Skip to main content
Log in

Decision-making and Related Processes in Internet Gaming Disorder and Other Types of Internet-Use Disorders

  • Technology Addiction (J Billieux, Section Editor)
  • Published:
Current Addiction Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

The review aims to characterize decision-making in individuals with symptoms of Internet gaming disorder (IGD) and other types of Internet-use disorders. We therefore discuss both theories of decision-making and theoretical models of Internet-use disorders as well as recent studies which investigated decision-making in these addictive behaviors.

Recent Findings

Studies from 2012 to 2017 demonstrated that individuals with symptoms of IGD show riskier behavior, tend to disregard objective probabilities, display reduced feedback processing, and have a preference for immediate rewards. These behaviors are related to increased reward sensitivity and reduced executive/inhibitory control on behavioral and brain levels.

Summary

Risky and short-termly oriented decisions may be major aspects in the development and maintenance of IGD and other Internet-use disorders. Dual-process models of decision-making can explain the addictive behavior by interactions between immediate reward expectation, specific predisposing factors, and situational aspects. These interactions make it increasingly likely that short-term-oriented impulses towards the use of specific Internet applications overwhelm attempts to reflectively control the behavior.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Bechara A. Decision making, impulse control and loss of willpower to resist drugs: a neurocognitive perspective. Nat Neurosci. 2005;8:1458–63. doi:10.1038/nn1584.

    Article  CAS  PubMed  Google Scholar 

  2. Bechara A, Tranel D, Damasio H. Characterization of the decision-making deficit of patients with ventromedial prefrontal cortex lesions. Brain. 2000;123:2189–202. doi:10.1093/brain/123.11.2189.

    Article  PubMed  Google Scholar 

  3. Brand M, Fujiwara E, Borsutzky S, Kalbe E, Kessler J, Markowitsch HJ. Decision-making deficits of Korsakoff patients in a new gambling task with explicit rules: associations with executive functions. Neuropsychology. 2005;19:267–77. doi:10.1037/0894-4105.19.3.267.

    Article  PubMed  Google Scholar 

  4. Lejuez CW, Read JP, Kahler CW, Richards JB, Ramsey SE, Stuart GL, et al. Evaluation of a behavioral measure of risk taking: the Balloon Analogue Risk Task (BART). J Exp Psychol. 2002;8:75–84. doi:10.1037//1076-898x.8.2.75.

    CAS  Google Scholar 

  5. Brand M, Roth-Bauer M, Driessen M, Markowitsch HJ. Executive functions and risky decision-making in patients with opiate dependence. Drug Alcohol Depend. 2008;97:64–72. doi:10.1016/j.drugalcdep.2008.03.017.

    Article  PubMed  Google Scholar 

  6. Bechara A, Dolan S, Denburg N, Hindes A, Anderson SW, Nathan PE. Decision-making deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers. Neuropsychologia. 2001;39:376–89. doi:10.1016/s0028-3932(00)00136-6.

    Article  CAS  PubMed  Google Scholar 

  7. Campbell JA, Samartgis JR, Crowe SF. Impaired decision making on the Balloon Analogue Risk Task as a result of long-term alcohol use. J Clin Exp Neuropsychol. 2013;35:1071–81. doi:10.1080/13803395.2013.856382.

    Article  PubMed  Google Scholar 

  8. Olsen VV, Lugo RG, Sütterlin S. The somatic marker theory in the context of addiction: contributions to understanding development and maintenance. Psychol Res Behav Manag. 2015;8:187–200. doi:10.2147/PRBM.S68695.

    PubMed  PubMed Central  Google Scholar 

  9. Brevers D, Bechara A, Cleeremans A, Noël X. Iowa Gambling Task (IGT): twenty years after—gambling disorder and IGT. Front Psychol. 2013;4:665. doi:10.3389/fpsyg.2013.00665.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Field M, Christiansen P, Cole J, Goudie A. Delay discounting and the alcohol Stroop in heavy drinking adolescents. Addict. 2007;102:579–86. doi:10.1111/j.1360-0443.2007.01743.x.

    Article  Google Scholar 

  11. Goudriaan AE, Oosterlaan J, Beurs E, van den Brink W. Decision making in pathological gambling: a comparison between pathological gamblers, alcohol dependents, persons with Tourette syndrome, and normal controls. Cogn Brain Res. 2005;23:137–51. doi:10.1016/j.cogbrainres.2005.01.017.

