Introducing the Fling – An Innovative Serious Game to Train Behavioral Control in Adolescents: Protocol of a Randomized Controlled Trial

  • Wouter J. Boendermaker
  • Remco Veltkamp
  • Robbert Jan Beun
  • Rens van de Schoot
  • Margot Peeters
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10056)

Abstract

Behavioral control weaknesses are a strong predictor of problematic behaviors in adolescents, such as heavy alcohol use. Heavy alcohol use at this young age can lead to health and school-related problems and is a severe societal problem. Strengthening of cognitive control mechanisms through computerized training has been shown to have positive effects on behavior, but is often perceived as a tedious exercise. Applying novel serious gaming techniques to evidence-based training paradigms may offer a solution to this motivational problem. This paper describes the design and analysis plan that will be used to evaluate an innovative Serious Game called The Fling, aimed specifically at increasing cognitive control over impulses in adolescents. The game will be evaluated in a randomized controlled trial (RCT) among adolescents between 15–18 years in mainstream and special education.

Keywords

Serious games Cognitive training Adolescents Motivation Inhibition 

Notes

Acknowledgments

The authors wish to thank our collaborators at Shosho Amsterdam, Harold de Groot and Frank van Vugt in particular, for their invaluable contributions to the game’s design and development. This research was supported by the Utrecht University Strategic Theme Dynamics of Youth grant #SM.DoY.2015.6.T, awarded to Margot Peeters.

