behavioral sciences, including in the areas of media effects generally and pornography effects specifically (Bowman, 2024; Keating & Totzkay, 2019; Wright, 2024a; Wright, Tokunaga, & Woodworth, 2024).

Method

Procedure

The present data are from Wave 8 of the National Survey of Sexual Health and Behavior (NSSHB), an ongoing, multi-decade, nationally representative probability study focused on understanding sexual health and behavior in the U.S. Wave 8 is the first NSSHB to include multiple items on pornography use. Research funding was provided by the Eunice Kennedy Shriver National Institute of Child Health and Development (NICHD; R01 R01HD102535). Study protocols were reviewed and approved by the institutional review board at Indiana University.

Wave 8 of the NSSHB was conducted using Ipsos KnowledgePanel®, a large online panel that uses address-based sampling methods to invite individuals and households in the U.S. into the panel; people cannot opt-in to the panel. To enhance coverage of the U.S. population, households that do not already have internet access are offered a web-enabled device to facilitate representative participation. Ipsos then uses probability methods to construct a sampling frame for a particular study. Once individuals are recruited into the study and data collection is complete, Ipsos used an iterative proportional fitting (raking) procedure to develop statistical weights for each study sample that account for any over/under-coverage or nonresponse that may have occurred during data collection (thus enhancing generalizability to the broader U.S. population). These weights were applied in the present analysis. A de-identified data set was then sent to the research team.

Ipsos KnowledgePanel® samples have been used for numerous U.S. nationally representative probability surveys on diverse topics including sexual health and behavior (Cuffe et al., 2016; Flynn et al., 2016; Townes et al., 2022). As variability in sampling procedures can confound lack of substantive replicability with differences in sampling, it is important to note that Wright, Herbenick, Paul, and Tokunaga (2021) also used a KnowledgePanel® sample.

Participants

Consistent with Wright, Herbenick, Paul, and Tokunaga (2021), participants in the present analysis were adolescents referred by their KnowledgePanel® participant parents/legal guardians. Specifically, KnowledgePanel® adults who were known by Ipsos to be a parent or legal guardian of a 14-17 year old adolescent living in their household were provided with information about the study and asked for their consent to invite their adolescent child into the study. If parents/legal guardians only had one child aged 14 to 17, that adolescent was asked to complete the survey questions; if they had more than one child in that age range, an adolescent was randomly selected for participation.

Parents/legal guardians were assured that their child’s participation was voluntary, that the research team would not be able to identify any participant, and that the NSSHB was covered by a Certificate of Confidentiality from the National Institute of Health (NIH). Parents/legal guardians were asked to give their adolescent privacy when completing the survey. Those who assented to participate could proceed to complete the survey either then or at a later time of their own choosing. In the survey itself, adolescents were provided phone and website resources related to mental health support and sexual assault.

Ultimately, a weighted sample of 1017 adolescents aged 14-17 participated in the survey. After data cleaning (e.g., elimination of cases due to inconsistent or mischievous responding), a weighted sample of 1010 remained.

As in Wright, Herbenick, Paul, and Tokunaga (2021), several criteria had to be met for adolescents to be eligible for the present study. First, they had to be in a romantic relationship to be asked about their degree of sexual satisfaction with their partner. Second, they had to be sexually experienced to be asked whether they had engaged in sexually dominant behavior. In Wright, Herbenick, Paul, and Tokunaga (2021), these criteria resulted in an analytical sample of 91 adolescents, from a base of 614. Consistent with data suggesting reductions in relational and sexual activity among youth in the U.S. over time (Centers for Disease Control and Prevention, 2023; Lindberg, Firestein, et al., 2021; Lindberg, Scott, et al., 2021), the ratio reduction was even more pronounced in the present data. From the base of 1010 adolescents, the application of the eligibility criteria led to an analytical sample of 59. Demographic information for these adolescents is presented in Table 1, following the demographic information reported by Wright, Herbenick, Paul, and Tokunaga (2021) (i.e., Wright et al. reported data on their participants’ sex assigned at birth, gender identity, age, race/ethnicity, and sexual orientation).

Table 1.

