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Evaluating the Effectiveness of Commercial Brain Game Training with Working-Memory Tasks

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Abstract

Commercial brain games are home- and computer-based cognitive trainings that are industrially offered and promise to enhance cognitive functioning by repeating cognitive tasks. Despite compelling evidence for the effectiveness of cognitive trainings in various domains and populations, the assumption of brain games’ effects on people’s minds has been challenged. However, there are only very few attempts to systematically evaluate the effectiveness of such games under ecologically valid training conditions. To approach this gap in the literature, we applied commercially available training tasks assumed to tap into working memory updating and capacity. The effectiveness of this training was measured by utilizing pre- and post-tests in trained tasks (criterion tasks), untrained transfer tasks from the assumed training domains (near-transfer tasks), as well as from the domains processing speed, shifting, inhibition, reasoning, and self-reported cognitive failures (far-transfer tasks). Training as well as pre-post-tests were completely administered home-based. In contrast to an active control group, a training group improved performance in the criterion tasks and near-transfer tasks. Improved performance was also evident in processing speed and shifting tasks (i.e., far-transfer tasks), but these improvements were not as conclusive as those in near-transfer tasks. Further, the number of reported cognitive failures was reduced in the training in contrast to the control group at post-test. Performance improvements were more pronounced for high-performing participants (i.e., magnification effects). In general, this study provides an evaluation of the effectiveness of a particular set of working-memory training tasks in an ecologically valid setting in the context of brain games.

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Notes

  1. Since the score measures of task performance underlying most of the reports presented here represent rather arbitrary values (reflecting a performance compound related to speed, accuracy, difficulty level, etc.), a probably more psychologically interpretable variable is the difficulty level achieved by participants in each particular task. For example, the difficulty level in working memory tasks is typically defined by the amount of information that needs to be stored and manipulated (objects, numbers etc., see detailed task descriptions in the method section). We therefore additionally ran a MANOVA for the matched sample (excluding the two criterion tasks for a most conservative assessment of transfer effects) in which we used the achieved difficulty level (instead of scores) as a dependent measure for the tasks Restorer, Turning tops, Turnabout, IQube, and Missing Link. The remaining tasks (for which no difficulty level existed as a dependent variable) remained the same as in the previous analysis (Digit span, Stroop error effect, Stroop RT effect, d2, TMT 1, TMT 2). As a result, the MANOVA still revealed the crucial significant group*time interaction, F(11, 138) = 4.036, p < .001, ηp 2 = 243. The pattern of significant effects in the subsequent ANOVAs were the same as in the previous analysis: Again, there were significant group*time interactions for Restorer, F(1148) = 5.612, p = .019, ηp 2 = .037 (increase in difficulty level from 3.73 to 4.22 (SE = 0.08) in the training group vs. from 3.66 to 3.92 (SE = 0.08) in the control group), Turning tops, F(1148) = 34.527, p < .001, ηp 2 = .189 (increase in difficulty level from 1.05 to 2.36 (SE = 0.12) in the training group vs. from 1.20 to 1.67 (SE = 0.12) in the control group), TMT 1, F(1148) = 5.110, p = .025, ηp2 = .033, and TMT 2, F(1148) = 6.212, p = .014, ηp2 = .040. Thus, the increase in difficulty level from pre- to post-training for the training group was about two times the size of the corresponding increase in the control group for the two variables Restorer (where the difficulty level is directly associated with the number of objects to be remembered) and Turning Tops. There was neither a significant group*time interaction regarding the variable Turnabout, F(11, 138) = 3.443, p = .066, ηp 2 = .023, nor regarding the remainder of dependent variables (Digit span, Stroop error effect, Stroop RT effect, d2, IQube, Missing link), all F < 1.