References

  1. 1.
    Steinberg, L.: Risk taking in adolescence new perspectives from brain and behavioral science. Curr. Dir. Psychol. 16, 55–59 (2007). doi:10.1111/j.1467-8721.2007.00475.x CrossRefGoogle Scholar
  2. 2.
    Peeters, M., Janssen, T., Monshouwer, K., Boendermaker, W., Pronk, T., Wiers, R., Vollebergh, W.: Weaknesses in executive functioning predict the initiating of adolescents’ alcohol use. Dev. Cogn. Neurosci. 16, 139–146 (2015). doi:10.1016/j.dcn.2015.04.003 CrossRefGoogle Scholar
  3. 3.
    Fernie, G., Peeters, M., Gullo, M.J., Christiansen, P., Cole, J.C., Sumnall, H., Field, M.: Multiple behavioural impulsivity tasks predict prospective alcohol involvement in adolescents. Addiction 108, 1916–1923 (2013). doi:10.1111/add.12283 CrossRefGoogle Scholar
  4. 4.
    Nigg, J.T., Wong, M.M., Martel, M.M., Jester, J.M., Puttler, L.I., Glass, J.M., Adams, K.M., Fitzgerald, H.E., Zucker, R.A.: Poor response inhibition as a predictor of problem drinking and illicit drug use in adolescents at risk for alcoholism and other substance use disorders. J. Am. Acad. Child Adolesc. Psychiatry 45(4), 468–475 (2006). doi:10.1097/01.chi.0000199028.76452.a9 CrossRefGoogle Scholar
  5. 5.
    Khurana, A., Romer, D., Betancourt, L.M., Brodsky, N.L., Giannetta, J.M., Hurt, H.: Working memory ability predicts trajectories of early alcohol use in adolescents: the mediational role of impulsivity. Addiction 108, 506–515 (2013). doi:10.1111/add.12001 CrossRefGoogle Scholar
  6. 6.
    Crone, E.A., Dahl, R.E.: Understanding adolescence as a period of social-affective engagement and goal flexibility. Nat. Rev. Neurosci. 13, 636–650 (2012). doi:10.1038/nrn3313 CrossRefGoogle Scholar
  7. 7.
    Houben, K., Nederkoorn, C., Wiers, R.W., Jansen, A.: Resisting temptation: decreasing alcohol-related affect and drinking behavior by training response inhibition. Drug Alcohol Depend. 116, 132–136 (2011). doi:10.1016/j.drugalcdep.2010.12.011 CrossRefGoogle Scholar
  8. 8.
    Houben, K., Wiers, R.W., Jansen, A.: Getting a grip on drinking behavior: training working memory to reduce alcohol abuse. Psychol. Sci. 22, 968–975 (2011). doi:10.1177/0956797611412392 CrossRefGoogle Scholar
  9. 9.
    Beard, C., Weisberg, R.B., Primack, J.: Socially anxious primary care patients’ attitudes toward cognitive bias modification (CBM): a qualitative study. Behav. Cogn. Psychother. 40, 618–633 (2012). doi:10.1017/S1352465811000671 CrossRefGoogle Scholar
  10. 10.
    Dovis, S., van der Oord, S., Wiers, R.W., Prins, P.J.M.: What part of working memory is not working in ADHD? Short-term memory, the central executive and effects of reinforcement. J. Abnorm. Child Psychol. 41, 901–917 (2013). doi:10.1007/s10802-013-9729-9 CrossRefGoogle Scholar
  11. 11.
    Granic, I., Lobel, A., Engels, R.C.: The benefits of playing video games. Am. Psychol. 69, 66–78 (2014). doi:10.1037/a0034857 CrossRefGoogle Scholar
  12. 12.
    Boendermaker, W.J., Prins, P.J.M., Wiers, R.W.: Cognitive bias modification for adolescents with substance use problems – can serious games help? J. Behav. Ther. Exp. Psychiatry 49, 13–20 (2015). doi:10.1016/j.jbtep.2015.03.008 CrossRefGoogle Scholar
  13. 13.
    Prins, P.J.M., Dovis, S., Ponsioen, A., Ten Brink, E., Van der Oord, S.: Does computerized working memory training with game elements enhance motivation and training efficacy in children with ADHD? Cyberpsychol. Behav. Soc. Netw. 14, 115–122 (2011). doi:10.1089/cyber.2009.0206 CrossRefGoogle Scholar
  14. 14.
    Antrop, I., Stock, P., Verté, S., Wiersema, J.R., Baeyens, D., Roeyers, H.: ADHD and delay aversion: the influence of non-temporal stimulation on choice for delayed rewards. J. Child Psychol. Psychiatry 47, 1152–1158 (2006). doi:10.1111/j.1469-7610.2006.01619.x CrossRefGoogle Scholar
  15. 15.
    Bickel, W.K., Yi, R., Landes, R.D., Hill, P.F., Baxter, C.: Remember the future: working memory training decreases delay discounting among stimulant addicts. Biol. Psychiatry 69, 260–265 (2011). doi:10.1016/j.biopsych.2010.08.017 CrossRefGoogle Scholar
  16. 16.
    Jones, A., Field, M.: The effects of cue-specific inhibition training on alcohol consumption in heavy social drinkers. Exp. Clin. Psychopharmacol. 21, 8–16 (2013). doi:10.1037/a0030683 CrossRefGoogle Scholar
  17. 17.
    Verbruggen, F., Logan, G.D.: Automatic and controlled response inhibition: associative learning in the Go/No-Go and stop-signal paradigms. J. Exp. Psychol. Gen. 137, 649–672 (2008). doi:10.1037/a0013170 CrossRefGoogle Scholar
  18. 18.
    Logan, G.D., Cowan, W.B.: On the ability to inhibit thought and action: a theory of an act of control. Psychol. Rev. 91, 295–327 (1984). doi:10.1037/0033-295X.91.3.295 CrossRefGoogle Scholar
  19. 19.