    Article  Google Scholar 

  12. Brand M, Kalbe E, Labudda K, Fujiwara E, Kessler J, Markowitsch HJ. Decision-making impairments in patients with pathological gambling. Psychiatry Res. 2005;133:91–9. doi:10.1016/j.psychres.2004.10.003.

    Article  PubMed  Google Scholar 

  13. Reynolds B. A review of delay-discounting research with humans: relations to drug use and gambling. Behav Pharmacol. 2006;17:651–67. doi:10.1097/FBP.0b013e3280115f99.

    Article  PubMed  Google Scholar 

  14. Alessi SM, Petry NM. Pathological gambling severity is associated with impulsivity in a delay discounting procedure. Behav Process. 2003;64:345–54. doi:10.1016/S0376-6357(03)00150-5.

    Article  Google Scholar 

  15. Pawlikowski M, Brand M. Excessive Internet gaming and decision making: do excessive world of Warcraft-players have problems in decision making under risky conditions? Psychiatry Res. 2011;188:428–33. doi:10.1016/j.psychres.2011.05.017.

    Article  PubMed  Google Scholar 

  16. Sun D-L, Chen ZJ, Ma N, Zhang X-C, Fu X-M, Zhang DR. Decision-making and prepotent response inhibition functions in excessive Internet users. CNS Spectrums. 2009;14:75–81. doi:10.1017/S1092852900000225.

    Article  PubMed  Google Scholar 

  17. Goldstein RZ, Volkow ND. Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications. Nat Rev Neurosci. 2011;12:652–69. doi:10.1038/nrn3119.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. •• Volkow ND, Wang GJ, Fowler JS, Tomasi D. Addiction circuitry in the human brain. Annu Rev Pharmacol Toxicol. 2012;52:321–36. doi:10.1146/annurev-pharmtox-010611-134625. An overview of brain regions and brain processes associated with addiction. The authors relate brain processes with psychological mechanisms involved in the addiction process, such as conditioning, executive control, motivation, mood, stress, and self-awareness.

    Article  CAS  PubMed  Google Scholar 

  19. Everitt BJ, Robbins TW. Neural systems of reinforcement for drug addiction: from actions to habits to compulsion. Nat Neurosci. 2005;8:1481–9. doi:10.1038/nn1579.

    Article  CAS  PubMed  Google Scholar 

  20. •• Everitt BJ, Robbins TW. Drug addiction: updating actions to habits to compulsions ten years on. Annu Rev Psychol. 2016;67:23–50. doi:10.1146/annurev-psych-122414-033457. A recent reconsideration of the idea that development of substance-use disorders can be considered a transition from voluntary recreational drug use to compulsive drug-seeking. The original idea is refined with respect to the role of dorsal and ventral striatal mechanisms and the influence of Pavlovian conditioning on drug-associated stimuli

    Article  PubMed  Google Scholar 

  21. Redish A, Jensen S, Johnson A. Addiction as vulnerabilities in the decision process. Behav Brain Sci. 2008;31:461–70. doi:10.1017/S0140525X08004986.

    Article  Google Scholar 

  22. Berridge KC, Robinson TE, Aldridge JW. Dissecting components of reward: ‘liking’, ‘wanting’, and learning. Curr Opin Pharmacology. 2009;9:65–73. doi:10.1016/j.coph.2008.12.014.

    Article  CAS  Google Scholar 

  23. Robinson TE, Berridge KC. The neural basis of drug craving: an incentive-sensitization theory of addiction. Brain Res Brain Res Rev. 1993;18:247–91. doi:10.1016/0165-0173(93)90013-P.

    Article  CAS  PubMed  Google Scholar 

  24. Robinson TE, Berridge KC. The incentive sensitization theory of addiction: some current issues. Philosophical Transactions Royal Soc B. 2008;363:3137–46. doi:10.1098/rstb.2008.0093.

    Article  Google Scholar 

  25. Robinson TE, Berridge KC. Incentive-sensitization and addiction. Addict. 2001;96:103–14. doi:10.1080/09652140020016996.

    Article  CAS  Google Scholar 

  26. •• Dong G, Potenza MN. A cognitive-behavioral model of Internet gaming disorder: theoretical underpinnings and clinical implications. J Psychiatr Res. 2014;58:7–11. doi:10.1016/j.jpsychires.2014.07.005. To the best of our knowledge, this is the first theoretical model focussing on the mechanisms and treatment starting points for IGD after this condition has been added to the DSM-5. The model emphasizes the potential relationships between stress, reward sensation, executive control, and decision-making in the development and maintenance of IGD.

