Abstract
Despite increasing interest in the implications of adolescents’ use of sexually explicit Internet material (SEIM), we still know little about the relationship between SEIM use and adolescents’ casual sexual activities. Based on a three-wave online panel survey study among Dutch adolescents (N = 1079; 53.1% boys; 93.5% with an exclusively heterosexual orientation; Mage = 15.11; SD = 1.39), we found that watching SEIM predicted engagement in casual sex over time. In turn, casual sexual activities partially predicted adolescents’ use of SEIM. A two-step mediation model was tested to explain the relationship between watching SEIM and casual sex. It was partially confirmed. First, watching SEIM predicted adolescents’ perceptions of SEIM as a relevant information source from Wave 2 to Wave 3, but not from Wave 1 to Wave 2. Next, such perceived utility of SEIM was positively related to stronger instrumental attitudes toward sex and thus their views about sex as a core instrument for sexual gratification. Lastly, adolescents’ instrumental attitudes toward sex predicted adolescents’ engagement in casual sex activities consistently across waves. Partial support emerged for a reciprocal relationship between watching SEIM and perceived utility. We did not find a reverse relationship between casual sex activities and instrumental attitudes toward sex. No significant gender differences emerged.
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Notes
The data of this three-wave panel study have also been used in six other papers of the authors to study the antecedents of SEIM use and relationships of SEIM use with other sexual outcomes. These papers can be acquired by sending an e-mail to the corresponding author.
An additional MANOVA analysis (N = 1,467), using Pillai’s trace, was performed to document the differences between the respondents who answered “I don’t know” on at least one of the questions regarding the perceived utility of SEIM at Wave 1 and also participated in Waves 2 and 3 (N = 388) and those respondents who answered all the questions at Wave 1 and also participated in Waves 2 and 3 (N = 1079, the analytical sample of the study). The analysis included age, gender, heterosexual orientation, watching SEIM, instrumental attitudes toward sexual activities, and experience with casual sexual activities, V = .12, F(6, 1460) = 32.72, p < .001, ηp² = .12. Significant differences were found for all variables except heterosexual orientation, p = .99. Descriptive statistics showed that respondents with missing data on one of the perceived utility questions were younger, more likely to be girls, and scored lower on watching SEIM, instrumental attitudes toward sex and casual sex activities, all p < .001. These findings are in line with prior literature reporting on the characteristics of adolescents who consume SEIM (e.g., Peter & Valkenburg, 2006).
The structural equation models reported in Figs. 2 and 3 were also tested with a sample that included the participants with missing data (N = 2,137). Automatic imputation was conducted to replace missing values in SPSS (version 23). A pooled dataset of the mean estimates of the missing data was calculated from the five imputed datasets (i.e., multiple imputation, Acock, 2007).
The results for the model that tested the reciprocal relationships between watching SEIM and casual sex were similar to the results reported in the manuscript for the sample that excluded participants with missing values (N = 1079, Fig. 2). The model, χ²(202) = 2524.88, p < .001, CFI = .95, RMSEA = .07 (90% CI: .071/.076), χ²/df = 12.50, showed that all paths were similar to the model reported in Fig. 2.
The results for the model that tested the two-step mediation model showed a good fit, χ²(833) = 4313.35, p < .001, CFI = .95, RMSEA = .04 (90% CI: .043/.046), χ²/df = 5.18. The results for the paths were similar to the results reported in Fig. 3, except for three paths. Exposure to SEIM at Wave 1 positively predicted perceived utility of SEIM at Wave 2, β = .07, B = .07, SE = 0.26, p < .01 (bc 95% bt CI: .021/.130). This relationship was not significant in the model shown in Fig. 3. The path from instrumental attitudes toward sex at Wave 1 marginally significantly predicted casual sex at Wave 2 according to the bootstrapped confidence intervals, β = .05, B = .01, SE = 0.00, p < .05 (bc 95% bt CI: − .001/.013). This path was significant in the model in Fig. 3. In addition, the paths from engagement into casual sex at Wave 1/Wave 2 to instrumental attitudes toward sex at Wave 2/Wave 3 were significant, respectively, β = .09, B = .67, SE = 0.17, p < .001 (bc 95% bt CI: .268/1.105), β = .07, B = .46, SE = 0.15, p < .005 (bc 95% bt CI: .136/.815). Theses paths were not significant in the model in Fig. 3. This shows that systematic drop-out due to unfamiliarity with SEIM (see footnote 2) may influence the results. Because imputation methods have been debated (Allison, 2003), we chose to report the results without imputation in the results section.