Participant demographics

Characteristic n %
Sex assigned at birth
  Male 24 40.68
  Female 35 59.32
Gender identity
  Man 23 38.98
  Woman 33 55.93
  Nonbinary 2 3.39
  Transgender man 1 1.70
Age
  14 3 5.09
  15 9 15.25
  16 11 18.64
  17 36 61.02
Race/ethnicity
  White, non-Hispanic 29 49.15
  Black, non-Hispanic 8 13.56
  Other, non-Hispanic 4 6.78
  Hispanic 14 23.73
  Multiple races/ethnicities 4 6.78
Sexual orientation
  Heterosexual/straight 51 86.44
  Gay or lesbian 0 0.00
  Bisexual 5 8.48
  Pansexual 2 3.39
  Queer 1 1.69
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Using t and 2 x 2 chi-square tests, these adolescents (i.e., those included in the present analysis) were compared to their peers who did not meet these criteria (i.e., those not included in the present analysis) for differences in sex assigned at birth (male or female), gender identity (man/women or trans/nonbinary), age, race/ethnicity (White or Person of Color), and sexual orientation identity (heterosexual or non-heterosexual). There was only one significant difference. Adolescents eligible for the present analysis were older on average (M = 16.36, SD = 0.92) than adolescents not eligible for the present analysis (M = 15.46, SD = 1.12) (t = 6.14, p < .001).

To assess demographic consistency with Wright, Herbenick, Paul, and Tokunaga (2021), we calculated 95% confidence intervals (CIs) around Wright et al.’s demographic point-estimates (i.e., proportion and mean CIs for sex assigned at birth [male or female], gender identity [man/women or trans/nonbinary], age, race/ethnicity [White or Person of Color], and sexual orientation identity [heterosexual or non-heterosexual] and then examined whether the same demographic point-estimates from the present study fell within these CIs (see Wright et al.’s Table 1 on page 224 for the demographic attributes of their participants). The present study’s demographic point-estimates fell outside of the demographic 95% CIs we calculated from Wright, Herbenick, Paul, and Tokunaga (2021) in just one instance. The mean age of participants in the present study (16.36) fell below the lower bound of the CI from Wright et al. (M = 16.97, 95% CI: 16.74, 17.20).2

In sum, adolescents eligible for the present analysis were generally demographically indistinguishable from adolescents not eligible for the present analysis as well as from the adolescents eligible for Wright, Herbenick, Paul, and Tokunaga’s (2021) analysis. The exception being that adolescents eligible for the present analysis were slightly older (+0.9 years) on average than adolescents not eligible for the present analysis and slightly younger on average (−0.61 years) than the adolescents in Wright, Herbenick, Paul, and Tokunaga (2021).

Focal Measures

Pornography exposure.

Participants who indicated they had seen pornography in the last six months were asked about their exposure to pornography showing someone being choked during sex, pornography showing someone hitting or slapping their partner during sex, and seven categories of pornography suggested by content analyses to feature dominant sexual behavior (Bridges et al., 2010; Fritz et al., 2020; Fritz & Paul, 2017; Gorman et al., 2010; Hald & Stulhofer, 2016; Klaassen & Peter, 2015; Kulibert et al., 2021; Seida & Shor, 2021; Sun et al., 2008; Vannier et al., 2014; Vera-Gray et al., 2021). The categories were: rough oral sex (i.e., a person forces or aggressively thrusts their penis in and out of another person’s mouth), double-penetration (i.e., two or more penises or objects in one person’s vagina and/or anus at the same time), gangbang (i.e., multiple different people having sex with one person after another), facial ejaculation (i.e., a person ejaculating on another person’s face), BDSM (e.g., 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. Adolescents who had never seen pornography, had not seen pornography in the last six months, or who had not seen the category in question, were coded 0. Adolescents who had seen the category in question in the last six months were coded 1. Responses were summed to form a pornography exposure index (omega = .92, alpha = .91), with higher scores indicating greater exposure (M = 1.80, SD = 2.71, skewness = 1.26).3

Sexually dominant behavior.

