Journal of Cognitive Enhancement

, Volume 3, Issue 1, pp 64–84 | Cite as

The Impact of Game-Based Task-Shifting Training on Motivation and Executive Control in Children with ADHD

  • Sandra DörrenbächerEmail author
  • Jutta Kray
Original Article


Children diagnosed with ADHD show pronounced impairments in both “cold” executive and “hot” motivational control. Importantly, recent cognitive training studies suggested that practice in shifting between competing tasks in alternating runs can promote executive control functioning in ADHD children and may especially in a motivationally enriched training setting, such as by adding video game elements. The aim of the present study was to examine how a game-based training environment influences motivational variables, such as training willingness (i.e., voluntary motivation) and behavioral inappropriateness (i.e., involuntary drive), as well as executive control during a cognitive training invention (a task-shifting training) in children with ADHD. Therefore, children diagnosed with the ADHD combined subtype were trained in either a low-(LowMot) or a high-motivational (HighMot) training setting. Results revealed that the HighMot-setting compared to the LowMot-setting (1) led to higher voluntary motivational control, but also to more behavioral inappropriateness and (2) did in turn not enable larger performance improvements in task shifting. The lacking incremental benefit from a HighMot training setting on cognitive performance will be discussed in the light of notions on an adequate arousal-performance relationship. Based on these findings, directions for future training interventions in ADHD children will be discussed.


ADHD children Task-shifting training Game setting Motivation Executive control 



The authors would like to thank Philipp Matthias Müller and Johannes Tröger for their support in conceiving the research design and implementing the video game environment. The authors would further thank Sophie Ehrlicher, Benjamin Ersch, Therese Fredenhagen, Lena Grüneisen, Myriam Pukallus, Marina Raupach, Jessica Scheiwen, Anna Schramek, Daniel Schwarm, Britta Loew, and Linda Sommerfeld for their valuable help and assistance with data collection. Importantly, the authors would thank the SHG clinics Merzig, St. Wendel, Kleinblittersdorf, and Schönbach (Saarland Heilstätten GmbH) for the good cooperation and support (special thanks to Prof. Dr. Eva Möhler, Dr. Janosch Haußmann, Stephan Schmitt-Dier, Anette Brausch, Ansaf Ewaiwi, Fabian Justinger, Anna Lisa Lermen, Volker Scheid, Gabriele Schönau, and all other voluntary helpers).

Author Contributions

Sandra Dörrenbächer carried out the statistical analyses and interpretations and contributed the most to the writing of the paper. Jutta Kray was the principal investigator, provided substantial support in proofreading the manuscript, and gave the final approval of the version to be published. Intellectual content was collectively revised by all authors. All authors read and approved the final manuscript.

Funding Information

This work was funded by the German Research Foundation under Grant DFG-IRTG-1457.

Compliance with Ethical Standards

For all children, written informed consent from one of their parents was warranted in accordance with the protocols approved by the local ethics committee at Saarland University.

Conflict of Interest

The authors declare that they have no conflict of interest.

Supplementary material

41465_2018_83_MOESM1_ESM.docx (58 kb)
ESM 1 (DOCX 58 kb)