  2. To rule out the objection that our final matching procedure affected our results, we additionally followed up on the MANOVA regarding the full sample of participants that contributed pre- and post-test data. These analyses revealed (strikingly similar) post-hoc ANOVA results when compared to the matched sample. Specifically, significant group*time interactions emerged for the two variables that were part of both the pre-/post tests and the training sessions, Shuffler and Memory interrupted, indicating a direct training effect, F(1171) = 26.554, p < .001, ηp 2 = .134, and F(1171) = 141.867, p < .001, ηp 2 = .453, respectively. Post-hoc contrasts revealed a significant pre-training advantage for the control group (p = .010 and p = .005), but a significant post-test advantage of the training group (p = .035 and p < .001, respectively).

    Furthermore, significant group*time interactions emerged for four dependent transfer variables: Restorer, F(1171) = 10.247, p = .002, ηp 2 = .057 (pre-test advantage of the control group, p = .009, but no significant post-test group difference, p = .359), Turning tops, F(1171) = 36.338, p < .001, ηp 2 = .175 (pre-test advantage of the control group, p = .022, post-test advantage of the training group, p = .014), TMT 1, F(1171) = 5.702, p = .018, ηp 2 = .032 (pre-test advantage of the control group, p = .008, no significant post-test group difference, p = .742), and TMT 2, F(1171) = 4.980, p = .027, ηp 2 = .028 (pre-test advantage of the control group, p = .003, no significant post-test group difference, p = .531). There were no significant interactions regarding the remainder of dependent variables (Turnabout, Digit span, Stroop error effect, Stroop RT effect, d2, IQube, Missing link), all Fs < 1. Taken together, it is important to note that the final (matched) selection of participants (in order to achieve comparable pre-training performance levels in the criterion tasks between groups) actually worked against our hypothesis of finding significantly greater training effects in the training group. When analyzing the complete set of pre-post data, in many cases a performance disadvantage of the training group in the pre-training assessment was turned into a performance advantage at post-test assessment.

References

  • A consensus on the brain training industry from the scientific community. (2014). Retrieved from http://longevity3.stanford.edu/blog/2014/10/15/the-consensus-on-the-brain-training-industry-from-the-scientific-community-2/ .

  • Anguera, J. A., Boccanfuso, J., Rintoul, J. L., Al-Hashimi, O., Faraji, F., Janowich, J., et al. (2013). Video game training enhances cognitive control in older adults. Nature, 501(7465), 97–101.

    Article  PubMed  PubMed Central  Google Scholar 

  • Arnett, J. A., & Labovitz, S. S. (1995). Effect of physical layout in performance of the trail making test. Psychological Assessment, 7(2), 220–221.

    Article  Google Scholar 

  • Au, J., Sheehan, E., Tsai, N., Duncan, G. J., Buschkuehl, M., & Jaeggi, S. M. (2015). Improving fluid intelligence with training on working memory: a meta-analysis. Psychonomic Bulletin & Review, 22(2), 366–377.

    Article  Google Scholar 

  • Baddeley, A. (1986). Working memory. Oxford: Clarendon Press.

    Google Scholar 

  • Baddeley, A. (2003). Working memory: looking back and looking forward. Nature Reviews Neuroscience, 4(10), 829–839.

    Article  PubMed  Google Scholar 

  • Baddeley, A. (2012). Working memory: theories, models, and controversies. Annual Review of Psychology, 63, 1–29.

    Article  PubMed  Google Scholar 

  • Blomqvist, N. (1977). On the relation between change and initial value. Journal of the American Statistical Association, 72(360a), 746–749.

    Article  Google Scholar 

  • Boot, W. R., Blakely, D. P., & Simons, D. J. (2011). Do action video games improve perception and cognition? Frontiers in Psychology, 2, 226.

    Article  PubMed  PubMed Central  Google Scholar 

  • Brickenkamp, R. (1962). Test d2: Aufmerksamkeits-Belastungs-Test. Göttingen: Hogrefe.

    Google Scholar 

  • Broadbent, D. E., Cooper, P. F., FitzGerald, P., & Parkes, K. R. (1982). The cognitive failures questionnaire (CFQ) and its correlates. British Journal of Clinical Psychology, 21(1), 1–16.

    Article  PubMed  Google Scholar 

  • Buckley, D., Codina, C., Bhardwaj, P., & Pascalis, O. (2010). Action video game players and deaf observers have larger Goldmann visual fields. Vision Research, 50(5), 548–556.

