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Are We Losing the Most Relevant Cases First? Selective Dropout in Two Longitudinal Studies of Adolescent Pornography Use

Abstract

In longitudinal studies of pornography use, selective loss of participants who may be more vulnerable to the effects of pornography than their peers is a serious concern. To explore the potential for such selective dropout, we used data from two independent large-scale panel studies of adolescents’ pornography use. Of the three types of attrition—early attrition, later attrition, and gaps in participation—only the first was substantially higher among more vulnerable adolescents, compared with other participants. Panel type (online vs. classroom-based) moderated only the association between vulnerability and participation gaps, which was significant in the classroom-based but not the online panel. Overall, this study’s findings point to the importance of delaying selective dropout by developing a comprehensive plan of action, for which we offer some guidelines.

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Notes

  1. 1.

    According to the national guidelines for ethical research with minors (Kolesarić & Ajduković, 2003), if participants are aged 14 years or older, their parents need only be informed about the study; informed consent should be obtained from participants.

  2. 2.

    The final study wave, in which the distinction was logically impossible, served to differentiate between attrition and participation gaps in the previous one. In addition, observations for students who attended a 3-year vocational program (the majority of our participants were enrolled in a 4-year secondary-school program) were right-censored after T3 in the Zagreb panel and T4 in the Rijeka panel.

  3. 3.

    Faced with the unexpectedly high dropout, the authors decided to end the study (personal communication with L. Kuyper).

  4. 4.

    The PROBIOPS study created a Facebook group to maintain contact with participants, mainly by periodically posting infographics with (non-central) study findings.

References

  1. Campbell, L., & Kohut, T. (2017). The use and effects of pornography in romantic relationships. Current Opinion in Psychology, 13, 6–10. https://doi.org/10.1016/j.copsyc.2016.03.004.

    Article  PubMed  Google Scholar 

  2. Cénat, J. M., Hébert, M., Blais, M., Lavoie, F., Guerrier, M., & Derivois, D. (2014). Cyberbullying, psychological distress and self-esteem among youth in Quebec schools. Journal of Affective Disorders, 169, 7–9. https://doi.org/10.1016/j.jad.2014.07.019

    Article  PubMed  PubMed Central  Google Scholar 

  3. Cronbach, L. J., Ambron, S. R., Dornbusch, S. M., Hess, R. D., Hornik, R. C., Phillips, D. C., et al. (1981). Toward reform of program evaluation. San Francisco: Jossey-Bass.

    Google Scholar 

  4. Dawson, K., Tafro, A., & Štulhofer, A. (2019). Adolescent sexual aggressiveness and pornography use: A longitudinal assessment. Aggressive Behavior, 45(6), 587–597. https://doi.org/10.1002/ab.21854.

    Article  PubMed  Google Scholar 

  5. Emerson, M. O., & Sikkink, D. (2006). Portraits of American Life Study, 1st Wave. https://www.thearda.com/pals/

  6. Fidler Mis, N., Kennedy, K., Fewtrell, M., Campoy, C., Koletzko, B., & Working Group on Early Nutrition Research, European Society for Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN). (2018). Role of incentives in long-term nutritional and growth studies in children. Journal of Pediatric Gastroenterology and Nutrition, 67(6), 767–772. https://doi.org/10.1097/MPG.0000000000002143.

    Article  PubMed  Google Scholar 

  7. Fisher, W. A., & Kohut, T. (2020). Reading pornography: Methodological considerations in evaluating pornography research. Journal of Sexual Medicine, 17(2), 195–209. https://doi.org/10.1016/j.jsxm.2019.11.257.

    Article  Google Scholar 

  8. Fröjd, S. A., Kaltiala-Heino, R., & Marttunen, M. J. (2011). Does problem behaviour affect attrition from a cohort study on adolescent mental health? European Journal of Public Health, 21(3), 306–310. https://doi.org/10.1093/eurpub/ckq078.

    Article  PubMed  Google Scholar 

  9. Graham, J. W., Taylor, B. J., Olchowski, A. E., & Cumsille, P. E. (2006). Planned missing data designs in psychological research. Psychological Methods, 11(4), 323–343. https://doi.org/10.1037/1082-989X.11.4.323.

    Article  PubMed  Google Scholar 

  10. Groves, R., & Peytcheva, E. (2008). The impact of nonresponse rates on nonresponse bias: A meta-analysis. Public Opinion Quarterly, 72(2), 167–189. https://doi.org/10.1093/poq/nfnOl.