  1. Audiffren, M. (2009). Acute exercise and psychological functions: a cognitive-energetic approach. Exercise and Cognitive Function, 1–39.Google Scholar
  2. Bellgrove, M. A., Hawi, Z., Kirley, A., Gill, M., & Robertson, I. H. (2005). Dissecting the attention deficit hyperactivity disorder (ADHD) phenotype: sustained attention, response variability and spatial attentional asymmetries in relation to dopamine transporter (DAT1) genotype. Neuropsychologia, 43(13), 1847–1857.Google Scholar
  3. Bioulac, S., Lallemand, S., Fabrigoule, C., Thoumy, A.-L., Philip, P., & Bouvard, M. P. (2014). Video game performances are preserved in ADHD children compared with controls. Journal of Attention Disorders, 18(6), 542–550. Scholar
  4. Braver, T. (2016). Motivation and cognitive control. UK: Routledge Taylor & Francis Group.Google Scholar
  5. Cepeda, N. J., Cepeda, M. L., & Kramer, A. F. (2000). Task switching and attention deficit hyperactivity disorder. Journal of Abnormal Child Psychology, 28(3), 213–226.Google Scholar
  6. Coghill, D. R., Seth, S., & Matthews, K. (2014). A comprehensive assessment of memory, delay aversion, timing, inhibition, decision making and variability in attention deficit hyperactivity disorder: advancing beyond the three-pathway models. Psychological Medicine, 44(9), 1989–2001.Google Scholar
  7. Cragg, L., & Chevalier, N. (2012). The processes underlying flexibility in childhood. The Quarterly Journal of Experimental Psychology, 65(2), 209–232.Google Scholar
  8. Demurie, E., Roeyers, H., Baeyens, D., & Sonuga-Barke, E. (2012). Temporal discounting of monetary rewards in children and adolescents with ADHD and autism spectrum disorders. Developmental Science, 15(6), 791–800.Google Scholar
  9. Deveau, J., Jaeggi, S. M., Zordan, V., Phung, C., & Seitz, A. R. (2015). How to build better memory training games. Frontiers in Systems Neuroscience, 8, 243.Google Scholar
  10. Döpfner, M., & Lehmkuhl, G. (2003). Diagnostik-System für psychische Störungen im Kindes-und Jugendalter nach ICD-10 und DSM-IV (DISYPS-KJ). Praxis der Kinderpsychologie und Kinderpsychiatrie, 46, 519–547.Google Scholar
  11. Dörrenbächer, S., Müller, P. M., Tröger, J., & Kray, J. (2014). Dissociable effects of game elements on motivation and cognition in a task-switching training in middle childhood. Frontiers in Psychology, 5, 1275.Google Scholar
  12. Dovis, S., Van der Oord, S., Wiers, R. W., & Prins, P. J. (2012). Can motivation normalize working memory and task persistence in children with attention-deficit/hyperactivity disorder? The effects of money and computer-gaming. Journal of Abnormal Child Psychology, 40(5), 669–681.Google Scholar
  13. Dovis, S., Van der Oord, S., Wiers, R. W., & Prins, P. J. (2015). ADHD subtype differences in reinforcement sensitivity and visuospatial working memory. Journal of Clinical Child & Adolescent Psychology, 44(5), 859–874.Google Scholar
  14. Egeland, J., Ueland, T., & Johansen, S. (2012). Central processing energetic factors mediate impaired motor control in ADHD combined subtype but not in ADHD inattentive subtype. Journal of Learning Disabilities, 45(4), 361–370.Google Scholar
  15. Epstein, J. N., Langberg, J. M., Rosen, P. J., Graham, A., Narad, M. E., Antonini, T. N., et al. (2011). Evidence for higher reaction time variability for children with ADHD on a range of cognitive tasks including reward and event rate manipulations. Neuropsychology, 25(4), 427–441.Google Scholar
  16. Fröhlich, T. E., Lanphear, B. P., Epstein, J. N., Barbaresi, W. J., Katusic, S. K., & Kahn, R. S. (2007). Prevalence, recognition, and treatment of attention-deficit/hyperactivity disorder in a national sample of US children. Archives of Pediatrics & Adolescent Medicine, 161(9), 857–864.Google Scholar
  17. Gade, M., Schuch, S., Druey, M. D., & Koch, I. (2014). Inhibitory control in task switching. In J. Grange & G. Houghton (Eds.), Task switching and cognitive control (pp. 137–159). Oxford: Oxford University Press.Google Scholar
