The dynamics of adolescents’ pornography use and psychological well-being: a six-wave latent growth and latent class modeling approach

European Child & Adolescent Psychiatry volume 28, pages1567–1579(2019)Cite this article

Abstract

Despite increasing concerns that pornography decreases adolescents’ well-being, existing empirical support for this position is largely limited to cross-sectional studies. To explore possible links between adolescent pornography use and psychological well-being more systematically, this study focused on parallel dynamics in pornography use, self-esteem and symptoms of depression and anxiety. A sample of 775 female and 514 male Croatian high school students (Mage at baseline 15.9 years, SD 0.52) from 14 larger secondary schools, who were surveyed 6 times at approximately 5-month intervals, was used for the analyses. The longitudinal data were analyzed using latent growth curve and latent class growth modeling. We observed no significant correspondence between growth in pornography use and changes in the two indicators of psychological well-being over time in either female or male participants. However, a significant negative association was found between female adolescents’ pornography use and psychological well-being at baseline. Controlling for group-specific trajectories of pornography use (i.e., latent classes) confirmed the robustness of findings in the both female and male samples. This study’s findings do not corroborate the notion that pornography use in middle to late adolescence contributes to adverse psychological well-being, but do not rule out such a link during an earlier developmental phase—particularly in female adolescents. The findings have ramifications for educational and adolescent health specialists, but also for concerned parents.

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Notes

  1. 1.

    Only primary schooling (8 years) is compulsory in Croatia. A great majority of children who finish a primary school continue their education. Secondary schools are divided into vocational schools (3- or 4-year programs) and gymnasiums (only 4-year programs). In contrast to students from vocational schools, the majority of gymnasium students enter a college or university program. Expectedly, there is are substantial differences in family socioeconomic status and parents’ education between students from vocational schools (lower) and gymnasiums (higher).

References

  1. 1.

    Mesch GS (2009) Social bonds and Internet pornographic exposure among adolescents. J Adolesc 32(3):601–618

    PubMed  Google Scholar 

  2. 2.

    Tylka TL (2015) No harm in looking, right? Men’s pornography consumption, body image, and well-being. Psychol Men Masculinity 16(1):97–107

    Google Scholar 

  3. 3.

    Peter J, Valkenburg PM (2011) The use of sexually explicit internet material and its antecedents: a longitudinal comparison of adolescents and adults. Arch Sex Behav 40(5):1015–1025

    PubMed  Google Scholar 

  4. 4.

    Doornwaard SM, Bickham DS, Rich M, Vanwesenbeeck I, van den Eijnden RJJM, ter Bogt TFM (2014) Sex-related online behaviors and adolescents’ body and sexual self-perceptions. Pediatrics 134(6):1103–1110

    PubMed  Google Scholar 

  5. 5.

    Kim YH (2001) Korean adolescents’ health risk behaviors and their relationships with the selected psychological constructs. J Adolesc Health 29(4):298–306

    CAS  PubMed  Google Scholar 

  6. 6.

    Kim Y-H (2011) Adolescents ’ health behaviours and its associations with psychological variables. Cent Eur J Public Health 19(4):205–209

    PubMed  Google Scholar 

  7. 7.

    Weaver JB, Weaver SS, Mays D, Hopkins GL, Kannenberg W, McBride D (2011) Mental- and physical-health indicators and sexually explicit media use behavior by adults. J Sex Med 8(3):764–772

    PubMed  Google Scholar 

  8. 8.

    Ybarra ML, Mitchell KJ, Hamburger M, Diener-West M, Leaf PJ (2011) X-rated material and perpetration of sexually aggressive behavior among children and adolescents: is there a link? Aggress Behav 37(1):1–18

    PubMed  Google Scholar 

  9. 9.

    Collins RL, Strasburger VC, Brown JD, Donnerstein E, Lenhart A, Ward LM (2017) Sexual media and childhood well-being and health. Pediatrics 140(Supplement 2):S162–S166

    PubMed  Google Scholar 

  10. 10.

    Štulhofer A, Buško V, Landripet I (2010) Pornography, sexual socialization, and satisfaction among young men. Arch Sex Behav 39(1):168–178

    PubMed  Google Scholar 

  11. 11.

    Zillmann D, Bryant J (1988) Effects of prolonged consumption of pornography on family values. J Fam 9(4):518–544

    Google Scholar 

  12. 12.

    Fredrickson BL, Roberts TA (1997) Toward understanding women’s lived experiences and mental health risks. Psychol Women Q 21(2):173–206

    Google Scholar 

  13. 13.

    Boynton PM (1999) ‘Is that supposed to be sexy?’ Women discuss women in ‘top shelf’ magazines. J Community Appl Soc Psychol 9(6):449–461

    Google Scholar 

  14. 14.