    Article  Google Scholar 

  11. Grubbs, J. B., Wilt, J. A., & Exline, J. J. (2018). Predicting pornography use over time: Does self-reported “addiction” matter? Addictive Behaviors, 82, 57–64. https://doi.org/10.1016/j.addbeh.2018.02.028.

    Article  PubMed  Google Scholar 

  12. Gustavson, K., von Soest, T., Karevold, E., & Røysamb, E. (2012). Attrition and generalizability in longitudinal studies: findings from a 15-year population-based study and a Monte Carlo simulation study. BMC Public Health, 12(1), 918. https://doi.org/10.1186/1471-2458-12-918.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Hagen, T., Thompson, M. P., & Williams, J. (2018). Religiosity reduces sexual aggression and coercion in a longitudinal cohort of college men: Mediating roles of peer norms, promiscuity, and pornography. Journal for the Scientific Study of Religion, 57(1), 95–108. https://doi.org/10.1111/jssr.12496.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Halpern, C. T., Udry, J. R., & Suchindran, C. (1998). Monthly measures of salivary testosterone predict sexual activity in adolescent males. Archives of Sexual Behavior, 27(5), 445–465.

    Article  Google Scholar 

  15. Hansen, W. B., Collins, L. M., Malotte, K., Johnson, C. A., & Fielding, J. E. (1985). Attrition in prevention research. Journal of Behavioral Medicine, 8(3), 261–275. https://doi.org/10.1007/BF00870313.

    Article  PubMed  Google Scholar 

  16. Hansen, W. B., Tobler, N. S., & Graham, J. W. (1990). Attrition in substance abuse prevention research: A meta-analysis of 85 longitudinally followed cohorts. Evaluation Review, 14(6), 677–685.

    Article  Google Scholar 

  17. Harden, K. P. (2014). A sex-positive framework for research on adolescent sexuality. Perspectives on Psychological Science, 9(5), 455–469. https://doi.org/10.1177/1745691614535934.

    Article  PubMed  Google Scholar 

  18. Horvath, M., Alys, L., Massey, K., Pina, A., Scally, M., & Adler, J. R. (2013). “Basically...porn is everywhere”. A rapid evidence assessment on the effects that access and exposure to pornography has on children and young people. Office of the Children’s Commissioner. http://kar.kent.ac.uk/44763/1/BasicallyporniseverywhereReport.pdf

  19. Kaufman, L., & Rousseeuw, P. J. (1990). Finding groups in data: An introduction to cluster analysis. Hoboken: Wiley.

    Book  Google Scholar 

  20. Kent, P., Jensen, R. K., & Kongsted, A. (2014). A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS twostep cluster analysis, latent gold and SNOB. BMC Medical Research Methodology, 14(1), 113. https://doi.org/10.1186/1471-2288-14-113.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kohut, T., Balzarini, R. N., Fisher, W. A., Grubbs, J. B., Campbell, L., & Prause, N. (2020). Surveying pornography use: A shaky science resting on poor measurement foundations. Journal of Sex Research, 57(6), 722–742. https://doi.org/10.1080/00224499.2019.1695244.

    Article  PubMed  Google Scholar 

  22. Kohut, T., Landripet, I., & Štulhofer, A. (2020). Testing the confluence model of the association between pornography use and male sexual aggression: A longitudinal assessment in two independent adolescent samples from Croatia. Archives of Sexual Behavior. https://doi.org/10.1007/s10508-020-01824-6.

  23. Kolesarić, V., & Ajduković, M. (2003). Etički kodeks istraživanja s djecom [Guidelines for ethical research in minors]. Vijeće za djecu Vlade Republike Hrvatske.

  24. Koletić, G. (2017). Longitudinal associations between the use of sexually explicit material and adolescents’ attitudes and behaviors: A narrative review of studies. Journal of Adolescence, 57, 119–133. https://doi.org/10.1016/j.adolescence.2017.04.006.

    Article  PubMed  Google Scholar 

  25. Kuyper, L., De Wit, J., Adam, P., & Woertman, L. (2012). Doing more good than harm? The effects of participation in sex research on young people in the Netherlands. Archives of Sexual Behavior, 41(2), 497–506. https://doi.org/10.1007/s10508-011-9780-y.

    Article  PubMed  Google Scholar 

  26. Ladin L’Engle, K., Pardun, C. J., & Brown, J. D. (2004). Accessing adolescents: A school-recruited, home-based approach to conducting media and health research. Journal of Early Adolescence, 24(2), 144–158. https://doi.org/10.1177/0272431603262668.