Three sexually dominant behaviors (Herbenick et al., 2020; Sun, Wright, & Steffen, 2017; Wright, Sun, & Steffen, 2015) that have been found in content analyses of popular pornography (Bridges et al., 2010; Fritz et al., 2020; Kulibert et al., 2021; Seida & Shor, 2021; Vera-Gray et al., 2021) were assessed, with accompanying definitions provided to participants: choking (i.e., using hands, arms, or objects to press against or squeeze a partner’s neck), hard spanking (i.e., spanked partner hard enough to leave a mark), and name calling (i.e., called partner names such as bitch, slut, whore, or fag). Adolescents who had engaged in a behavior in the past month were coded 1. Adolescents who had never engaged in a behavior or engaged in it but more than a month ago were coded 0.4 Responses were summed to form an index of sexually dominant behavior (omega = .63, alpha = .53), with higher scores indicating greater sexual dominance (M = 0.18, SD = 0.51, skewness = 3.25).5 To reduce the right skew of the sexual dominance measure, a square-root transformation was applied (Byrne, 2010; Cohen & Cohen, 1983; Newton & Rudestam, 2017; Tabachnick & Fidell, 2001).6

Sexual satisfaction.

Sexual satisfaction was assessed with the same item employed by Wright, Herbenick, Paul, and Tokunaga (2021): “Over the past 4 weeks, how satisfied have you been with your sexual relationship with your partner?” (1 = very dissatisfied, 5 = very satisfied) (M = 3.74, SD = 1.09, skewness = −1.00). Higher scores were indicative of greater sexual satisfaction. The sexual satisfaction indicator in the present study and Wright, Herbenick, Paul, and Tokunaga (2021) was adapted from established measures of sexual function (Rosen et al., 1997; Rosen et al., 2000) and has been used as a single-item measure of sexual satisfaction in other research (Heiman et al., 2011).

Results

Analytic Approach

As in Wright, Herbenick, Paul, and Tokunaga (2021), path analysis was used to evaluate the empirical fit of the data with a conceptual model wherein exposure to sexually dominant behavior in pornography increases adolescents’ likelihood of engaging in sexually dominant behavior, which in turn decreases their partnered sexual satisfaction (i.e., pornography exposure → sexually dominant behavior → sexual satisfaction). Also following Wright, Herbenick, Paul, and Tokunaga (2021), the fit of the data with the hypothesized mediation effect (i.e., pornography exposure reduces partnered sexual satisfaction through increases in sexually dominant behavior) was assessed through the calculation of the indirect effect (i.e., pornography exposure → sexually dominant behavior path coefficient * sexually dominant behavior → sexual satisfaction path coefficient).

Replication Assessment

As the Royal Netherlands Academy of Arts and Sciences (2018) aptly notes, there is not a “single, universal approach” to incontestably determining that a particular scientific finding has (or has not) been reproduced in a replication study (p. 20). An approach that aligns with the National Academies of Sciences, Engineering, and Medicine’s (2019) report on reproducibility and replicability in science, however, is the dual incorporation of statistical significance testing and confidence interval calculation.

In particular, the replication study can take into account whether (1) the statistical significance (or lack thereof) of the replication point-estimate is similar to the statistical significance (or lack thereof) of the original point-estimate (Cova et al., 2021), (2) the replication point-estimate falls within the 95% confidence interval (CI) of the original point-estimate (Braithwaite et al., 2015; Cumming & Maillardet, 2006; Gilbert et al., 2016), and (3) the original point-estimate falls within the 95% CI of the replication point-estimate (Open Science Collaboration, 2015; Verschuere et al., 2018). Following Wright (2024a, 2024b), the present investigation will deploy the following conclusions depending on whether zero, one, two, or three of the aforementioned criteria are met: no replication (0/3), semi-partial replication (1/3), partial replication (2/3), full replication (3/3).

Findings

The fit indices of the path analysis demonstrated acceptable model fit: χ2(1) = 0.92, p = .34, CFI > .99, RMSEA = .00, 90% CI [.00, .34], SRMR = .05. An illustration of the hypothesized model with the standardized path coefficients is presented in Figure 1.

Figure 1.

Figure 1.

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Path results for the hypothesize model. Estimates are standardized path coefficients. *p < .05.

The path coefficient between pornography exposure and sexually dominant behavior was positive and significant (b* = 0.26, 95% CI [0.02, 0.50], SE = 0.12, p = .04) and the path coefficient between sexually dominant behavior and sexual satisfaction was negative and significant (b* = −0.26, 95% CI [−0.50, −0.02], SE = 0.12, p = .04). The indirect effect of greater pornography exposure on lower sexual satisfaction through sexually dominant behavior, however, was not significant: b = −0.03, 95% CI [−0.06, 0.01], SE = 0.02, p = .15.

Replication.