  18. Goldin, A., Hermida, M., Shalom, D., Costa, M., Lopez-Rosenfeld, M., Segretin, M., et al. (2014). Far transfer to language and math of a short software-based gaming intervention. Proceedings of the National Academy of Sciences, 111(17), 6443–6448.Google Scholar
  19. Haenlein, M., & Caul, W. (1987). Attention deficit disorder with hyperactivity: a specific hypothesis of reward dysfunction. Journal of the American Academy of Child & Adolescent Psychiatry, 26(3), 356–362.Google Scholar
  20. Hager, W., Patry, J. L., & Brezing, H. (2000). Evaluation psychologischer Evaluationsmaßnahmen. Standards und Kriterien. Ein Handbuch. Bern: Huber.Google Scholar
  21. Hawkins, G. E., Rae, B., Nesbitt, K. V., & Brown, S. D. (2013). Gamelike features might not improve data. Behavior Research Methods, 45(2), 301–318.Google Scholar
  22. Hockey, G. R. J. (1993). Cognitive-energetical control mechanisms in the management of work demands and psychological health. In A. D. Baddeley & L. Weiskrantz (Eds.), Attention: selection, awareness, and control: a tribute to Donald Broadbent (pp. 328–345). New York: Clarendon Press/Oxford University Press.Google Scholar
  23. Hovik, K. T., Saunes, B. K., Aarlien, A. K., & Egeland, J. (2013). RCT of working memory training in ADHD: long-term near-transfer effects. PLoS One, 8(12), e80561.Google Scholar
  24. Hughes, M. M., Linck, J. A., Bowles, A. R., Koeth, J. T., & Bunting, M. F. (2014). Alternatives to switch-cost scoring in the task-switching paradigm: their reliability and increased validity. Behavior Research Methods, 46(3), 702–721.Google Scholar
  25. Humphreys, M. S., & Revelle, W. (1984). Personality, motivation, and performance: a theory of the relationship between individual differences and information processing. Psychological Review, 91(2), 153–184.Google Scholar
  26. Jarmasz, J., & Hollands, J. G. (2009). Confidence intervals in repeated-measures designs: the number of observations principle. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale, 63(2), 124. Scholar
  27. Jeffreys, H. (1961). Theory of probability. Oxford: Oxford University Press.Google Scholar
  28. Kahneman, D. (1973). Attention and effort (Vol. 1063). Englewood Cliffs: Prentice-Hall.Google Scholar
  29. Karbach, J., & Kray, J. (2009). How useful is executive control training? Age differences in near and far transfer of task-switching training. Developmental Science, 12(6), 978–990.Google Scholar
  30. Katz, B., Jaeggi, S., Buschkuehl, M., Stegman, A., & Shah, P. (2014). Differential effect of motivational features on training improvements in school-based cognitive training. Frontiers in Human Neuroscience, 8, 242.Google Scholar
  31. Kiesel, A., Steinhauser, M., Wendt, M., Falkenstein, M., Jost, K., Philipp, A. M., & Koch, I. (2010). Control and interference in task switching—a review. Psychological Bulletin, 136(5), 849–874.Google Scholar
  32. Kleinsorge, T., & Rinkenauer, G. (2012). Effects of monetary incentives on task switching. Experimental Psychology, 59(4), 216–226.Google Scholar
  33. Klingberg, T., Fernell, E., Olesen, P. J., Johnson, M., Gustafsson, P., Dahlström, K., et al. (2005). Computerized training of working memory in children with ADHD—a randomized, controlled trial. Journal of the American Academy of Child & Adolescent Psychiatry, 44(2), 177–186.Google Scholar
  34. Kofler, M., Rapport, M., Sarver, D., Raiker, J., Orban, S., Friedman, L., & Kolomeyer, E. (2013). Reaction time variability in ADHD: a meta-analytic review of 319 studies. Clinical Psychology Review, 33(6), 795–811.Google Scholar
  35. Kouneiher, F., Charron, S., & Koechlin, E. (2009). Motivation and cognitive control in the human prefrontal cortex. Nature Neuroscience, 12(7), 939–945.Google Scholar