    Kohut T, Štulhofer A (2018) Is pornography use a risk for adolescent wellbeing? An examination of temporal relationships in two independent panel samples. PLoS One 13(8):1–20

    Google Scholar 

  15. 15.

    Valkenburg PM, Peter J (2013) The differential susceptibility to media effects model. J Commun 63(2):221–243

    Google Scholar 

  16. 16.

    Doornwaard SM, van den Eijnden RJJM, Overbeek G, ter Bogt TFM (2015) Differential developmental profiles of adolescents using sexually explicit internet material. J Sex Res 52(3):269–281

    PubMed  Google Scholar 

  17. 17.

    Cranney S, Koletić G, Štulhofer A (2018) Varieties of religious and pornographic experience: latent growth in adolescents’ religiosity and pornography use. Int J Psychol Relig 28(3):174–186

    Google Scholar 

  18. 18.

    Kroenke K, Spitzer RL, Williams JBW, Lowe B (2009) An ultra-brief screening scale for anxiety and depression: the PHQ-4. Psychosomatics 50(6):613–621

    PubMed  Google Scholar 

  19. 19.

    Cénat JM, Hébert M, Blais M, Lavoie F, Guerrier M, Derivois D (2014) Cyberbullying, psychological distress and self-esteem among youth in Quebec schools. J Affect Disord 169:7–9

    PubMed  PubMed Central  Google Scholar 

  20. 20.

    Graham JW (2012) Missing data: analysis and design. Springer, New York

    Google Scholar 

  21. 21.

    Little TD (2013) Longitudinal structural equation modeling. Guilford Press, New York

    Google Scholar 

  22. 22.

    Xitao F, Xiaotao F (2005) Power of latent growth modeling for detecting linear growth: number of measurements and comparison with other analytic approaches. J Exp Educ 73(2):121–139

    Google Scholar 

  23. 23.

    Preacher KJ, Wicham AL, MacCallum RC, Briggs NE (2008) Latent growth curve modeling. Sage, Thousand Oaks

    Google Scholar 

  24. 24.

    Duncan TE, Duncan SC, Strycker LA (2006) An introduction to latent variable growth curve modeling. Psychology Press, New York

    Google Scholar 

  25. 25.

    Nagin DS (1999) Analyzing developmental trajectories: a semiparametric, group-based approach. Psychol Methods 4(2):139–157

    Google Scholar 

  26. 26.

    Andruff H, Carraro N, Thompson A, Gaudreau P (2009) Latent class growth modelling: a tutorial. Tutor Quant Methods Psychol 5(1):11–24

    Google Scholar 

  27. 27.

    Jung T, Wickrama KAS (2008) An introduction to latent class growth analysis and growth mixture modeling. Soc Pers Psychol Compass 2(1):302–317

    Google Scholar 

  28. 28.

    Grimm KJ, Ram N, Estabrook R (2017) Growth modeling: structural equation and multilevel modeling approaches. Guilford Press, New York

    Google Scholar 

  29. 29.

    Nagin DS (2005) Group-based modelling of development. Harvard University Press, Cambridge

    Google Scholar 

  30. 30.

    Berlin KS, Parra GR, Williams NA (2014) An introduction to latent variable mixture modeling (part 2): longitudinal latent class growth analysis and growth mixture models. J Pediatr Psychol 39(2):188–203

    PubMed  Google Scholar 

  31. 31.

    Nagin DS, Odgers CL (2010) Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol 6(1):109–138

    PubMed  Google Scholar 

  32. 32.

    Nylund KL, Asparouhov T, Muthén BO (2007) Deciding on the number of classes in latent class analysis and growth mixture modeling: a monte carlo simulation study. Struct Equ Model A Multidiscip J 14(4):535–569

    Google Scholar 

  33. 33.

    Proust-Lima C, Philipps V, Liquet B (2017) Estimation of extended mixed models using latent classes and latent processes: the R package lcmm. J Stat Softw 78(2):1–56

    Google Scholar 

  34. 34.

    Tomić I, Burić J, Štulhofer A (2018) Associations between Croatian adolescents’ use of sexually explicit material and sexual behavior: does parental monitoring play a role? Arch Sex Behav 47(6):1881–1893

    PubMed  Google Scholar 

  35. 35.

    Wetterneck CT, Burgess AJ, Short MB, Smith AH, Cervantes ME (2012) The role of sexual compulsivity, impulsivity, and experiential avoidance in internet pornography use. Psychol Rec 62(1):3–18

    Google Scholar 

  36. 36.

    Peter J, Valkenburg PM (2016) Adolescents and pornography: a review of 20 years of research. J Sex Res 53(4–5):509–531

    PubMed  Google Scholar 

  37. 37.

    Harden KP (2014) A sex-positive framework for research on adolescent sexuality. Perspect Psychol Sci 9(5):455–469

    PubMed  Google Scholar 

  38. 38.

