Advertisement

Relationships between Exposure to Online Pornography, Psychological Well-Being and Sexual Permissiveness among Hong Kong Chinese Adolescents: a Three-Wave Longitudinal Study

  • Cecilia M. S. MaEmail author
Article

Abstract

With the increased accessibility to the Internet, adolescents can access the online pornography intentionally and accidentally. The purposes of this study were (a) to examine the relationships of exposure to online pornography to subsequent psychological well-being (depression and life satisfaction) and sexual permissive attitudes and (b) to explore whether these relationships differ by the nature of exposure. A sample of 1401 early Chinese adolescents participated a three-wave longitudinal study. Results from the cross-lagged models suggested that the effects of online pornography differ by the nature of exposure. The present study sheds light on the dynamic relationships between exposure to online pornography, depression, life satisfaction and permissiveness sexual attitudes.

Keywords

Online pornography Depression Life satisfaction Chinese adolescents Sexual permissive attitudes 

Notes

Acknowledgments

The present study is funded by a grant (Grant no. 25401414) of the Early Career Scheme of the Research Grants Council of the University Grants Committee of Hong Kong.

Compliance with Ethical Standards

Conflict of Interest

No competing financial interests exist.

References

  1. Amichai-Hamburger, Y., & Ben-Artzi, E. (2003). Loneliness and internet use. Computers in Human Behavior, 19, 71–80.CrossRefGoogle Scholar
  2. Apaolaza, V., Hartmann, P., Medina, E., Barrutia, J. M., & Echebarria, C. (2013). The relationship between socializing on the Spanish online networking site Tuenti and teenagers’ subjective wellbeing: The roles of self-esteem and loneliness. Computers in Human Behavior, 29, 1282–1289.CrossRefGoogle Scholar
  3. Arulogun, O. S., Ogbu, I. A., & Dipeolu, I. O. (2016). Influence of internet exposure on sexual behavior of young persons in urban district of Southwest Nigeria. The Pan African Medical Journal, 25, 261–268.CrossRefGoogle Scholar
  4. Baams, L., Overbeek, G., Dubas, J. S., Doornwaard, S. M., Rommes, E., & van Aken, M. A. G. (2015). Perceived realism moderates the relation between sexualized media consumption and permissive sexual attitudes in Dutch adolescents. Archives of Sexual Behavior, 44, 743–754.CrossRefGoogle Scholar
  5. Bonetti, L., Campbell, M. A., & Gilmore, L. (2010). The relationship of loneliness and social anxiety with children’s and adolescents’ online communication. Cyberpsychology, Behavior and Social Networking, 13(3), 279–285.CrossRefGoogle Scholar
  6. Braun-Courville, D. K., & Rojas, M. (2009). Exposure to sexually explicit web sites and adolescent sexual attitudes and behaviors. The Journal of Adolescent Health, 45(2), 156–162.CrossRefGoogle Scholar
  7. Brown, J. D., & Cantor, J. (2000). An agenda for research on youth and the media. Journal of Adolescent Health, 27, 1–7.Google Scholar
  8. Brown, J. D., & L’Engle, K. L. (2009). X-rated: Sexual attitudes and behaviors associated with U.S. early adolescents’ exposure to sexually explicit media. Communication Research, 36(1), 129–151.CrossRefGoogle Scholar
  9. Brown, J. D., L’Engle, K., Pardun, C., Guo, G., Kenneavy, K., & Jackson, C. (2006). Sexy media matter: Exposure to sexual content in music, movies, television and magazines predicts black and white adolescents’ sexual behavior. Pediatrics, 117, 1018–1027.CrossRefGoogle Scholar
  10. Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230–258.CrossRefGoogle Scholar
  11. Byrne, B. M. (1990). Methodological approaches to the validation of academic self-concept: The construct and its measures. Applied Measurement in Education, 3, 185–207.CrossRefGoogle Scholar
  12. Chen, A.-S., Leung, M., Chen, C.-H., & Yang, S. C. (2013). Exposure to internet pornography among Taiwanese adolescents. Social Behavior and Personality, 41(1), 157–164.CrossRefGoogle Scholar
  13. Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality Assessment, 49(1), 71–75.CrossRefGoogle Scholar
  14. Doornwaard, S. M., Bickham, D. S., Rich, M., ter Bogt, T. F. M., & van den Eijnden, R. J. J. M. (2015). Adolescents’ use of sexually explicit internet material and their sexual attitudes and behavior: Parallel development and directional effects. Developmental Psychology, 51(10), 1476–1488.CrossRefGoogle Scholar