There was a semi-partial replication for the path between pornography exposure and sexually dominant behavior. In Wright, Herbenick, Paul, and Tokunaga (2021) the results for this path were: b* = 0.53, 95% CI [0.38, 0.68], SE = 0.08, p < 0.001. Both point-estimates (i.e., present study’s and Wright et al.’s) were positive and statistically significant. But the point-estimate in the present study fell below the lower bound of Wright et al.’s CI and the point-estimate in Wright et al. fell above the upper bound of the present study’s CI.

There was a full replication for the path between sexually dominant behavior and sexual satisfaction. In Wright, Herbenick, Paul, and Tokunaga (2021) the results for this path were: b* = −0.36, 95% CI [−0.54, −0.18], SE = 0.09, p < 0.001. Both point-estimates (i.e., present study’s and Wright et al.’s) were negative and statistically significant. And each point-estimate fell within its counterpart’s CI.

There was a semi-partial replication for the indirect effect. The indirect effect results in Wright, Herbenick, Paul, and Tokunaga (2021) were: b = −0.07, 95% CI [−0.03, −0.11], SE = 0.02, p = 0.002. The present study’s indirect effect point-estimate was not statistically significant but overlapped with the lower bound of Wright et al.’s CI. Wright et al.’s indirect effect point-estimate fell above the upper bound of the present study’s CI.

Discussion

From adolescence through the various stages of adulthood, sexual satisfaction is an integral component of sexual health (Hensel & Fortenberry, 2013; Sladden et al., 2021; Tolman & McClelland, 2011; Ventegodt et al., 2005). Pornography use has been theorized as impactful to partnered sexual health for decades (Kenrick et al., 1989; Zillmann & Bryant, 1988) and multiple meta-analyses have investigated whether observational and experimental data are consistent with this hypothesis (Wright & Tokunaga, 2025; Wright, Tokunaga, Kraus, & Klann, 2017).

Few studies have investigated this association among adolescents, however, and only one study (Wright, Herbenick, Paul, and Tokunaga, 2021) has (to our knowledge) probed the potentiality that modeling sexually dominant behaviors they have seen in pornography (Wright, 2011, 2014, 2020) reduces adolescents’ emotional connectedness to and sense of sexual satisfaction with their partners (Campbell et al., 2024; Fisher et al., 2015; Herbenick et al., 2017; Herbenick et al., 2019). Given calls for increased replication studies across the social and behavioral sciences in general and in the area of media and pornography effects in particular (Bowman, 2024; Keating & Totzkay, 2019; Wright, 2024a; Wright, Tokunaga, & Woodworth, 2024), as well as the novelty and theoretical importance of the original study, the present brief report attempted to replicate the findings of Wright, Herbenick, Paul, and Tokunaga (2021).

In order to assess replication, the results of Wright, Herbenick, Paul, and Tokunaga (2021) and the results of the present study were compared with respect to statistical significance similarity and confidence interval overlap (Cumming & Maillardet, 2006; Gilbert et al., 2016; National Academies of Sciences, Engineering, and Medicine, 2019; Open Science Collaboration, 2015). Wright’s (2024a, 2024b) four-tiered replication assessment scheme (no replication, semi-partial replication, partial replication, full replication) was employed to add specificity to these assessments.

As in Wright, Herbenick, Paul and Tokunaga (2021), a path model positing that exposure to sexually dominant behavior in pornography increases adolescents’ likelihood of engaging in sexually dominant behavior, which in turn decreases their partnered sexual satisfaction, exhibited acceptable fit to the data (i.e., pornography exposure → sexually dominant behavior → sexual satisfaction). Further, as in Wright, Herbenick, Paul and Tokunaga (2021), the positive path coefficient between pornography exposure and sexually dominant behavior was statistically significant and the negative path coefficient between sexually dominant behavior and sexual satisfaction was statistically significant.

Wright’s (2024a, 2024b) criteria for full replication were only met in the case of the sexually dominant behavior → sexual satisfaction path, however (i.e., both coefficients were statistically significant and fell within their counterpart’s 95% CI). The significant coefficient for the pornography exposure → sexually dominant behavior path in the present study was smaller than the lower bound of the 95% CI for this significant path in Wright, Herbenick, Paul and Tokunaga (2021) and the parallel path coefficient in Wright et al. was larger than the lower bound of the 95% CI in the present study (i.e., a semi-partial replication). Additionally, the indirect effect coefficient in the present study for the hypothesis that greater pornography exposure results in lower partnered sexual satisfaction through increased sexually dominant behavior overlapped with the 95% indirect effect CI in Wright et al. but was not statistically significant (whereas in Wright et al. it was). Further, the indirect effect point-estimate in Wright et al. fell above the upper bound of the present study’s CI (i.e., a semi-partial replication).