Because our three-wave design did not allow to model the relationship between perceived utility of SEIM and instrumental attitudes toward sex over time, a separate model was tested. In line with cognitive dissonance theory (Festinger, 1957) and RSM (Slater, 2007, 2014), a new model with the cross-lagged relationships between perceived utility of SEIM and instrumental attitudes toward sex was tested. Age, gender, and heterosexual orientation were added as control variables. The fit was good, χ²(202) = 412.70, p < .001, CFI = .99, RMSEA = .03 (90% CI: .027/.035), χ²/df = 2.04, and all expected longitudinal paths between perceived utility of SEIM and instrumental attitudes toward sex were significant according to normal test theory and bootstrapped CFI’s, p < .05. One exception was that perceived utility of SEIM at Wave 1 significantly predicted instrumental attitudes at Wave 2 according to results of normal test theory, β = .09, B = .07, SE = 0.32, p < .05, but marginally significant according to bootstrapping analysis, bc 95% bt CI: − .004/.137. The model thus supported that perceived utility of SEIM is a predictor of instrumental attitudes toward sex, but also that instrumental attitudes toward sex predict the perceived utility of SEIM over time.
See footnote 4
Prior literature has suggested that the influence of sexual media content may differ according to age (Ward, 2003). Therefore, we conducted two additional model constrain tests to examine whether the models reported in Figs. 2 and 3 differed between adolescents aged 13 to 15 years (n = 613) and adolescents aged 16 to 17 years (n = 466). These models controlled for heterosexual orientation and gender. The results showed the relationships were not significantly different for the models shown in Fig. 2, CMIN (4) = 7.47, p = . 113, and Fig. 3, CMIN (11) = 10.61, p = .467. Age did not moderate the results.
References
Acock, A. C. (2007). Working with missing values. Journal of Marriage and Family, 67, 1012–1028.
Allen, M., Emmers-Sommer, T. M., D’Alessio, D., Timmerman, L., Hanzal, A., & Korus, J. (2007). The connection between the physiological and psychological reactions to sexually explicit materials: A literature summary using meta-analysis. Communication Monographs, 74, 541–560. https://doi.org/10.1080/03637750701578648.
Allison, P. D. (2003). Missing data techniques for structural equation modeling. Journal of Abnormal Psychology, 112, 545–557. https://doi.org/10.1037/0021-843X.112.4.545.
Allison, R., & Risman, B. J. (2013). A double standard for “hooking up”: How far have we come toward gender equality? Social Science Research, 42, 1191–1206. https://doi.org/10.1016/j.ssresearch.2013.04.006.
Angrist, J. D., & Pischke, J. S. (2008). Mostly harmless econometrics: An empiricist’s companion. Woodstock, NJ: Princeton University Press.
Angrist, J. D., & Pischke, J. S. (2015). The path from cause to effect: Mastering’ metrics. Woodstock, NJ: Princeton University Press.
Bandura, A. (2001). Social cognitive theory of mass communication. Media Psychology, 3, 265–299. https://doi.org/10.1207/S1532785XMEP0303_03.
Bem, D. J. (1967). Self-perception: An alternative interpretation of cognitive dissonance phenomena. Psychological Review, 74, 183–200. https://doi.org/10.1037/h0024835.
Bem, S. L. (1981). Gender schema theory: A cognitive account of sex typing. Psychological Review, 88, 354–364. https://doi.org/10.1037/0033-295X.88.4.354.
Beyens, I., Vandenbosch, L., & Eggermont, S. (2015). Early adolescent boys’ exposure to Internet pornography: Relationships to pubertal timing, sensation seeking, and academic performance. Journal of Early Adolescence, 35, 1045–1068. https://doi.org/10.1177/0272431614548069.
Bleakley, A., Hennessy, M., Fishbein, M., & Jordan, A. (2008). It works both ways: The relationship between exposure to sexual content in the media and adolescent sexual behavior. Media Psychology, 11, 443–446. https://doi.org/10.1080/15213260802491986.
Brosius, H. B., Weaver, J. B., & Staab, J. F. (1993). Exploring the social and sexual “reality” of contemporary pornography. Journal of Sex Research, 30, 161–170. https://doi.org/10.1080/00224499309551697.
Brown, J., & L’Engle, K. (2009). X-rated: Sexual attitudes and behaviors associated with U.S. early adolescents’ exposure to sexually explicit media. Communication Research, 36, 129–151. https://doi.org/10.1177/0093650208326465.