    Article  PubMed  PubMed Central  Google Scholar 

  27. •• Brand M, Young KS, Laier C, Wölfling K, Potenza MN. Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: an Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neurosci Biobehav Rev. 2016;71:252–66. doi:10.1016/j.neubiorev.2016.08.033. The authors suggest a theoretical model of the development and maintenance of specific Internet-use disorders, based on previous literature. The I-PACE model summarizes personal, affective, and cognitive mechanisms most likely involved in Internet-use disorders. Examples of the concepts involved are the following: biopsychological constitution, personality, psychopathology, motivation, Internet-related cognitions, coping, cue reactivity, craving, executive functions, and decision-making.

  28. D’Hondt F, Billieux J, Maurage P. Electrophysiological correlates of problematic internet use: critical review and perspectives for future research. Neurosci Biobehav Rev. 2015;59:64–82. doi:10.1016/j.neubiorev.2015.10.005.

    Article  PubMed  Google Scholar 

  29. Turel O, Qahri-Saremi H. Problematic use of social networking sites: antecedents and consequence from a dual system theory perspective. J Manag Inf Syst. in press; doi:10.1080/07421222.2016.1267529.

  30. Soror AA, Hammer BI, Steelman ZR, Davis FD, Limayem MM. Good habits gone bad: explaining negative consequences associated with the use of mobile phones from a dual-systems perspective. Inf Syst J. 2015;25:403–27. doi:10.1111/isj.12065.

    Article  Google Scholar 

  31. Brevers D, Noël X. Pathological gambling and the loss of willpower: a neurocognitive perspective. Socioaffect Neurosci. 2013;3:21592. doi:10.3402/snp.v3i0.21592.

    Google Scholar 

  32. Kaess M, Parzer P, Mehl L, Weil L, Strittmatter E, Resch F, et al. Stress vulnerability in male youth with Internet gaming disorder. Psychoneuroendocrinology. 2017;77:244–51. doi:10.1016/j.psyneuen.2017.01.008.

    Article  PubMed  Google Scholar 

  33. Reinecke L. Games and recovery—the use of video and computer games to recuperate from stress and strain. J Media Psychol. 2009;21:126–42. doi:10.1027/1864-1105.21.3.126.

    Article  Google Scholar 

  34. Weinstein A. Computer and video game addiction—a comparison between game users and non-game users. Am J Drug Alcohol Abuse. 2010;36:268–76. doi:10.3109/00952990.2010.491879.

    Article  PubMed  Google Scholar 

  35. •• Schiebener J, Brand M. Decision making under objective risk conditions—a review of cognitive and emotional correlates, strategies, feedback processing, and external influences. Neuropsychol Rev. 2015;25:171–98. doi:10.1007/s11065-015-9285-x. A review of the literature investigating the cognitive and emotional processes in decision-making under objective risk. Situational aspects (e.g., stress), attributes of the individual (e.g., impulsivity), and inner processes (e.g., reward-seeking and executive control processes) are considered as factors determining decision-making performance.

    Article  PubMed  Google Scholar 

  36. Green L, Myerson J. A discounting framework for choice with delayed and probabilistic rewards. Psychol Bull. 2004;130:769–92. doi:10.1037/0033-2909.130.5.769.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Levin IP, Hart SS. Risk preferences in young children: early evidence of individual differences in reaction to potential gains and losses. J Behav Decis Mak. 2003;16:397–413. doi:10.1002/bdm.453.

    Article  Google Scholar 

  38. Yao Y-W, Chen P-R, Chen C, Wang L-J, Zhang J-T, Xue G, et al. Failure to utilize feedback causes decision-making deficits among excessive Internet gamers. Psychiatry Res. 2014;219:583–8. doi:10.1016/j.psychres.2014.06.033.

    Article  PubMed  Google Scholar 

  39. Yao Y-W, Chen P-R, Li S, Wang L-J, Zhang J-T, Yip SW, et al. Decision-making for risky gains and losses among college students with Internet gaming disorder. PLoS One. 2015;10:e0116471. doi:10.1371/journal.pone.0116471.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Chen SHWL, Weng L, Su Y, Wu H, Yang P. Development of a Chinese Internet addiction scale and its psychometric study. Chin J Psychol. 2003;45:279.