These results echo an elementary but important point made by many a thoughtful scholar: determining whether the results of an original study have or have not been replicated in a subsequent study is a more challenging task than at first it may appear (Anderson & Maxwell, 2016; Baumeister et al., 2023; Boster, 2002; Brandt et al., 2014; Cumming & Maillardet, 2006; Gilbert et al., 2016; Royal Netherlands Academy of Arts and Sciences, 2018).

The most obvious complicating factor in the case of the present study is low statistical power. The multiple needs and goals of an extensive survey such as the NSSHB, coupled with the unique attributes required of adolescents for a replication of Wright, Herbenick, Paul and Tokunaga (2021) (i.e., sexually experienced and in a romantic relationship), makes an assured a priori sample size selection challenging.

As described in the Method section, Wright, Herbenick, Paul, and Tokunaga (2021) started from a base of 614 adolescents, 91 of whom (14.82%) were eligible for their analysis. The present study started from a base of 1010 adolescents, only 59 of whom (5.84%) were eligible for analysis. Had 14.82% of the adolescents in the present study been eligible for analysis, the sample size would have been 150 rather than 59. Yet with the same pattern of covariances and just twice the sample size (a still diminutive N of 118), the present study’s indirect effect would have been statistically significant (b = −0.03, 95% CI [−0.05, −0.001], SE = .01, p = .04.

Two notes on confidence intervals (CIs) are also important. First, while it is sound replicative practice to examine whether the point-estimate from the replication study falls within the 95% CI of the original study (Braithwaite et al., 2015; Gilbert et al., 2016; Wright, 2023), this evaluative tactic will result in false negatives more often than at first it might seem. Cumming and Maillardet (2006) make this point using the basic example of attempting to replicate a mean value from an original study: “Most 95% CIs will capture around 90% or more of replication means, but some will capture a much lower proportion. On average, a 95% CI will include just 83.4% of future replication means” (p. 217).

Second, both 95% and 99% CIs are frequently reported across the social and behavioral sciences and conclusions can vary depending on which CI analysts employ. For instance, had this investigation utilized 99% CIs, the present study’s indirect effect (b = −0.03) would have fallen well-within the CI (99% CI: −0.07, 0.02) for the indirect effect in Wright, Herbenick, Paul and Tokunaga (2021), rather than overlapping with the 95% CI lower bound.

Thus, it appears most objective to conclude the following. First, the results of the present study represented a range of replication outcomes (see Wright, 2024a, 2024b) in relation to Wright, Herbenick, Paul and Tokunaga (2021), depending on which Wright et al. finding an analyst is interested in. Second, whether the central hypothesis of Wright et al. (i.e., that greater pornography exposure results in lower partnered sexual satisfaction through increased sexually dominant behavior) received more or less support depends on an analyst’s views on probability values and statistical power and preference for 95% or 99% CIs.

Finally, it also appears reasonable to call for future research efforts using (a) longitudinal survey designs (with at least three waves to facilitate temporal sequencing for the pornography exposure → sexually dominant behavior → sexual satisfaction relationships)7 with (b) significantly larger samples. As such investigations will be quite expensive due to the base of adolescents required to yield a large analytical sample (for assistance with power calculations, see Qin, 2024; Schoemann et al., 2017; Sim et al., 2022), we encourage funding agencies to be generous in their allotments when presented with such proposals.

Strengths and Limitations

Our study had several strengths. First, we used data from a U.S. nationally representative probability survey, thus supporting generalizability to the broader population. Second, Wave 8 of the NSSHB was available in both English and Spanish languages. Third, we collected data online, which has been shown to facilitate the reporting of sensitive behaviors, including sexual behaviors (Burkill et al., 2016), and asked parents/legal guardians to give their adolescent privacy while completing the survey.

Our study also had several limitations. First, we used a single-item assessment of sexual satisfaction. While multi-item measures of sexual satisfaction may be more robust, single-item measures of sexual satisfaction have been found to be positively correlated with established scales of sexual satisfaction (Mark et al., 2014). Indeed, single item measures of sexual satisfaction are commonly used in large-scale studies (Heiman et al., 2011; Mitchell et al., 2012), including population studies, given that researchers need to balance their selection of items with issues of survey length and participant burden.

