Numerous studies have examined the connection between pornography viewing and marital quality, with findings most often revealing a negative association. Data limitations, however, have precluded establishing directionality with a representative sample. This study is the first to draw on nationally representative, longitudinal data (2006–2012 Portraits of American Life Study) to test whether more frequent pornography use influences marital quality later on and whether this effect is moderated by gender. In general, married persons who more frequently viewed pornography in 2006 reported significantly lower levels of marital quality in 2012, net of controls for earlier marital quality and relevant correlates. Pornography’s effect was not simply a proxy for dissatisfaction with sex life or marital decision-making in 2006. In terms of substantive influence, frequency of pornography use in 2006 was the second strongest predictor of marital quality in 2012. Interaction effects revealed, however, that the negative effect of porn use on marital quality applied to husbands, but not wives. In fact, post-estimation predicted values indicated that wives who viewed pornography more frequently reported higher marital quality than those who viewed it less frequently or not at all. The implications and limitations of this study are discussed.
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The term “pornography” is both difficult to define and freighted with moral baggage (Lindgren, 1993; Manning, 2006; Short, Black, Smith, Wetterneck, & Wells, 2012). Researchers occasionally elect to use more neutral and descriptive terms like “sexually explicit media or materials,” “erotica,” or “online sexual activity” (Carroll et al., 2008). Yet many studies and national surveys (e.g., General Social Surveys, Portraits of American Life Study, National Study of Youth and Religion, and Baylor Religion Surveys) ask questions about “pornography” attitudes and consumption, and thus I use the term pornography or porn here. For this purposes of this study, pornography will be understood as visual material (magazines, movies, and internet images) intended to sexually arouse the viewer.
Data from the 2014 General Social Survey, for example, suggest that over a third of American men and over 15 percent of women reported viewing an “X-rated movie” in the previous year. Other surveys like the 2006 Portraits of American Life Study indicate that over half of men and over a fifth of women report viewing “pornographic material” in the previous twelve months. Using methods that actually monitored internet users’ online behavior, Edelman (2009) indicates that somewhere over 35 percent of internet users visit an “adult” website at least once a month, and those who visit adult websites once a month average nearly 8 visits per month.
See the limitations acknowledged in Doran and Price (2014, p. 496), Doring (2009, p. 1093), Lambert et al. (2012, p. 419), Maddox et al. (2011, p. 447), Perry (2015, 2016a), Poulsen et al. (2013, p. 81), Stack et al. (2004, p. 86), Stewart and Szymanksi (2012, p. 267), Yucel and Gassanov (2010, p. 731, 736), and Willoughby et al. (2016, p. 157).
Stack et al. (2004), for example, found that a leading predictor of internet porn consumption is an unhappy marriage. Paul (2005) recounted how men who frequently viewed pornography often attributed their use of it to their own sexual frustrations or other relationship problems (see also Olmstead et al., 2013). And Willoughby et al. (2016) recently found significant bi-directional effects between porn use and relationship quality.
Outside of attrition, missing values were either minimal or non-existent for most variables, with the majority of missing values coming from the Wave 2 marital outcome variables (between 11 and 12 % missing values). The independent variables, by comparison, were missing between 0 and 4 %. Because imputing on the dependent variable can risk bias (Allison, 2009), imputation was only done for independent variables with missing information. The MI procedure generated 10 imputation models and then combined them into a single estimation model. The results from all regression models used the MI data. In the end, the results from the MI model estimates were nearly identical to those from regression models I initially ran using listwise deletion.
I also estimated models with these two measures separate and the results were virtually identical in both substantive and statistical significance (results are available upon request).
While I am unable to discern whether pornography use remained stable in participants’ lives between Wave 1 and Wave 2, any observed effect of earlier porn use on later marital quality net of relevant controls would suggest either that porn use at that specific time had a lasting effect on participants’ marital quality or that the trend observed at Wave 1 was indicative of a consistent pattern of porn use in participants’ lives.
Diagnostics for collinearity issues indicated that variance inflation factors (VIFs) and tolerance levels were all well within acceptable ranges. VIFs were all below 1.84 and tolerance levels were all above .55.
Supplementary analyses were run to test for whether the men at more extreme levels of porn use were to blame for the statistically significant effect of porn use on marital quality for men. Results (available upon request) indicated the greatest difference was between those who did not view pornography at all and those who did, rather than between those who viewed pornography at moderate levels and those at more extreme levels.
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This study did not receive any direct funding.
Conflict of Interest
The author declares that he has no conflict of interest.
This article does not contain any studies with human participants by the author. Secondary data were used.
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Perry, S.L. Does Viewing Pornography Reduce Marital Quality Over Time? Evidence from Longitudinal Data. Arch Sex Behav 46, 549–559 (2017). https://doi.org/10.1007/s10508-016-0770-y