    Verbruggen, F., Adams, R., Chambers, C.D.: Proactive motor control reduces monetary risk taking in gambling. Psychol. Sci. 23, 805–815 (2012). doi:10.1177/0956797611434538 CrossRefGoogle Scholar
  20. 20.
    Dovis, S., van der Oord, S., Wiers, R.W., Prins, P.J.M.: Improving executive functioning in children with ADHD: training multiple executive functions within the context of a computer game. A randomized double-blind placebo controlled trial. PLoS ONE 10(4), e0121651 (2015). doi:10.1371/journal.pone.0121651 CrossRefGoogle Scholar
  21. 21.
    Rubia, K., Smith, A.B., Brammer, M.J., Taylor, E.: Right inferior prefrontal cortex mediates response inhibition while mesial prefrontal cortex is responsible for error detection. Neuroimage 20, 351–358 (2003). PMID:14527595CrossRefGoogle Scholar
  22. 22.
    Spierer, L., Chavan, C.F., Manuel, A.L.: Training-induced behavioral and brain plasticity in inhibitory control. Front. Hum. Neurosci. 7, 427 (2013). doi:10.3389/fnhum.2013.00427 CrossRefGoogle Scholar
  23. 23.
    Blakemore, S.J., Choudhury, S.: Development of the adolescent brain: implications for executive function and social cognition. J. Child Psychol. Psychiatry 47, 296–312 (2006). doi:10.1111/j.1469-7610.2006.01611.x CrossRefGoogle Scholar
  24. 24.
    Luna, B., Garver, K.E., Urban, T.A., Lazar, N.A., Sweeney, J.A.: Maturation of cognitive processes from late childhood to adulthood. Child Dev. 75, 1357–1372 (2004). doi:10.1111/j.1467-8624.2004.00745.x CrossRefGoogle Scholar
  25. 25.
    Veling, H., Aarts, H.: Unintentional preparation of motor impulses after incidental perception of need-rewarding objects. Cogn. Emot. 25, 1131–1138 (2011). doi:10.1080/02699931.2010.524053 CrossRefGoogle Scholar
  26. 26.
    Veling, H., Holland, R.W., van Knippenberg, A.: When approach motivation and behavioral inhibition collide: behavior regulation through stimulus devaluation. J. Exp. Soc. Psychol. 44, 1013–1019 (2008). doi:10.1016/j.jesp.2008.03.004 CrossRefGoogle Scholar
  27. 27.
    Kepper, A., van den Eijnden, R., Monshouwer, K., Vollebergh, W.: Understanding the elevated risk of substance use by adolescents in special education and residential youth care: the role of individual, family and peer factors. Eur. Child Adolesc. Psychiatry 23(6), 461–472 (2014). doi:10.1007/s00787-013-0471-1 Google Scholar
  28. 28.
    van de Schoot, R., Hoijtink, H.J.A., Dekovic, M.: Testing inequality constrained hypotheses in SEM models. Struct. Equ. Modeling 17, 443–463 (2010). doi:10.1080/10705511.2010.489010 MathSciNetCrossRefGoogle Scholar
  29. 29.
    Vanbrabant, L., Van De Schoot, R., Rosseel, Y.: Constrained statistical inference: sample-size tables for ANOVA and regression. Front. Psychol. 5, 1–7 (2015). doi:10.3389/fpsyg.2014.01565 CrossRefGoogle Scholar
  30. 30.
    Peeters, M., Monshouwer, K., van de Schoot, R., Janssen, T., Vollebergh, W.A.M., Wiers, R.W.: Automatic processes and the drinking behavior in early adolescence: a prospective study. Alcohol. Clin. Exp. Res. 37(10), 1737–1744 (2013). doi:10.1111/acer.12156 Google Scholar
  31. 31.
    Peeters, M., Wiers, R.W., Monshouwer, K., Van de Schoot, R., Janssen, T., Vollebergh, W.A.M.: Automatic processes in at-risk adolescents: the role of alcohol-approach tendencies and response inhibition in drinking behavior. Addiction 107, 1939–1946 (2012). doi:10.1111/j.1360-0443.2012.03948.x CrossRefGoogle Scholar
  32. 32.
    Tangney, J.P., Baumeister, R.F., Boone, A.L.: High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. J. Pers. 72, 271–324 (2004). PMID:15016066CrossRefGoogle Scholar
  33. 33.
    Hinson, J.M., Jameson, T.L., Whitney, P.: Impulsive decision making and working memory. J. Exp. Psychol. Learn. Mem. Cogn. 29(2), 298–306 (2003). PMID:12696817CrossRefGoogle Scholar
  34. 34.
    Petrides, M., Milner, B.: Deficits on subject-ordered tasks after frontal-and temporal-lobe lesions in man. Neuropsychologia 20, 249–262 (1982). PMID:7121793CrossRefGoogle Scholar
  35. 35.
    Boendermaker, W.J., Sanchez Maceiras, S., Boffo, M., Wiers, R.W.: Attentional bias modification with serious game elements: evaluating the shots game. J. Med. Internet Res.: Serious Games (in press)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Wouter J. Boendermaker
    • 1
  • Remco Veltkamp
    • 2
  • Robbert Jan Beun
    • 2
  • Rens van de Schoot
    • 3
  • Margot Peeters
    • 1
  1. 1.Department of Interdisciplinary Social SciencesUtrecht UniversityUtrechtThe Netherlands
  2. 2.Department of Information and Computing SciencesUtrecht UniversityUtrechtThe Netherlands
  3. 3.Department of Social Sciences: Methodology and StatisticsUtrecht UniversityUtrechtThe Netherlands

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