    Article  PubMed  Google Scholar 

  • Campbell, D. T., & Stanley, J. (1966). Experimental and quasi-experimental designs for research. Chicago: Rand McNally.

    Google Scholar 

  • Carpenter, P. A., Just, M. A., & Shell, P. (1990). What one intelligence test measures: a theoretical account of the processing in the raven progressive matrices test. Psychological Review, 97(3), 404–431.

    Article  PubMed  Google Scholar 

  • Caruso, J. C. (2004). A comparison of the reliabilities of four types of difference scores for five cognitive assessment batteries. European Journal of Psychological Assessment, 20(3), 166–171.

    Article  Google Scholar 

  • Castel, A. D., Pratt, J., & Drummond, E. (2005). The effects of action video game experience on the time course of inhibition of return and the efficiency of visual search. Acta Psychologica, 119(2), 217–230.

    Article  PubMed  Google Scholar 

  • Chein, J. M., & Morrison, A. B. (2010). Expanding the mind’s workspace: training and transfer effects with a complex working memory span task. Psychonomic Bulletin & Review, 17(2), 193–199.

    Article  Google Scholar 

  • Cronbach, L. J., & Furby, L. (1970). How we should measure" change": or should we? Psychological Bulletin, 74(1), 68–80.

    Article  Google Scholar 

  • Dahlin, K. I. E. (2013). Working memory training and the effect on mathematical achievement in children with attention deficits and special needs. Journal of Education and Learning, 2(1), 118–133.

    Article  Google Scholar 

  • Dahlin, E., Neely, A. S., Larsson, A., Bäckman, L., & Nyberg, L. (2008a). Transfer of learning after updating training mediated by the striatum. Science, 320(5882), 1510–1512.

    Article  PubMed  Google Scholar 

  • Dahlin, E., Nyberg, L., Bäckman, L., & Neely, A. S. (2008b). Plasticity of executive functioning in young and older adults: Immediate training gains, transfer, and long-term maintenance. Psychology and Aging, 23(4), 720–730.

    Article  PubMed  Google Scholar 

  • Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior, 19(4), 450–466.

    Article  Google Scholar 

  • Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64, 135–168.

    Article  PubMed  Google Scholar 

  • Dye, M. W., Green, C. S., & Bavelier, D. (2009). Increasing speed of processing with action video games. Current Directions in Psychological Science, 18(6), 321–326.

    Article  PubMed  PubMed Central  Google Scholar 

  • Engle, R. W., Carullo, J. J., & Collins, K. W. (1991). Individual differences in working memory for comprehension and following directions. The Journal of Educational Research, 84(5), 253–262.

    Article  Google Scholar 

  • Green, C. S., & Bavelier, D. (2003). Action video game modifies visual selective attention. Nature, 423(6939), 534–537.

    Article  PubMed  Google Scholar 

  • Green, C. S., & Bavelier, D. (2006a). Effect of action video games on the spatial distribution of visuospatial attention. Journal of Experimental Psychology: Human Perception and Performance, 32(6), 1465–1478.

    PubMed  PubMed Central  Google Scholar 

  • Green, C. S., & Bavelier, D. (2006b). Enumeration versus multiple object tracking: the case of action video game players. Cognition, 101(1), 217–245.

    Article  PubMed  Google Scholar 

  • Green, C. S., & Bavelier, D. (2007). Action-video-game experience alters the spatial resolution of vision. Psychological Science, 18(1), 88–94.

    Article  PubMed  PubMed Central  Google Scholar 

  • Green, C. S., Strobach, T., & Schubert, T. (2014). On methodological standards in training and transfer experiments. Psychological Research, 78(6), 756–772.