    Article  Google Scholar 

  27. Landripet, I., Štulhofer, A., & Baćak, V. (2011). Changes in human immunodeficiency virus and sexually transmitted infections-related sexual risk taking among young Croatian adults: Findings from the 2005 and 2010 population-based surveys. Croatian Medical Journal, 52(4), 458–468. https://doi.org/10.3325/cmj.2011.52.458.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Laurie, H. (2008). Minimizing panel attrition. In S. Menard (Ed.), Handbook of longitudinal research, design, measurement, and analysis (pp. 167–184). Cambridge, England: Academic Press.

    Google Scholar 

  29. Laurie, H., & Lynn, P. (2009). The use of respondent incentives on longitudinal surveys. In P. Lynn (Ed.), Methodology of longitudinal surveys (pp. 205–233). Hoboken, NJ: Wiley. https://doi.org/10.1002/9780470743874.ch1

    Chapter  Google Scholar 

  30. Liu, M., & Wronski, L. (2018). Trap questions in online surveys: Results from three web survey experiments. International Journal of Market Research, 60(1), 32–49. https://doi.org/10.1177/1470785317744856.

    Article  Google Scholar 

  31. Lynn, P. (2018). Tackling panel attrition. In D. L. Vannette & J. A. Krosnick (Eds.), Palgrave handbook of survey research (pp. 143–153). Berlin: Springer.https://doi.org/10.1007/978-3-319-54395-6_19

    Chapter  Google Scholar 

  32. Malamuth, N., & Huppin, M. (2005). Pornography and teenagers: The importance of individual differences. Adolescent Medicine Clinics, 16, 315–326. https://doi.org/10.1016/j.admecli.2005.02.004.

    Article  PubMed  Google Scholar 

  33. Marshall, E. A., & Miller, H. A. (2019). Consistently inconsistent: A systematic review of the measurement of pornography use. Aggression and Violent Behavior, 48, 169–179. https://doi.org/10.1016/j.avb.2019.08.019.

    Article  Google Scholar 

  34. Michaud, P.-A., Suris, J. C., & Deppen, A. (2006). Gender-related psychological and behavioural correlates of pubertal timing in a national sample of Swiss adolescents. Molecular and Cellular Endocrinology, 254–255, 172–178. https://doi.org/10.1016/j.mce.2006.04.037.

    Article  PubMed  Google Scholar 

  35. Miller, D. J., Raggatt, P. T. F., & McBain, K. (2020). A literature review of studies into the prevalence and frequency of men’s pornography use. American Journal of Sexuality Education, 15, 502–529. https://doi.org/10.1080/15546128.2020.1831676.

    Article  Google Scholar 

  36. Müller, B., & Castiglioni, L. (2017). Do temporary dropouts improve the composition of panel data? An analysis of “gap interviews” in the German Family Panel pairfam. Sociological Methods & Research. https://doi.org/10.1177/0049124117729710.

    Article  Google Scholar 

  37. Owens, E. W., Behun, R. J., Manning, J. C., & Reid, R. C. (2012a). The impact of internet pornography on adolescents: A review of the research. Sexual Addiction and Compulsivity, 19(1–2), 99–122. https://doi.org/10.1080/10720162.2012.660431.

    Article  Google Scholar 

  38. Owens, E. W., Behun, R. J., Manning, J. C., & Reid, R. C. (2012b). The impact of internet pornography on adolescents: A review of the research. Sexual Addiction & Compulsivity, 19, 99–122. https://doi.org/10.1080/10720162.2012.660431.

    Article  Google Scholar 

  39. Perry, S. L. (2017a). Does viewing pornography diminish religiosity over time? Evidence from two-wave panel. Journal of Sex Research, 54(2), 214–226. https://doi.org/10.1080/00224499.2016.1146203.

    Article  PubMed  Google Scholar 

  40. Perry, S. L. (2017b). Does viewing pornography diminish religiosity over time? Evidence from two-wave panel data. Journal of Sex Research, 54(2), 214–226. https://doi.org/10.1080/00224499.2016.1146203.

    Article  PubMed  Google Scholar 

  41. Perry, S. L., & Schleifer, C. (2018). Till porn do us part? A longitudinal examination of pornography use and divorce. Journal of Sex Research, 55(3), 284–296. https://doi.org/10.1080/00224499.2017.1317709.

    Article  PubMed  Google Scholar 

  42. Peter, J., & Valkenburg, P. M. (2008). Adolescents’ exposure to sexually explicit internet material and sexual preoccupancy: A three-wave panel study. Media Psychology, 11(2), 207–234. https://doi.org/10.1080/15213260801994238.

    Article  Google Scholar 

  43. 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.