    Google Scholar 

  41. • Yao Y-W, Wang L-J, Yip SW, Chen PR, Li S, Xu J, et al. Impaired decision-making under risk is associated with gaming-specific inhibition deficits among college students with Internet gaming disorder. Psychiatry Res. 2015;229:302–9. doi:10.1016/j.psychres.2015.07.004. The study uses a Go/No-Go Task with gaming-related and neutral pictures as well as decision-making tasks. The findings that individuals with IGD symptoms show inhibition deficits when gaming-related stimuli are presented and the finding that this was associated with decision-making deficits are helpful for understanding potential neurocognitive deficits in IGD.

    Article  PubMed  Google Scholar 

  42. • Dong G, Potenza MN. Risk-taking and risky decision-making in Internet gaming disorder: implications regarding online gaming in the setting of negative consequences. J Psychiatr Res. 2016;73:1–8. doi:10.1016/j.jpsychires.2015.11.011. Patients with IGD diagnosis were carefully chosen for this fMRI study. The brain-behavior relationships discovered in this study are very helpful for understanding the role of executive control for hasty and risky decision-making in IGD.

    Article  PubMed  Google Scholar 

  43. Wang L, Wu L, Lin X, Zhang Y, Zhou H, Du X, et al. Dysfunctional default mode network and executive control network in people with Internet gaming disorder: independent component analysis under a probability discounting task. Eur Psychiatry. 2016;34:36–42. doi:10.1016/j.eurpsy.2016.01.2424.

    Article  CAS  PubMed  Google Scholar 

  44. • Wang Y, Wu L, Wang L, Zhang Y, Du X, Dong G. Impaired decision-making and impulse control in Internet gaming addicts: evidence from the comparison with recreational Internet game users. Addict Biol. in press. doi:10.1111/adb.12458. The authors compared decision-making performance of recreational video gamers and video gamers with symptoms of IGD at the behavioral and brain levels.

  45. Bechara A, Damasio AR, Damasio H, Anderson SW. Insensitivity to future consequences following damage to human prefrontal cortex. Cognition. 1994;50:7–15. doi:10.1016/0010-0277(94)90018-3.

    Article  CAS  PubMed  Google Scholar 

  46. Nikolaidou M, Fraser DS, Hinvest N. Physiological markers of biased decision-making in problematic Internet users. J Behav Addict. 2016;5:510–7. doi:10.1556/2006.5.2016.052.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Dunn BD, Dalgleish T, Lawrence AD. The somatic marker hypothesis: a critical evaluation. Neurosci Biobehav Rev. 2006;30:239–71. doi:10.1016/j.neubiorev.2005.07.001.

    Article  PubMed  Google Scholar 

  48. Billieux J, Gay P, Rochat L, Van der Linden M. The role of urgency and its underlying psychological mechanisms in problematic behaviours. Behav Res Ther. 2010;48:1085–96. doi:10.1016/j.brat.2010.07.008.

    Article  PubMed  Google Scholar 

  49. Brand M, Recknor EC, Grabenhorst F, Bechara A. Decisions under ambiguity and decisions under risk: correlations with executive functions and comparisons of two different gambling tasks with implicit and explicit rules. J Clin Exp Neuropsychol. 2007;29:86–99. doi:10.1080/13803390500507196.

    Article  PubMed  Google Scholar 

  50. Laier C, Pawlikowski M, Brand M. Sexual picture processing interferes with decision-making under ambiguity. Arch Sex Behav. 2014;43:473–82. doi:10.1007/s10508-013-0119-8.

    Article  PubMed  Google Scholar 

  51. Brand M, Laier C, Pawlikowski M, Schächtle U, Schöler T, Altstötter-Gleich C. Watching pornographic pictures on the Internet: role of sexual arousal ratings and psychological-psychiatric symptoms for using Internet sex sites excessively. Cyberpsychol Behav Soc Netw. 2011;14:371–7. doi:10.1089/cyber.2010.0222.

    Article  PubMed  Google Scholar 

  52. Laier C, Pawlikowski M, Pekal J, Schulte FP, Brand M. Cybersex addiction: experienced sexual arousal when watching pornography and not real-life sexual contacts makes the difference. J Behav Addict. 2013;2:100–7. doi:10.1556/JBA.2.2013.002.

