Display options
Share it on

Exp Clin Psychopharmacol. 2021 Apr 29; doi: 10.1037/pha0000459. Epub 2021 Apr 29.

Reinforcer pathology of internet-related behaviors among college students: Data from six countries.

Experimental and clinical psychopharmacology

Samuel F Acuff, Angelina Pilatti, Megan Collins, Leanne Hides, Nutankumar S Thingujam, Wen Jia Chai, Wai Meng Yap, Ruichong Shuai, Lee Hogarth, Adrian J Bravo, James G Murphy

Affiliations

  1. Department of Psychology.
  2. Instituto de Investigaciones Psicológicas.
  3. School of Psychology.
  4. Department of Neurosciences.
  5. Department of Psychological Science.

PMID: 33914568 PMCID: PMC8553798 DOI: 10.1037/pha0000459

Abstract

Research has demonstrated that repeated engagement in low-effort behaviors that are associated with immediate reward, such as Internet use, can result in a pathological reinforcement process in which the behavior is increasingly selected over other activities due, in part, to a low availability of alternative activities and to a strong preference for immediate rather than delayed rewards (delay discounting). However, this reinforcer pathology model has not been generalized to other Internet-related behaviors, such as online gaming or smartphone use. Given the widespread availability of these technologies, it is also important to examine whether reinforcer pathology of Internet-related behaviors is culturally universal or culture-specific. The current study examines relations between behavioral economic constructs (Internet demand, delay discounting, and alternative reinforcement) and Internet-related addictive behaviors (harmful Internet use, smartphone use, online gaming, and Internet sexual behavior) in a cross-sectional sample of college students (N = 1,406) from six different countries (Argentina, Australia, India, Malaysia, the United Kingdom, and the United States). Using structural equation modeling, Internet demand was associated with harmful Internet use, smartphone use, and online gaming; delay discounting was associated with harmful smartphone use; and alternative reinforcement was associated with harmful Internet and smartphone use. The models were partially invariant across countries. However, mean levels of behavioral economic variables differed across countries, country-level gross domestic product, person-level income, and sex at birth. Results support behavioral economic theory and highlight the importance of considering both individual and country-level sociocultural contextual factors in models for understanding harmful engagement with Internet-related behaviors. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

References

  1. Alcohol Clin Exp Res. 2020 Jul;44(7):1497-1507 - PubMed
  2. J Abnorm Psychol. 1988 May;97(2):181-95 - PubMed
  3. Exp Clin Psychopharmacol. 1999 Nov;7(4):412-26 - PubMed
  4. Cyberpsychol Behav Soc Netw. 2017 Feb;20(2):104-108 - PubMed
  5. Prev Med. 2019 Nov;128:105789 - PubMed
  6. J Exp Anal Behav. 2003 Jan;79(1):37-48 - PubMed
  7. Exp Clin Psychopharmacol. 2015 Dec;23(6):504-12 - PubMed
  8. Addiction. 2012 Dec;107(12):2191-200 - PubMed
  9. Int J Environ Res Public Health. 2018 Jan 16;15(1): - PubMed
  10. Nicotine Tob Res. 2012 Jun;14(6):761-5 - PubMed
  11. Addict Behav. 1998 Sep-Oct;23(5):705-9 - PubMed
  12. Psychol Med. 2016 Aug;46(11):2423-34 - PubMed
  13. Psychol Addict Behav. 2018 Aug;32(5):564-572 - PubMed
  14. Addict Behav. 2018 Sep;84:207-214 - PubMed
  15. Annu Rev Psychol. 2004;55:431-61 - PubMed
  16. Nature. 2010 Jul 1;466(7302):29 - PubMed
  17. Nicotine Tob Res. 2017 Jan;19(1):49-58 - PubMed
  18. Exp Clin Psychopharmacol. 2006 May;14(2):219-27 - PubMed
  19. Behav Processes. 2019 Aug;165:51-57 - PubMed
  20. J Sex Res. 2016 Jul-Aug;53(6):689-700 - PubMed
  21. J Adolesc. 2018 Jan;62:38-46 - PubMed
  22. Behav Brain Res. 2020 Sep 15;394:112815 - PubMed
  23. Behav Processes. 2017 Aug;141(Pt 1):33-41 - PubMed
  24. Psychol Aging. 1996 Mar;11(1):79-84 - PubMed
  25. Clin Psychol Sci. 2017 Jul;5(4):683-697 - PubMed
  26. Psychol Addict Behav. 2018 Nov;32(7):846-857 - PubMed
  27. Annu Rev Clin Psychol. 2014;10:641-77 - PubMed
  28. Front Psychol. 2017 Mar 10;8:363 - PubMed
  29. Cyberpsychol Behav. 1999;2(5):475-9 - PubMed
  30. Psychol Addict Behav. 2020 Feb;34(1):136-146 - PubMed
  31. Drug Alcohol Depend. 2016 Oct 01;167:57-66 - PubMed
  32. Exp Clin Psychopharmacol. 2015 Oct;23(5):377-86 - PubMed
  33. Behav Res Methods. 2008 May;40(2):563-74 - PubMed
  34. Psychopharmacology (Berl). 2011 Aug;216(3):305-21 - PubMed
  35. Addiction. 1998 Mar;93(3):321-35 - PubMed
  36. Cyberpsychol Behav Soc Netw. 2015 Aug;18(8):457-61 - PubMed
  37. J Exp Anal Behav. 1974 Jan;21(1):159-64 - PubMed
  38. PLoS One. 2013;8(2):e56936 - PubMed
  39. Drug Alcohol Depend. 2018 Nov 1;192:193-200 - PubMed
  40. JAMA Psychiatry. 2019 Nov 1;76(11):1176-1186 - PubMed
  41. Alcohol Clin Exp Res. 2018 Jul;42(7):1304-1314 - PubMed
  42. Prog Neuropsychopharmacol Biol Psychiatry. 2018 Dec 20;87(Pt A):3-10 - PubMed
  43. Behav Processes. 2014 Mar;103:256-60 - PubMed
  44. Addict Behav. 2020 Jul;106:106377 - PubMed
  45. Behav Res Methods. 2016 Mar;48(1):400-7 - PubMed
  46. Exp Clin Psychopharmacol. 2017 Oct;25(5):346-352 - PubMed
  47. Prev Med. 2015 Nov;80:75-81 - PubMed
  48. Clin Psychol Rev. 2019 Jun;70:79-90 - PubMed
  49. Psychopharmacology (Berl). 1999 Oct;146(4):447-54 - PubMed
  50. J Exp Anal Behav. 2018 Nov;110(3):553-568 - PubMed
  51. Addict Behav. 2018 Jun;81:125-133 - PubMed
  52. J Exp Anal Behav. 2016 Jul;106(1):93-106 - PubMed
  53. J Behav Addict. 2017 Sep 1;6(3):271-279 - PubMed

Publication Types

Grant support