  36. Kramer, A. F., Cepeda, N. J., & Cepeda, M. L. (2001). Methylphenidate effects on task-switching performance in attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 40(11), 1277–1284.Google Scholar
  37. Kray, J., Karbach, J., Haenig, S., & Freitag, C. (2012). Can task-switching training enhance executive control functioning in children with attention deficit/-hyperactivity disorder? Frontiers in Human Neuroscience, 5, 180.Google Scholar
  38. Leung, P., & Connolly, K. (1994). Attentional difficulties in hyperactive and conduct-disordered children: a processing deficit. Journal of Child Psychology and Psychiatry, 35(7), 1229–1245.Google Scholar
  39. Love, J., Selker, R., Marsman, M., Jamil, T., Dropmann, D., Verhagen, A., & Wagenmakers, E. (2015). JASP (version 0.7) [computer software]. Amsterdam, the netherlands: Jasp project.Google Scholar
  40. Luman, M., Oosterlaan, J., Hyde, C., Van Meel, C. S., & Sergeant, J. A. (2007). Heart rate and reinforcement sensitivity in ADHD. Journal of Child Psychology and Psychiatry, 48(9), 890–898.Google Scholar
  41. Morey, R., & Rouder, J. (2015). BayesFactor: computation of Bayes factors for common designs (R package version 0.9. 11-1) [computer software manual].Google Scholar
  42. Mulder, M. J., Bos, D., Weusten, J. M., van Belle, J., van Dijk, S. C., Simen, P., et al. (2010). Basic impairments in regulating the speed-accuracy tradeoff predict symptoms of attention-deficit/hyperactivity disorder. Biological Psychiatry, 68(12), 1114–1119. Scholar
  43. Nieuwenhuis, S., & Monsell, S. (2002). Residual costs in task switching: testing the failure-to-engage hypothesis. Psychonomic Bulletin & Review, 9(1), 86–92.Google Scholar
  44. Peirce, J. W. (2008). Generating stimuli for neuroscience using PsychoPy. Frontiers in Neuroinformatics, 2.Google Scholar
  45. Pessoa, L. (2009). How do emotion and motivation direct executive control? Trends in Cognitive Sciences, 13(4), 160–166.Google Scholar
  46. Petrescu-Ghenea, C., Trutesco, C., Mihailescu, I., Kobylinska, L., & Rad, F. (2013). Arousal modulation in ADHD. Romanian Journal of Child and Adolescent Psychiatry, 1(1), 1–3.Google Scholar
  47. Pribram, K., & McGuinness, D. (1975). Arousal, activation, and effort in the control of attention. Psychological Review, 82(2), 116–149.Google Scholar
  48. Prins, P. J., Dovis, S., Ponsioen, A., Ten Brink, E., & Van der Oord, S. (2011). Does computerized working memory training with game elements enhance motivation and training efficacy in children with ADHD? Cyberpsychology, Behavior, and Social Networking, 14(3), 115–122.Google Scholar
  49. Prins, P. J., Ten Brink, E., Dovis, S., Ponsioen, A., Geurts, H. M., De Vries, M., & Van Der Oord, S. (2013). “Braingame Brian”: toward an executive function training program with game elements for children with ADHD and cognitive control problems. GAMES FOR HEALTH: Research, Development, and Clinical Applications, 2(1), 44–49.Google Scholar
  50. Rapport, M. D., Orban, S. A., Kofler, M. J., & Friedman, L. M. (2013). Do programs designed to train working memory, other executive functions, and attention benefit children with ADHD? A meta-analytic review of cognitive, academic, and behavioral outcomes. Clinical Psychology Review, 33(8), 1237–1252.Google Scholar
  51. Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5), 356–374.Google Scholar
  52. Ryan, R. M., Rigby, C. S., & Przybylski, A. (2006). The motivational pull of video games: a self-determination theory approach. Motivation and Emotion, 30(4), 344–360.Google Scholar
  53. Sanders, A. F. (1981). Stress and human performance: a working model and some applications. Machine Pacing and Occupational Stress, 57–64.Google Scholar
  54. Sanders, A. (1983). Towards a model of stress and human performance. Acta Psychologica, 53(1), 61–97.Google Scholar
  55. Sarter, M., Gehring, W., & Kozak, R. (2006). More attention must be paid: the neurobiology of attentional effort. Brain Research Reviews, 51(2), 145–160.Google Scholar