  15. Flood, M. (2007). Exposure to pornography among youth in Australia. Journal of Sociology, 43(1), 45–60.CrossRefGoogle Scholar
  16. Häggström-Nordin, E., Hanson, U., & Tydén, T. (2005). Associations between pornography consumption and sexual practices among adolescents in Sweden. International Journal of STD & AIDS, 16, 102–107.CrossRefGoogle Scholar
  17. Hong Kong Census and Statistics Department. (2017). Information technology usage and penetration (Thematic Household Survey Report No. 62). Retrieved from http://www.censtatd.gov.hk/hkstat/sub/so120.jsp
  18. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.CrossRefGoogle Scholar
  19. Internet World Stats. (2018). World internet users statistics and 2017 world population stats. Retrieved from http://www.internetworldstats.com/stats.htm
  20. Jun, S. (2016). The reciprocal longitudinal relationships between mobile phone addiction and depressive symptoms among Korean adolescents. Computers in Human Behavior, 58, 179–186.CrossRefGoogle Scholar
  21. Kessler, R. C., & Greenberg, D. F. (1981). Linear panel analysis: Models of quantitative change. New York: Academic Press.Google Scholar
  22. Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613.CrossRefGoogle Scholar
  23. Little, T. D., Preacher, K. J., Selig, J. P., & Card, N. A. (2007). New developments in latent variable panel analyses of longitudinal data. International Journal of Behavioral Development, 31, 357–365.CrossRefGoogle Scholar
  24. Livingstone, S., & Bober, M. (2004). UK children go online: Surveying the experiences of young people and their parents. London: London School of Economics and Political Science.Google Scholar
  25. Lo, V., & Wei, R. (2006). Exposure to internet pornography and Taiwanese adolescents’ sexual attitudes and behavior. Journal of Broadcasting & Electronic Media, 49(2), 221–237.CrossRefGoogle Scholar
  26. Lou, C., Cheng, Y., Gao, E., Zuo, X., Emerson, M. R., & Zabin, L. S. (2012). Media’s contribution to sexual knowledge, attitudes, and behaviors for adolescents and young adults in three Asian cities. Journal of Adolescent Health, 50(3), S26–S36.CrossRefGoogle Scholar
  27. Ma, C. M. S. (2017). A latent profile analysis of internet use and its association with psychological well-being outcomes among Hong Kong Chinese early adolescents. Applied Research in Quality of Life. Advance online publication.  https://doi.org/10.1007/s11482-017-9555-2.
  28. Ma, C. M. S., & Shek, D. T. L. (2013). Consumption of pornographic materials in early adolescents in Hong Kong. Journal of Pediatric and Adolescent Gynecology, 26(3), S18–S25.CrossRefGoogle Scholar
  29. Ma, C. M. S., Shek, D. T. L., & Lai, C. C. W. (2016). Individual differences in intentional and unintentional exposure to online pornography among Hong Kong Chinese adolescents. International Journal on Disability and Human Development, 16(4), 417–423.Google Scholar
  30. Ma, C. M. S., Lai, C. C. W. & Shek, D. T. L. (2018). Intentional and unintentional exposure to online pornography among early adolescents: Findings in a Chinese context. Paper presented at International conference on business and social science. Kyoto, Japan. Retrieved from http://icbass.org/site/mypage.aspx?pid=24&lang=en&sid=6066
  31. Mitchell, K. J., Finkelhor, D., & Wolak, J. (2003). The exposure of youth to unwanted sexual material on the internet: A national survey of risk, impact, and prevention. Youth Society, 34(3), 330–358.CrossRefGoogle Scholar
  32. Morahan-Martin, J., & Schumacher, P. (2003). Loneliness and social uses of the internet. Computers in Human Behavior, 19, 659–671.CrossRefGoogle Scholar
  33. Nesi, J., & Prinstein, M. J. (2015). Using social media for social comparison and feedback-seeking: Gender and popularity moderate associations with depressive symptoms. Journal of Abnormal Child Psychology, 43, 1427–1438.CrossRefGoogle Scholar
  34. Peter, J., & Valkenburg, P. M. (2006). Adolescents’ exposure to sexually explicit online material and recreational attitudes toward sex. Communication Research, 56, 639–660.Google Scholar
  35. Peter, J., & Valkenburg, P. M. (2008). Adolescents’ exposure to sexually explicit materials, sexual uncertainty, and attittudes toward uncommitted sexual exploration: Is there a link? Communication Research, 35, 579–601.Google Scholar