Byrne, D. (1976). Social psychology and the study of sexual behavior. Personality and Social Psychology Bulletin, 3, 3–30.
Byrne, B. M. (2001). Multivariate applications series. Structural equation modeling with AMOS: Basic concepts, applications, and programming. New York: Routledge/Taylor & Francis Group.
CBS. (2014). Sociaaleconomische status: Wat is de huidige situatie? [Socio-economic status: What is the current situation?]. Retrieved from http://www.nationaalkompas.nl/bevolking/sociaaleconomischestatus/wat-is-sociaaleconomische-status/.
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9, 233–255. https://doi.org/10.1207/S15328007SEM0902.
Chock, T. M. (2011). Is it seeing or believing? Exposure, perceived realism, and emerging adults’ perceptions of their own and others’ attitudes about relationships. Media Psychology, 14, 355–386. https://doi.org/10.1080/15213269.2011.620537.
Collins, W. A. (2003). More than myth: The developmental significance of romantic relationships during adolescence. Journal of Research on Adolescence, 13, 1–24. https://doi.org/10.1111/1532-7795.1301001.
Collins, R. L., Elliot, M. N., Berry, S. H., Kanouse, D. E., Kunkel, D., Hunter, S. B., & Miu, A. (2004). Watching sex on television predicts adolescent initiation of sexual behavior. Pediatrics, 114, 280–289. https://doi.org/10.1542/peds.2003-1065-L.
Davis, K. C., Norris, J., George, W. H., Martell, J., & Heima, J. R. (2006). Rape-myth congruent beliefs in women resulting from exposure to violent pornography effects of alcohol and sexual arousal. Journal of Interpersonal Violence, 21, 1208–1225. https://doi.org/10.1177/0886260506290428.
Festinger, L. (1957). Theory of cognitive dissonance. Stanford, CA: Stanford University Press.
Fortunato, L., Young, A. M., Boyd, C. J., & Fons, C. E. (2010). Hook-up sexual experiences and problem behaviors among adolescents. Journal of Child & Adolescent Substance Abuse, 19, 261–278. https://doi.org/10.1080/1067828X.2010.488965.
Frison, E., Vandenbosch, L., Trekels, J., & Eggermont, S. (2015). Reciprocal relationships between music television exposure and adolescents’ sexual behaviors: The role of perceived peer norms. Sex Roles, 72, 183–197. https://doi.org/10.1007/s11199-015-0454-4.
Garcia, J. R., & Reiber, C. (2008). Hook-up behavior: A biopsychosocial perspective. Journal of Social, Evolutionary, and Cultural Psychology, 2, 192–208. https://doi.org/10.1037/h0099345.
Gorman, S., Monk-Turner, E., & Fish, J. N. (2010). Free adult Internet web sites: How prevalent are degrading acts? Gender Issues, 27, 131–145. https://doi.org/10.1007/s12147-010-9095-7.
Green, M. C. (2006). Narratives and cancer communication. Journal of Communication, 56, S163–S183. https://doi.org/10.1111/j.1460-2466.2006.00288.x.
Green, M. C., & Brock, T. C. (2000). The role of transportation in the persuasiveness of public narratives. Journal of Personality and Social Psychology, 79, 701–721. https://doi.org/10.1037//0022-3514.79.5.701.
Green, M. C., & Brock, T. C. (2002). In the mind’s eye: Transportation-imagery model of narrative persuasion. In M. C. Green, J. J. Strange, & T. C. Brock (Eds.), Narrative impact: Social and cognitive foundations (pp. 315–341). Mahwah, NJ: Lawrence Erlbaum.
Green, M. C., Brock, T. C., & Kaufman, G. F. (2004). Understanding media enjoyment: The role of transportation into narrative worlds. Communication Theory, 14, 311–327. https://doi.org/10.1111/j.1468-2885.2004.tb00317.x.
Guttman, L. (1945). A basis for analyzing test-retest reliability. Psychometrika, 10, 255–282. https://doi.org/10.1007/BF02288892.
Hald, G. M., Malamuth, N. N., & Lange, T. (2013). Pornography and sexist attitudes among heterosexuals. Journal of Communication, 63, 638–660. https://doi.org/10.1111/jcom.12037.
Heldman, C., & Wade, L. (2010). Hook-up culture: Setting a new research agenda. Sexuality Research and Social Policy, 7, 323–333. https://doi.org/10.1007/s13178-010-0024-z.