    Article  PubMed  Google Scholar 

  • Halford, G. S., Cowan, N., & Andrews, G. (2007). Separating cognitive capacity from knowledge: a new hypothesis. Trends in Cognitive Sciences, 11(6), 236–242.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hardy, J. L., Nelson, R. A., Thomason, M. E., Sternberg, D. A., Katovich, K., Farzin, F., & Scanlon, M. (2015). Enhancing cognitive abilities with comprehensive training: a large, online, randomized, active-controlled trial. PLoS One, 10(9), e0134467.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hedge, C., Powell, G., Sumner, P. (2017). The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences. Behavior Research Methods.(In press)

  • Holmes, J., Gathercole, S. E., Dunning, D. L. (2009). Adaptive training leads to sustained enhancement of poor working memory in children. Developmental science, 12(4), 9–15.

  • Jaeggi, S. M., Buschkuehl, M., Jonides, J., & Perrig, W. J. (2008). Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences, 105(19), 6829–6833.

    Article  Google Scholar 

  • Jaeggi, S. M., Studer-Luethi, B., Buschkuehl, M., Su, Y.-F., Jonides, J., & Perrig, W. J. (2010). The relationship between n-back performance and matrix reasoning—Implications for training and transfer. Intelligence, 38(6), 625–635.

    Article  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • Karbach, J., Strobach, T., & Schubert, T. (2015). Adaptive working-memory training benefits reading, but not mathematics in middle childhood. Child Neuropsychology, 21(3), 285–301.

    Article  PubMed  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • Klingberg, T. (2010). Training and plasticity of working memory. Trends in Cognitive Sciences, 14(7), 317–324.

    Article  PubMed  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Koenen, T., Strobach, T., & Karbach, J. (2016). Working memory training. In T. Strobach & K. J. (Eds.), Cognitive training: An overview of features and applications. New York: Springer.

    Google Scholar 

  • Kristjánsson, Á. (2013). The case for causal influences of action videogame play upon vision and attention. Attention, Perception, & Psychophysics, 75(4), 667–672.

    Article  Google Scholar 

  • Li, R., Polat, U., Makous, W., & Bavelier, D. (2009). Enhancing the contrast sensitivity function through action video game training. Nature Neuroscience, 12(5), 549–551.

    Article  PubMed  PubMed Central  Google Scholar 

  • MacLeod, C. M. (1991). Half a century of research on the Stroop effect: an integrative review. Psychological Bulletin, 109(2), 163–203.

    Article  PubMed  Google Scholar 

  • Mahncke, H. W., Connor, B. B., Appelman, J., Ahsanuddin, O. N., Hardy, J. L., Wood, R. A., et al. (2006). Memory enhancement in healthy older adults using a brain plasticity-based training program: a randomized, controlled study. Proceedings of the National Academy of Sciences, 103(33), 12523–12528.

    Article  Google Scholar 

  • Melby-Lervåg, M., & Hulme, C. (2013). Is working memory training effective? A meta-analytic review. Developmental Psychology, 49(2), 270–291.

    Article  PubMed  Google Scholar 

  • Morrison, A. B., & Chein, J. M. (2011). Does working memory training work? The promise and challenges of enhancing cognition by training working memory. Psychonomic Bulletin & Review, 18(1), 46–60.

    Article  Google Scholar 

  • Nouchi, R., Taki, Y., Takeuchi, H., Hashizume, H., Akitsuki, Y., Shigemune, Y., et al. (2012). Brain training game improves executive functions and processing speed in the elderly: a randomized controlled trial. PLoS One, 7(1), e29676.

    Article  PubMed  PubMed Central  Google Scholar 

  • Oberauer, K. (2009). Design for a working memory. Psychology of Learning and Motivation, 51, 45–100.

    Article  Google Scholar 

  • Oldham, P. (1962). A note on the analysis of repeated measurements of the same subjects. Journal of Chronic Diseases, 15(10), 969–977.

    Article  PubMed  Google Scholar 

  • Olesen, P. J., Westerberg, H., & Klingberg, T. (2004). Increased prefrontal and parietal activity after training of working memory. Nature Neuroscience, 7(1), 75–79.

    Article  PubMed  Google Scholar 

  • Owen, A. M., Hampshire, A., Grahn, J. A., Stenton, R., Dajani, S., Burns, A. S., et al. (2010). Putting brain training to the test. Nature, 465(7299), 775–778.