  36. 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(5), 1015–1025.  https://doi.org/10.1007/s10508-010-9644-x.CrossRefGoogle Scholar
  37. Peter, J., & Valkenburg, P. M. (2016). Adolescents and Pornography: A review of 20 years of research. The Journal of Sex Research, 53, 509–531.Google Scholar
  38. Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among U.S. young adults. Computers in Human Behavior, 69, 1–9.CrossRefGoogle Scholar
  39. Satorra, A., & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications to development research (pp. 399–419). Thousand Oaks: Sage.Google Scholar
  40. Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507–514.  https://doi.org/10.1007/BF02296192.CrossRefGoogle Scholar
  41. Schalet, A. T. (2011). Beyound abstinence and risk: A new paradigm for adolescent sexual health. Women's Health Issues, 21(3), S5–S7.CrossRefGoogle Scholar
  42. Selig, J. P., & Little, T. D. (2012). Autoregressive and cross-lagged panel analysis for longitudinal data. In B. Laursen, T. D. Little, & N. A. Card (Eds.), Handbook of developmental research methods (pp. 265–278). New York: The Guildford Press.Google Scholar
  43. Shek, D. T. L., & Ma, C. M. S. (2016). A six-year longitudinal study of consumption of pornographic materials in Chinese adolescents in Hong Kong. Journal of Pediatric and Adolescent Gynecology, 29, S12–S21.CrossRefGoogle Scholar
  44. Sprecher, S. (1989). Premarital sexual standards of different categories of individuals. The Journal of Sex Research, 26(2), 232–248.CrossRefGoogle Scholar
  45. Statista (2018). Countries with the highest number of internet users 2017. Retrieved from https://www.statista.com/statistics/262966/number-of-internet-users-in-selected-countries/
  46. To, S. M., & Chu, F. (2009). An interpretive phenomenological analysis of the lived experiences of Chinese young females in the course of unintended pregnancy. International Journal of Adolescence Medicine and Health, 21(4), 531–543.Google Scholar
  47. Tom, S. M., Ngai, S. S. Y., & 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(11), 2156–2163.CrossRefGoogle Scholar
  48. Trepte, S., & Reinecke, L. (2013). The reciprocal effects of social network site use and the disposition for self-disclosure: A longitudinal study. Computers in Human Behavior, 29, 1101–1112.CrossRefGoogle Scholar
  49. Tu, X., Lou, C., Gao, E., Li, N., & Zabin, L. S. (2012). The relationship between sexual behavior and nonsexual risk behaviors among unmarried youth in three Asian cities. Journal of Adolescent Health, 50, S75–S82.CrossRefGoogle Scholar
  50. Valkenburg, P. M., Koutamanis, M., & Vossen, H. G. M. (2017). The concurrent and longitudinal relationships between adolescents’ use of social network sites and their social self-esteem. Computers in Human Behavior, 76, 35–41.CrossRefGoogle Scholar
  51. Van Oosten, J. M. F., Peter, J., & Boot, I. (2015). Exploring associations between exposure to sexy online self-presentations and adolescents’ sexual attitudes and behavior. Journal of Youth and Adolescence, 44, 1078–1091.CrossRefGoogle Scholar
  52. 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.CrossRefGoogle Scholar
  53. Wolak, J., Mitchell, K., & Finkelhor, D. (2007). Unwanted and wanted exposure to online pornography in a national sample of youth internet users. Pediatrics, 119(2), 247–257.  https://doi.org/10.1542/peds.2006-1891.CrossRefGoogle Scholar
  54. World Internet Project (2015). The world internet project international report (6th Ed.). Center for the Digital Future, USC Annenberg. Retrieved from http://www.digitalcenter.org/world-internet-project
  55. Ybarra, M. L., & Mitchell, K. J. (2005). Exposure to internet pornography among children and adolescents: A national survey. Cyberpsychology & Behavior, 8(5), 473–486.  https://doi.org/10.1089/cpb.2005.8.473.CrossRefGoogle Scholar
  56. Zhao, F., Zhang, Z. H., Bi, L., Wu, X. S., Wang, W. J., Li, Y. F., & Sun, Y. H. (2017). The association between life events and internet addiction among Chinese vocational school students: The mediating role of depression. Computers in Human Behavior, 70, 30–38.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature and The International Society for Quality-of-Life Studies (ISQOLS) 2018

Authors and Affiliations

  1. 1.Department of Applied Social SciencesThe Hong Kong Polytechnic UniversityKowloonHong Kong

Personalised recommendations