Hendrick, S., & Hendrick, C. (1987). Multidimensionality of sexual attitudes. Journal of Sex Research, 23, 502–526. https://doi.org/10.1080/00224498709551387.
Kinsey, A. C., Pomeroy, W. B., & Martin, C. E. (1948). Sexual behavior in the human male. Philadelphia: Saunder.
Klaassen, M. J. E., & Peter, J. (2015). Gender (in)equality in Internet pornography: A content analysis of popular pornographic Internet videos. Journal of Sex Research, 52, 721–735. https://doi.org/10.1080/00224499.2014.976781.
Kline, R. B. (2010). Principles and practices of structural equation modeling (3rd ed.). New York: Guilford Press.
Little, T. D., Card, N. A., Preacher, K. J., & McConnell, E. (2009). Modeling longitudinal data from research on adolescence. In R. M. Lerner & L. Steinberg (Eds.), Handbook of adolescent psychology (3rd ed., pp. 15–54). New York, NY: Wiley.
Lo, V., Neilan, E., Sun, M., & Chiang, S. (1999). Exposure of Taiwanese adolescents to pornographic media and its impact on sexual attitudes and behaviour. Asian Journal of Communication, 9, 50–71. https://doi.org/10.1080/01292989909359614.
Lo, V., & Wei, R. (2005). Exposure to internet pornography and Taiwanese adolescents’ sexual attitudes and behavior. Journal of Broadcasting & Electronic Media, 49, 221–237. https://doi.org/10.1207/s15506878jobem4902_5.
Lonsway, K. A., & Fitzgerald, L. F. (1994). Rape myths in review. Psychology of Women Quarterly, 18, 133–164. https://doi.org/10.1111/j.1471-6402.1994.tb00448.x.
Manning, W. D., Giordano, P. C., & Longmore, M. A. (2006). Hooking up the relationship contexts of “nonrelationship” sex. Journal of Adolescent Research, 21, 459–483. https://doi.org/10.1177/0743558406291692.
Mattebo, M., Tydén, T., Häggström-Nordin, E., Nilsson, K. W., & Larsson, M. (2014). Pornography and sexual experiences among high school students in Sweden. Journal of Developmental and Behavioral Pediatrics, 35, 179–188. https://doi.org/10.1097/DBP.0000000000000034.
Miller, B. C., & Moore, K. A. (1990). Adolescent sexual behavior, pregnancy, and parenting: Research through the 1980s. Journal of Marriage and Family, 52, 1025–1044.
Omori, K., Zhang, Y. B., Allen, M., Ota, H., & Imamura, M. (2011). Japanese college students’ media exposure to sexually explicit materials, perceptions of women, and sexually permissive attitudes. Journal of Intercultural Communication Research, 40, 93–110. https://doi.org/10.1080/17475759.2011.581031.
Peter, J., & Valkenburg, P. M. (2006). Adolescents’ exposure to sexually explicit online material and recreational attitudes toward sex. Journal of Communication, 56, 639–660. https://doi.org/10.1111/j.1460-2466.2006.00313.x.
Peter, J., & Valkenburg, P. M. (2008). Adolescents’ exposure to sexually explicit internet material, sexual uncertainty, and attitudes toward uncommitted sexual exploration: Is there a link? Communication Research, 35, 569–601. https://doi.org/10.1177/0093650208321754.
Peter, J., & Valkenburg, P. M. (2009a). Adolescents’ exposure to sexually explicit internet material and notions of women as sex objects. Journal of Communication, 59, 407–433. https://doi.org/10.1111/j.1460-2466.2009.01422.x.
Peter, J., & Valkenburg, P. M. (2009b). Adolescents’ exposure to sexually explicit internet material and sexual satisfaction: A longitudinal study. Human Communication Research, 35, 171–194. https://doi.org/10.1111/j.1468-2958.2009.01343.x.
Peter, J., & Valkenburg, P. M. (2010). Adolescents’ use of sexually explicit internet material and sexual uncertainty: The role of involvement and gender. Communication Monographs, 77, 357–375. https://doi.org/10.1080/03637751.2010.498791.
Peter, J., & Valkenburg, P. M. (2011). The use of sexually explicit internet material and its antecedents: A longitudinal comparison of adolescents and adults. Archives of Sexual Behavior, 40, 1015–1025. https://doi.org/10.1007/s10508-010-9644-x.
Peter, J., & Valkenburg, P. M. (2016). Adolescents and pornography: A review of 20 years of research. Journal of Sex Research, 53, 509–531. https://doi.org/10.1080/00224499.2016.114344.