Another limitation is that parents/legal guardians had to provide consent in order for their adolescent to be invited into the survey. As such, it is possible that the adolescents who participated were different in some way than adolescents who did not have the opportunity to participate in the study and that such differences could limit the generalizability to the broader population of U.S. adolescents. Yet, the alternatives each have their own challenges and likely far more difficulties with generalizability—for example, social media recruitment would only include adolescents who are already on social media and data collection through social media is often rife with imposters; opt-in panels only include those who are already internet-connected and have their own challenges with self-selection bias, lack of generalizability, and professional survey takers; and school-based data collections (especially in more conservative states or districts) are less likely to allow the inclusion of questions related to pornography use and other sexual behaviors. Thus, on the balance, it is suggested that the present study provides important data that can inform scientific understanding of the influences on adolescent sexual development.

Data Availability

Available upon request within funder’s guidelines

Funding

Wave 8 of the National Survey of Sexual Health and Behavior was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under the Award Number R01HD102535. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Conflicts of Interest

None

Ethical Approval

The institutional review board at Indiana University reviewed and approved study protocols and measures.

Informed Consent

Informed consent was obtained from all participants.

1.

From Wright, Herbenick, Paul, and Tokunaga (2021, p. 226): “Although these behavior [i.e., sexually dominating behavior] do not necessarily result in emotional distancing, especially among sexually experienced adults with strong sexual self-concepts and communication skills, we hypothesize that this is the most likely outcome among adolescents.”

2.

See Wright (2024b) for an illustration of how not taking demographic consistency into account can obscure replicability even when the same measures and sampling approach are employed.

3.

This measure improved on Wright, Herbenick, Paul, and Tokunaga (2021) in two ways. First, it measured exposure to specific dominant behavior in pornography assessed in the theorized mediator (i.e., exposure to choking and hitting). Second, to reduce the likelihood of recall error, it assessed recent (i.e., last six months) exposure to the various pornography categories (rather than lifetime exposure) (Grotpeter, 2008). This approach follows from Peter and Valkenburg’s seminal and frequently emulated approach to measuring pornography exposure among adolescents and young adults (Peter & Valkenburg, 2006a, 2006b, 2007, 2008, 2009, 2011; see also Maes et al., 2024; van Oosten et al., 2017; Wright & Herbenick, 2022; Wright, Tokunaga, & Tokunaga, 2023).

4.

Wright, Herbenick, Paul, and Tokunaga (2021) assessed whether adolescents had ever engaged in each sexually dominant behavior. The present measurement approach is an improvement over Wright, Herbenick, Paul, and Tokunaga (2021) for two reasons. First, assessing recent (past month) rather than distal sexually dominant behavior should reduce the probability of recall error (Grotpeter, 2008). Second, measuring sexually dominant behavior in the past month and pornography exposure in the past six months reduces the likelihood of selective-exposure as a credible alternative explanation for the temporal sequencing of the association between pornography exposure and sexually dominant behavior (see also Wright, 2021).

5.

The alpha reliability coefficient (0.58) for the sexual dominance measure in Wright, Herbenick, Paul, and Tokunaga (2021) was also below suggested “rules-of-thumb” (Iacobucci & Duhachek, 2003). Wright, Herbenick, Paul, and Tokunaga (2021) did not report an omega reliability coefficient.

6.

Zero-order correlations between the nontransformed sexually dominant behavior measure and the pornography exposure and sexual satisfaction measures were r = .235, p = .037 and r = −.214, p = .052, respectively. Zero-order correlations between the transformed sexually dominant behavior measure and the pornography exposure and sexual satisfaction measures were r = .257, p = .025 and r = −.257, p = .025, respectively.

7.

For a review of longitudinal studies indicating empirical support for the hypothesis that pornography exposure at an earlier timepoint predicts theoretically expected outcomes at a later time point, see Wright (2021).

Contributor Information

Paul J. Wright, University of Arizona; The Media School at Indiana University, Bloomington..

Debby Herbenick, Indiana University; The Center for Sexual Health Promotion in The School of Public Health at Indiana University, Bloomington..

Robert S. Tokunaga, University of Arizona; The Department of Communication at University of Texas..

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