    Article  PubMed  PubMed Central  Google Scholar 

  • Rabipour, S., & Raz, A. (2012). Training the brain: fact and fad in cognitive and behavioral remediation. Brain and Cognition, 79(2), 159–179.

    Article  PubMed  Google Scholar 

  • Rebok, G. W., Carlson, M. C., & Langbaum, J. B. (2007). Training and maintaining memory abilities in healthy older adults: traditional and novel approaches. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 62(1), 53–61.

    Article  Google Scholar 

  • Richmond, L. L., Morrison, A. B., Chein, J. M., & Olson, I. R. (2011). Working memory training and transfer in older adults. Psychology and Aging, 26(4), 813–822.

    Article  PubMed  Google Scholar 

  • Rogosa, D. (1995). Myths and methods: “myths about longitudinal research” plus supplemental questions. In J. M. Gottman (Ed.), The analysis of change (pp. 3–66). Hillsdale: Lawrence Ealbaum Associates.

    Google Scholar 

  • Salminen, T., Frensch, P., Strobach, T., & Schubert, T. (2016a). Age-specific differences of dual n-back training. Aging, Neuropsychology, and Cognition, 23(1), 18–39.

    Article  Google Scholar 

  • Salminen, T., Kühn, S., Frensch, P. A., & Schubert, T. (2016b). Transfer after dual n-back training depends on striatal activation change. Journal of Neuroscience, 36(39), 10198–10213.

    Article  PubMed  Google Scholar 

  • Schmiedek, F. (2016). Methods and designs. In T. Strobach & J. Karbach (Eds.), Cognitive training: An overview of features and applications. New York: Springer.

    Google Scholar 

  • Schmiedek, F., Bauer, C., Lövdén, M., Brose, A., & Lindenberger, U. (2010a). Cognitive enrichment in old age: web-based training programs. GeroPsych: The Journal of Gerontopsychology and Geriatric Psychiatry, 23(2), 59–67.

    Article  Google Scholar 

  • Schmiedek, F., Lövdén, M., & Lindenberger, U. (2010b). Hundred days of cognitive training enhance broad cognitive abilities in adulthood: findings from the COGITO study. Frontiers in Aging Neuroscience, 2, 27.

    PubMed  PubMed Central  Google Scholar 

  • Schubert, T., Finke, K., Redel, P., Kluckow, S., Müller, H., & Strobach, T. (2015). Video game experience and its influence on visual attention parameters: an investigation using the framework of the theory of visual attention (TVA). Acta Psychologica, 157, 200–214.

    Article  PubMed  Google Scholar 

  • Shipstead, Z., Redick, T. S., & Engle, R. W. (2012). Is working memory training effective? Psychological Bulletin, 138(4), 628–654.

    Article  PubMed  Google Scholar 

  • Simons, D. J., Boot, W. R., Charness, N., Gathercole, S. E., Chabris, C. F., Hambrick, D. Z., & Stine-Morrow, E. A. (2016). Do “brain-training” programs work? Psychological Science in the Public Interest, 17(3), 103–186.

    Article  PubMed  Google Scholar 

  • Spence, I., Yu, J. J., Feng, J., & Marshman, J. (2009). Women match men when learning a spatial skill. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35(4), 1097–1103.

    PubMed  Google Scholar 

  • Stanovich, K. E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading research quarterly 21(4), 360–407.

  • Steinborn, M., Langner, R., Flehmig, H. C., & Huestegge, L. (2016). Everyday life cognitive instability predicts simple reaction time variability: analysis of reaction time distributions and delta plots. Applied Cognitive Psychology, 30(1), 92–102.

    Article  Google Scholar 

  • Steinborn, M., Langner, R., Flehmig, H., Huestegge, L. (2017). Methodology of performance scoring in the d2 sustained-attention test: Cumulative-reliability functions and practical guidelines. Psychological Assessment (In press).

  • Strobach, T., & Karbach, J. (2016). Cognitive training: an overview of features and applications. New York: Springer.

    Book  Google Scholar 

  • Strobach, T., Frensch, P. A., & Schubert, T. (2012a). Video game practice optimizes executive control skills in dual-task and task switching situations. Acta Psychologica, 140(1), 13–24.