Petersen, J. L., & Hyde, J. S. (2011). Gender differences in sexual attitudes and behaviors: A review of meta-analytic results and large datasets. Journal of Sex Research, 48, 149–165. https://doi.org/10.1080/00224499.2011.551851.
Rigdon, E. E., Schumacker, R. E., & Wothke, W. (1998). A comparative review of interaction and nonlinear modeling. In R. E. Schumacker & G. A. Marcoulides (Eds.), Interaction and nonlinear effects in structural equation modeling (pp. 1–16). Mahwah, NJ: Erlbaum.
Schalet, A. T. (2000). Raging hormones, regulated love: Adolescent sexuality and the constitution of the modern individual in the United States and the Netherlands. Body Society, 6, 75–105. https://doi.org/10.1177/1357034X00006001006.
Ševčíková, A., & Daneback, K. (2014). Online pornography use in adolescence: Age and gender differences. European Journal of Developmental Psychology, 11, 674–686. https://doi.org/10.1080/17405629.2014.926808.
Shafer, A., Bobkowski, P., & Brown, J. D. (2013). Sexual media practice: How adolescents select, engage with, and are affected by sexual media. In K. E. Dill (Ed.), The Oxford handbook of media psychology (pp. 223–251). New York: Oxford University Press.
Slater, M. D. (2007). Reinforcing spirals: The mutual influence of media selectivity and media effects and their impact on individual behavior and social identity. Communication Theory, 17, 281–303. https://doi.org/10.1111/j.1468-2885.2007.00296.x.
Slater, M. D. (2015). Reinforcing spirals model: Conceptualizing the relationship between media content exposure and the development and maintenance of attitudes. Media Psychology, 18, 370–395. https://doi.org/10.1080/15213269.2014.897236.
Slater, M. D., & Rouner, D. (2002). Entertainment—education and elaboration likelihood: Understanding the processing of narrative persuasion. Communication Theory, 12, 173–191. https://doi.org/10.1111/j.1468-2885.2002.tb00265.x.
Steele, J. R., & Brown, J. D. (1995). Adolescent room culture: Studying media in the context of everyday life. Journal of Youth and Adolescence, 24, 551–576. https://doi.org/10.1007/BF01537056.
Stinson, R. D. (2010). Hooking up in young adulthood: A review of factors influencing the sexual behavior of college students. Journal of College Student Psychotherapy, 24, 98–115. https://doi.org/10.1080/87568220903558596.
Štulhofer, A., Buško, V., & Schmidt, G. (2012). Adolescent exposure to pornography and relationship intimacy in young adulthood. Psychology & Sexuality, 3, 95–107. https://doi.org/10.1080/19419899.2010.537367.
Tang, W., & Cui, Y. (2012). A simulation study for comparing three lower bounds to reliability. Paper presented at the annual meeting of the American Educational Research Association, Vancouver, Canada.
Ter Bogt, T. F., Engels, R. C., Bogers, S., & Kloosterman, M. (2010). “Shake it baby, shake it”: Media preferences, sexual attitudes and gender stereotypes among adolescents. Sex Roles, 63, 844–859. https://doi.org/10.1007/s11199-010-9815-1.
To, S. M., Ngai, S. S. Y., & Iu Kan, S. M. (2012). Direct and mediating effects of accessing sexually explicit online materials on Hong Kong adolescents’ attitude, knowledge, and behavior relating to sex. Children and Youth Services Review, 34, 2156–2163. https://doi.org/10.1016/j.childyouth.2012.07.019.
Tolman, D. L., & McClelland, S. I. (2011). Normative sexuality development in adolescence: A decade in review, 2000–2009. Journal of Research on Adolescence, 21, 242–255. https://doi.org/10.1111/j.1532-7795.2010.00726.x.
Tolman, D. L., Striepe, M. I., & Harmon, T. (2003). Gender matters: Constructing a model of adolescent sexual health. Journal of Sex Research, 40, 4–12. https://doi.org/10.1080/00224490309552162.
Traeen, B., Stigum, H., & Sorensen, D. (2002). Sexual diversity in urban Norwegians. Journal of Sex Research, 39, 249–258. https://doi.org/10.1080/00224490209552148.
Valkenburg, P. M., & Peter, J. (2013a). The differential susceptibility to media effects model. Journal of Communication, 63, 221–243. https://doi.org/10.1111/jcom.12024.
Valkenburg, P. M., & Peter, J. (2013b). Five challenges for the future of media-effects research. International Journal of Communication, 7, 197–215.