    Article  PubMed  Google Scholar 

  53. Qi X, Du X, Yang Y, Du G, Gao P, Zhang Y, et al. Decreased modulation by the risk level on the brain activation during decision making in adolescents with internet gaming disorder. Front Behav Neurosci. 2015;9 doi:10.3389/fnbeh.2015.00296.

  54. Weinstein A, Abu HB, Timor A, Mama Y. Delay discounting, risk-taking, and rejection sensitivity among individuals with Internet and video gaming disorders. J Behav Addict. 2016;5:674–82. doi:10.1556/2006.5.2016.081.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Eisenegger C, Knoch D, Ebstein RP, Gianotti LR, Sandor PS, Fehr E. Dopamine receptor D4 polymorphism predicts the effect of L-DOPA on gambling behavior. Biol Psychiatry. 2010;67:702–6. doi:10.1016/j.biopsych.2009.09.021.

    Article  CAS  PubMed  Google Scholar 

  56. Sariyska R, Lachmann B, Markett S, Reuter M, Montag C. Individual differences in implicit learning abilities and impulsive behavior in the context of Internet addiction and Internet gaming disorder under the consideration of gender. Addict Behav Rep. in press; doi:10.1016/j.abrep.2017.02.002.

  57. Pawlikowski M, Altstötter-Gleich C, Brand M. Validation and psychometric properties of a short version of Young’s Internet addiction test. Computers Hum Behav. 2013;29:1212–23. doi:10.1016/j.chb.2012.10.014.

    Article  Google Scholar 

  58. Dong G, Hu Y, Lin X, Lu Q. What makes Internet addicts continue playing online even when faced by severe negative consequences? Possible explanations from an fMRI study. Biol Psychol. 2013;94:282–9. doi:10.1016/j.biopsycho.2013.07.009.

    Article  PubMed  Google Scholar 

  59. Wang Y, Wu L, Zhou H, Lin X, Zhang Y, Du X, et al. Impaired executive control and reward circuit in Internet gaming addicts under a delay discounting task: independent component analysis. Eur Arch Psychiatry Clin Neurosci. in press; doi:10.1007/s00406-016-0721-6.

  60. Li H, Jin S, Guo Y. How do construal levels affect the intertemporal choices of Internet addicts? Computers Hum Behav. 2016;60:173–8. doi:10.1016/j.chb.2016.02.016.

    Article  Google Scholar 

  61. Zhou Z, Yuan G, Yao J. Cognitive biases toward Internet game-related pictures and executive deficits in individuals with an Internet game addiction. PLoS One. 2012;7:e48961. doi:10.1371/journal.pone.0048961.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Schiebener J, Laier C, Brand M. Getting stuck with pornography? Overuse or neglect of cybersex cues in a multitasking situation is related to symptoms of cybersex addiction. J Behav Addict. 2015;4:14–21. doi:10.1556/JBA.4.2015.1.5.

    Article  PubMed  PubMed Central  Google Scholar 

  63. •• Kardefelt-Winther D, Heeren A, Schimmenti A, van Rooij A, Maurage P, Carras M, et al. How can we conceptualize behavioural addiction without pathologizing common behaviours? Addict. 2017; doi:10.1111/add.13763. The threat of overpathologizing common behaviors as behavioral addictions is discussed. The authors propose an operational definition as well as exclusion criteria which help to avoid the problem of overpathologizing of everyday behaviors.

  64. •• Billieux J, Schimmenti A, Khazaal Y, Maurage P, Heeren A. Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research. J Behav Addict. 2015;4:119–23. doi:10.1556/2006.4.2015.009. The article uses single-case examples and historical views on behavioral addictions to vividly point out the threat of overpathologizing common behaviors as behavioral addictions. Suggestions for future research are made and the importance of psychological research in the field is highlighted.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Matthias Brand.

Ethics declarations

Conflict of Interest

Dr. Johannes Schiebener and Prof. Dr. Matthias Brand declare that they have no conflicts of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

This article is part of the Topical Collection on Technology Addiction

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schiebener, J., Brand, M. Decision-making and Related Processes in Internet Gaming Disorder and Other Types of Internet-Use Disorders. Curr Addict Rep 4, 262–271 (2017). https://doi.org/10.1007/s40429-017-0156-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40429-017-0156-9

Keywords

Navigation