    Article  PubMed  Google Scholar 

  • Strobach, T., Frensch, P. A., Soutschek, A., & Schubert, T. (2012b). Investigation on the improvement and transfer of dual-task coordination skills. Psychological Research, 76(6), 794–811.

    Article  PubMed  Google Scholar 

  • Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18(6), 643–662.

    Article  Google Scholar 

  • Taatgen, N. A. (2013). The nature and transfer of cognitive skills. Psychological Review, 120(3), 439–471.

    Article  PubMed  Google Scholar 

  • Thorndike, E. L. (1924). The influence of the chance imperfections of measures upon the relation of initial score to gain or loss. Journal of Experimental Psychology, 7(3), 225–232.

    Article  Google Scholar 

  • Torous, J., Staples, P., Fenstermacher, E., Dean, J., & Keshavan, M. (2016). Barriers, benefits, and beliefs of brain training smartphone apps: an internet survey of younger US consumers. Frontiers in Human Neuroscience, 10, 180.

    PubMed  PubMed Central  Google Scholar 

  • Tu, Y. K., & Gilthorpe, M. S. (2007). Revisiting the relation between change and initial value: A review and evaluation. Statistics in Medicine, 26(2), 443–457.

    Article  PubMed  Google Scholar 

  • van Muijden, J., Band, G. P., & Hommel, B. (2012). Online games training aging brains: Limited transfer to cognitive control functions. Frontiers in Human Neuroscience, 6, 221.

    PubMed  PubMed Central  Google Scholar 

  • von Bastian, C. C., & Oberauer, K. (2013). Distinct transfer effects of training different facets of working memory capacity. Journal of Memory and Language, 69(1), 36–58.

    Article  Google Scholar 

  • Walberg, H. J., & Tsai, S.-L. (1983). Matthew effects in education. American Educational Research Journal, 20(3), 359–373.

    Google Scholar 

  • Wechsler, D. (2008). Wechsler adult intelligence scale-fourth. San Antonio: Pearson.

    Google Scholar 

  • Westerberg, H., Jacobaeus, H., Hirvikoski, T., Clevberger, P., Östensson, M.-L., Bartfai, A., & Klingberg, T. (2007). Computerized working memory training after stroke—a pilot study. Brain Injury, 21(1), 21–29.

    Article  PubMed  Google Scholar 

  • Wilhelm, O., Hildebrandt, A., & Oberauer, K. (2013). What is working memory, and how can we measure it? Frontiers in Psychology, 4, 433.

    Article  PubMed  PubMed Central  Google Scholar 

  • Willett, J. B. (1988). Questions and answers in the measurement of change. Review of Research in Education, 15(1), 345–422.

    Article  Google Scholar 

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Acknowledgements

We would like to thank www.neuronation.com and Rouwen Hirth for their technical support during data collection. Correspondence concerning this article should be addressed to Tilo Strobach, Medical School Hamburg, Department of Psychology, Am Kaiserkai 1, 20457 Hamburg, Germany. E-mail may be sent to tilo.strobach@medicalschool-hamburg.de.

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TS and LH have full positions at Medical School Hamburg and at University of Würzburg, respectively. The authors have no financial interest in this study and have no financial disclosure to the participating company. They do not hold shares in this company.

Appendices

Appendix A

Table 6 List of first appearances of presented TV news issues in Sessions 1–21 of control group treatment (all issues were primarily aired in 1994)

Appendix B

Fig. 4
figure 4

Overview of the non-significant group*time interactions based on the matched samples data. Performance in the tests a Turnabout, b Digit span, c Stroop Effect (in reaction times [RT]), Stroop Effect (in error rates), e d2, f IQube, and g Missing Link is illustrated for pre-test and post-test sessions as well as for the training and the control groups. Error bars represent SEs

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Strobach, T., Huestegge, L. Evaluating the Effectiveness of Commercial Brain Game Training with Working-Memory Tasks. J Cogn Enhanc 1, 539–558 (2017). https://doi.org/10.1007/s41465-017-0053-0

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