Van Doorn, N. (2010). Keeping it real user-generated pornography, gender reification, and visual pleasure. Convergence: The International Journal of Research into New Media Technologies, 16, 411–430. https://doi.org/10.1177/1354856510375144.
van Oosten, J. M. F. (2016). Sexually explicit Internet material and adolescents’ sexual uncertainty: The role of disposition-content congruency. Archives of Sexual Behavior, 45, 1011–1022. https://doi.org/10.1007/s10508-015-0594-1.
van Oosten, J. M. F., Peter, J., & Boot, I. (2015). Women’s critical responses to sexually explicit material: The role of hyperfemininity and processing style. Journal of Sex Research, 52, 306–316. https://doi.org/10.1080/00224499.2013.858305.
Vandenbosch, L. (2015). Antecedents of adolescents’ exposure to different types of sexually explicit Internet material: A longitudinal study. Computers in Human Behavior, 50, 439–448. https://doi.org/10.1016/j.chb.2015.04.032.
Vandenbosch, L., & Eggermont, S. (2013). Sexually explicit websites and sexual initiation: Reciprocal relationships and the moderating role of pubertal status. Journal of Research on Adolescence, 23, 621–634. https://doi.org/10.1111/jora.12008.
Vandenbosch, L., van Oosten, J. M. F., & Peter, J. (2018). Sexually explicit Internet material and adolescents’ sexual performance orientation: The mediating roles of enjoyment and perceived utility. Media Psychology, 21, 50–74. https://doi.org/10.1080/15213269.2017.1361842.
Ward, L. M. (2003). Understanding the role of entertainment media in the sexual socialization of American youth: A review of empirical research. Developmental Review, 23, 347–388. https://doi.org/10.1016/S0273-2297(03)00013-3.
Ward, L. M., Epstein, M., Caruthers, A., & Merriwether, A. (2011). Men’s media use, sexual cognitions, and sexual risk behavior: Testing a mediational model. Developmental Psychology, 47, 592–602. https://doi.org/10.1037/a0022669.
Weinberg, M. S., Lottes, I. L., & Gordon, L. E. (1997). Social class background, sexual attitudes, and sexual behavior in heterosexual undergraduate sample. Archives of Sexual Behavior, 26, 625–642.
Wright, P. J. (2011). Mass media effects on youth sexual behavior: Assessing the claim for causality. Communication Yearbook, 35, 343–386.
Wright, P. J. (2012). A longitudinal analysis of U.S. adults’ pornography exposure sexual socialization, selective exposure, and the moderating role of unhappiness. Journal of Media Psychology, 24, 67–76. https://doi.org/10.1027/1864-1105/a000063.
Wright, P. J. (2014). Pornography and the sexual socialization of children: Current knowledge and a theoretical future. Journal of Children and Media, 8, 305–312. https://doi.org/10.1080/17482798.2014.923606.
Wright, P. J., & Bae, S. (2013). Pornography consumption and attitudes toward homosexuality: A national longitudinal study. Human Communication Research, 39, 492–513. https://doi.org/10.1111/hcre.12009.
Wright, P. J., & Randall, A. K. (2012). Internet pornography exposure and risky sexual behavior among adult males in the United States. Computers in Human Behavior, 28, 1410–1416. https://doi.org/10.1016/j.chb.2012.03.003.
Wright, P. J., Tokunaga, R. S., & Bae, S. (2014). More than a dalliance? Pornography consumption and extramarital sex attitudes among married US adults. Psychology of Popular Media Culture, 3, 97–109. https://doi.org/10.1037/ppm0000024.
Ybarra, M. L., & Mitchell, K. J. (2005). Exposure to Internet pornography among children and adolescents: A national survey. CyberPsychology & Behavior, 8, 473–486. https://doi.org/10.1089/cpb.2005.8.473.
Yee, N., & Bailenson, J. (2007). The Proteus effect: The effect of transformed self-representation on behavior. Human Communication Research, 33, 271–290. https://doi.org/10.1111/j.1468-2958.2007.00299.x.
Zillman, D., & Bryant, J. (1985). Selective exposure to communication. Mahwah, NJ: Lawrence Erlbaum Associates.
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Vandenbosch, L., van Oosten, J.M.F. Explaining the Relationship Between Sexually Explicit Internet Material and Casual Sex: A Two-Step Mediation Model. Arch Sex Behav 47, 1465–1480 (2018). https://doi.org/10.1007/s10508-017-1145-8
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DOI: https://doi.org/10.1007/s10508-017-1145-8