    Article  PubMed  Google Scholar 

  44. Peter, J., & Valkenburg, P. M. (2016). Adolescents and pornography: A review of 20 years of research. Journal of Sex Research, 53(4–5), 509–531. https://doi.org/10.1080/00224499.2016.1143441.

    Article  PubMed  Google Scholar 

  45. Reitz, E., van de Bongardt, D., Baams, L., Doornwaard, S., Dalenberg, W., Dubas, J., et al. (2015). Project STARS (Studies on Trajectories of Adolescent Relationships and Sexuality): A longitudinal, multi-domain study on sexual development of Dutch adolescents. European Journal of Developmental Psychology, 12(5), 613–626. https://doi.org/10.1080/17405629.2015.1018173.

    Article  Google Scholar 

  46. Rhemtulla, M., & Hancock, G. R. (2016). Planned missing data designs in educational psychology research. Educational Psychologist, 51(3–4), 305–316. https://doi.org/10.1080/00461520.2016.1208094.

    Article  Google Scholar 

  47. Rothman, S. (2009). Estimating attrition bias in the Year 9 cohorts of the Longitudinal Surveys of Australian Youth: Technical Report No. 48. In LSAY Technical Reports.

  48. Seymour, K. (2012). Using incentives: Encouraging and recognising participation in youth research. Youth Studies Australia, 31(3), 51–59.

    Google Scholar 

  49. Short, M. B., Black, L., Smith, A. H., Wetterneck, C. T., & Wells, D. E. (2012). A review of Internet pornography use research: methodology and content from the past 10 years. Cyberpsychology, Behavior and Social Networking, 15(1), 13–23. https://doi.org/10.1089/cyber.2010.0477.

    Article  PubMed  Google Scholar 

  50. Steer, C., Goodman, R., Lamberts, K., Waylen, A., Wolke, D., Samara, M., & Ford, T. (2009). Selective drop-out in longitudinal studies and non-biased prediction of behaviour disorders. British Journal of Psychiatry, 195, 249–256. https://doi.org/10.1192/bjp.bp.108.053751.

    Article  Google Scholar 

  51. Štulhofer, A., Kohut, T., & Koletić, G. (in press). Pornography use in adolescence and young adulthood. In D. P. VanderLaan & W. I. Wong (Eds.), Gender and sexuality development. Berlin: Springer.

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

    Article  Google Scholar 

  53. Valkenburg, P. M., & Peter, J. (2013). The differential susceptibility to media effects model. Journal of Communication, 63(2), 221–243. https://doi.org/10.1111/jcom.12024.

    Article  Google Scholar 

  54. 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.

    Article  Google Scholar 

  55. Winefield, A. H., Winefield, H., & Tiggemann, M. (1990). Sample attrition bias in a longitudinal study of young people. Australian Journal of Psychology, 42(1), 75–85.

    Article  Google Scholar 

  56. Wright, P. J. (2014). Pornography and the sexual socialization of children: Current knowledge and a theoretical future. Journal of Children and Media, 8(3), 305–312. https://doi.org/10.1080/17482798.2014.923606.

    Article  Google Scholar 

  57. Ybarra, M. L., Mitchell, K. J., Hamburger, M., Diener-West, M., & Leaf, P. J. (2011). X-rated material and perpetration of sexually aggressive behavior among children and adolescents: Is there a link? Aggressive Behavior, 37(1), 1–18. https://doi.org/10.1002/ab.20367.

    Article  PubMed  Google Scholar 

  58. Young, A. F., Powers, J. R., & Bell, S. L. (2006). Attrition in longitudinal studies: Who do you lose? Australian and New Zealand Journal of Public Health, 30(4), 353–361. https://doi.org/10.1111/j.1467-842X.2006.tb00849.x.

    Article  PubMed  Google Scholar 

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Acknowledgements

This work has been fully funded by Croatian Science Foundation (Grant Number 9221 awarded to the first author).

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Correspondence to Goran Koletić.

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The authors confirm that all relevant ethical safeguards have been met in relation to subject protection including informed consent and approval by the Committee on Ethics Issues in Science and Research of the Faculty of Humanities and Social Sciences, University of Zagreb. The Ethics Issues Confirmation was issued on 2 June 2014.

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Štulhofer, A., Matković, T., Kohut, T. et al. Are We Losing the Most Relevant Cases First? Selective Dropout in Two Longitudinal Studies of Adolescent Pornography Use. Arch Sex Behav 50, 2215–2226 (2021). https://doi.org/10.1007/s10508-021-01931-y

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Keywords

  • Adolescents
  • Pornography use
  • Panel attrition
  • Selective dropout
  • PROBIOPS