  56. Scheres, A., Oosterlaan, J., & Sergeant, J. (2001). Response execution and inhibition in children with AD/HD and other disruptive disorders: the role of behavioural activation. The Journal of Child Psychology and Psychiatry and Allied Disciplines, 42(3), 347–357.Google Scholar
  57. Schupp, H. T., Flaisch, T., Stockburger, J., & Junghöfer, M. (2006). Emotion and attention: event-related brain potential studies. Progress in Brain Research, 156, 31–51. Scholar
  58. Sergeant, J. A., Oosterlaan, J., & van der Meere, J. (1999). Information processing and energetic factors in attention-deficit/hyperactivity disorder. In H. C. Quay & A. E. Hogan (Eds.), Handbook of disruptive behavior disorders (pp. 75–104). Boston: Springer.Google Scholar
  59. Sergeant, J., Geurts, H. M., Huijbregts, S., Scheres, A., & Oosterlaan, J. (2003). The top and the bottom of ADHD: a neuropsychological perspective. Neuroscience & Biobehavioral Reviews, 27(7), 583–592.Google Scholar
  60. Shaw, R., & Lewis, V. (2005). The impact of computer-mediated and traditional academic task presentation on the performance and behaviour of children with ADHD. Journal of Research in Special Educational Needs, 5(2), 47–54.Google Scholar
  61. Somerville, L. H., Hare, T., & Casey, B. J. (2011). Frontostriatal maturation predicts cognitive control failure to appetitive cues in adolescents. Journal of Cognitive Neuroscience, 23(9), 2123–2134.Google Scholar
  62. Sonuga-Barke, E. (2002). Psychological heterogeneity in AD/HD—a dual pathway model of behaviour and cognition. Behavioural Brain Research, 130(1), 29–36.Google Scholar
  63. Sonuga-Barke, E. (2003). The dual pathway model of AD/HD: an elaboration of neuro-developmental characteristics. Neuroscience & Biobehavioral Reviews, 27(7), 593–604.Google Scholar
  64. Sonuga-Barke, E., Bitsakou, P., & Thompson, M. (2010). Beyond the dual pathway model: evidence for the dissociation of timing, inhibitory, and delay-related impairments in attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 49(4), 345–355.Google Scholar
  65. Sonuga-Barke, E., Taylor, E., Sembi, S., & Smith, J. (1992). Hyperactivity and delay aversion—I. The effect of delay on choice. Journal of Child Psychology and Psychiatry, 33(2), 387–398.Google Scholar
  66. van der Meere, J., & Stemerdink, N. (1999). The development of state regulation in normal children: an indirect comparison with children with ADHD. Developmental Neuropsychology, 16(2), 213–225.Google Scholar
  67. Van der Oord, S., Ponsioen, A. J. G. B., Geurts, H. M., Brink, E. T., & Prins, P. J. M. (2014). A pilot study of the efficacy of a computerized executive functioning remediation training with game elements for children with ADHD in an outpatient setting: outcome on parent-and teacher-rated executive functioning and ADHD behavior. Journal of Attention Disorders, 18(8), 699–712.Google Scholar
  68. Willcutt, E. G., Doyle, A. E., Nigg, J. T., Faraone, S. V., & Pennington, B. F. (2005). Validity of the executive function theory of attention-deficit/hyperactivity disorder: a meta-analytic review. Biological Psychiatry, 57(11), 1336–1346.Google Scholar
  69. Wu, K. K., Anderson, V., & Castiello, U. (2006). Attention-deficit/hyperactivity disorder and working memory: a task switching paradigm. Journal of Clinical and Experimental Neuropsychology, 28(8), 1288–1306.Google Scholar
  70. Zelazo, P. D., Li, Q., & Kesek, A. C. (2010). Hot executive function: emotion and the development of cognitive control. In S. D. Calkins & M. A. Bell (Eds.), Child development at the intersection of emotion and cognition (pp. 97–111). Washington, D.C.: American Psychological Association.Google Scholar

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Authors and Affiliations

  1. 1.Department of Psychology, Development of Language, Learning and ActionSaarland UniversitySaarbrückenGermany

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