    Mota NP, Cox BJ, Katz LY, Sareen J (2010) Relationship between mental disorders/suicidality and three sexual behaviors: results from the National Comorbidity Survey replication. Arch Sex Behav 39(3):724–734

    PubMed  Google Scholar 

  39. 39.

    Hallfors DD, Waller MW, Bauer D, Ford CA, Halpern CT (2005) Which comes first in adolescence—sex and drugs or depression? Am J Prev Med 29(3):163–170

    PubMed  Google Scholar 

  40. 40.

    Kastbom ÅA, Sydsjö G, Bladh M, Priebe G, Svedin C-G (2015) Sexual debut before the age of 14 leads to poorer psychosocial health and risky behaviour in later life. Acta Paediatr 104(1):91–100

    PubMed  Google Scholar 

  41. 41.

    Principi N, Magnoni P, Grimoldi L, Carnevali D, Cavazzana L, Pellai A (2019) Consumption of sexually explicit internet material and its effects on minors’ health: latest evidence from the literature. Minerva Pediatr. https://www.minervamedica.it/en/journals/minervapediatrica/article.php?cod=R15Y9999N00A19021302

  42. 42.

    Baer JL, Kohut T, Fisher WA (2015) Is pornography use associated with anti-woman sexual aggression? Re-examining the confluence model with third variable considerations. Can J Hum Sex 24(2):160–173

    Google Scholar 

  43. 43.

    Campbell L, Kohut T (2017) The use and effects of pornography in romantic relationships. Curr Opin Psychol 13:6–10

    PubMed  Google Scholar 

  44. 44.

    Kohut T, Balzarini RN, Fisher WA, Campbell L (2018) Pornography’s associations with open sexual communication and relationship closeness vary as a function of dyadic patterns of pornography use within heterosexual relationships. J Soc Pers Relat 35(4):655–676

    Google Scholar 

  45. 45.

    Rasmussen KR, Bierman A (2018) Risk or release? Porn use trajectories and the accumulation of sexual partners. Soc Curr 5(6):566–582

    Google Scholar 

  46. 46.

    Carvalheira A, Traeen B, Štulhofer A (2014) Correlates of men’s sexual interest: a cross-cultural study. J Sex Med 11(1):154–164

    PubMed  Google Scholar 

  47. 47.

    Landripet I, Štulhofer A (2015) Is pornography use associated with sexual difficulties and dysfunctions among younger heterosexual men? J Sex Med 12(5):1136–1139

    PubMed  Google Scholar 

  48. 48.

    Werner M, Štulhofer A, Waldorp L, Jurin T (2018) A network approach to hypersexuality: insights and clinical implications. J Sex Med 15(3):410–415

    Google Scholar 

  49. 49.

    Bergkvist L, Rossiter JR (2007) The predictive validity of multiple-item versus single-item measures of the same constructs. J Mark Res 44(2):175–184

    Google Scholar 

  50. 50.

    Diamantopoulos A, Sarstedt M, Fuchs C, Wilczynski P, Kaiser S (2012) Guidelines for choosing between multi-item and single-item scales for construct measurement: a predictive validity perspective. J Acad Mark Sci 40(3):434–449

    Google Scholar 

  51. 51.

    Suldo S, Thalji A, Ferron J (2011) Longitudinal academic outcomes predicted by early adolescents’ subjective well-being, psychopathology, and mental health status yielded from a dual factor model. J Posit Psychol 6(1):17–30

    Google Scholar 

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Funding

The study has been funded by the Croatian Science foundation (Grant #9221 awarded to the first author). Additional funding was provided by Atlantic Grupa, d.d.

Author information

Affiliations

  1. Department of Sociology, Faculty of Humanities and Social Sciences, University of Zagreb, Zagreb, Croatia

    Aleksandar Štulhofer & Taylor Kohut

  2. Department of Electronics Systems and Information Processing, Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

    Azra Tafro

  3. Department of Psychology, Faculty of Social Science, 7430 Social Science Centre, University of Western Ontario, 1151 Richmond St, London, ON, N6A 3K7, Canada

    Taylor Kohut

Authors
  1. Aleksandar Štulhofer
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  2. Azra Tafro
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  3. Taylor Kohut
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Contributions

AŠ conceptualized and designed the study, collected data, carried out the analysis with AT and, together with TK, drafted the initial manuscript. All the authors revised and approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Corresponding author

Correspondence to Taylor Kohut.

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Štulhofer, A., Tafro, A. & Kohut, T. The dynamics of adolescents’ pornography use and psychological well-being: a six-wave latent growth and latent class modeling approach. Eur Child Adolesc Psychiatry 28, 1567–1579 (2019). https://doi.org/10.1007/s00787-019-01318-4

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Keywords

  • Adolescents
  • Pornography use
  • Depression and anxiety
  • Self-esteem
  • Psychological