Advertisement

Journal of Cognitive Enhancement

, Volume 1, Issue 4, pp 374–393 | Cite as

Do Individual Differences Predict Change in Cognitive Training Performance? A Latent Growth Curve Modeling Approach

  • Sabrina GuyeEmail author
  • Carla De Simoni
  • Claudia C. von Bastian
Original Article

Abstract

Cognitive training interventions have become increasingly popular as a potential means to cost-efficiently stabilize or enhance cognitive functioning across the lifespan. Large training improvements have been consistently reported on the group level, with, however, large differences on the individual level. Identifying the factors contributing to these individual differences could allow for developing individually tailored interventions to boost training gains. In this study, we therefore examined a range of individual differences variables that had been discussed in the literature to potentially predict training performance. To estimate and predict individual differences in the training trajectories, we applied Latent Growth Curve models to existing data from three working memory training interventions with younger and older adults. However, we found that individual differences in demographic variables, real-world cognition, motivation, cognition-related beliefs, personality, leisure activities, and computer literacy and training experience were largely unrelated to change in training performance. Solely baseline cognitive performance was substantially related to change in training performance and particularly so in young adults, with individuals with higher baseline performance showing the largest gains. Thus, our results conform to magnification accounts of cognitive change.

Keywords

Working memory training Individual differences Latent growth curve modeling 

Notes

Acknowledgements

During the work on her dissertation, Sabrina Guye was a pre-doctoral fellow of the International Max Planck Research School on the Life Course (LIFE; participating institutions: MPI for Human Development, Humboldt-Universität zu Berlin, Freie Universität Berlin, University of Michigan, University of Virginia, University of Zurich).

Funding Information

Data reported in this work has been collected with the support of grants awarded to the first and second author from the Suzanne and Hans Biäsch Foundation for Applied Psychology (Ref 2014/32; 2016/08). The first author was further supported by the Forschungskredit of the University of Zurich (FK-16-062), and the second author by the Swiss National Science Foundation (No. 100014_146074). Moreover, both authors were supported by the URPP “Dynamics of Healthy Aging” of the University of Zurich.

Compliance with Ethical Standards

Written informed consent was obtained from all participants. Both studies were approved by the ethics committee of the Department of Psychology of the University of Zurich.

Supplementary material

41465_2017_49_MOESM1_ESM.docx (222 kb)
ESM 1 (DOCX 221 kb)

References

  1. Ackerman, P. L., & Lohman, D. F. (2006). Individual differences in cognitive functions. In P. A. Alexander & P. H. Winne (Eds.), Handbook of Educational Psychology (2nd ed., pp. 139–161). Mahwah: Lawrence Erlbaum Associates Publishers.Google Scholar
  2. Antón, E., Duñabeitia, J. A., Estévez, A., Hernández, J. A., Castillo, A., Fuentes, L. J., et al. (2014). Is there a bilingual advantage in the ANT task? Evidence from children. Frontiers in Psychology, 5, 398.  https://doi.org/10.3389/fpsyg.2014.00398.PubMedPubMedCentralGoogle Scholar
  3. 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.  https://doi.org/10.3758/s13423-014-0699-x.CrossRefGoogle Scholar
  4. Bandura, A. (2006). Guide for constructing self-efficacy scales. In F. Pajares & T. Urdan (Eds.), Self-efficacy beliefs of adolescents (pp. 307–337). Greenwich: Information Age Publishing.Google Scholar
  5. Bherer, L., Kramer, A. F., Peterson, M. S., Colcombe, S., Erickson, K., & Becic, E. (2008). Transfer effects in task-set cost and dual-task cost after dual-task training in older and younger adults: further evidence for cognitive plasticity in attentional control in late adulthood. Experimental Aging Research, 34(3), 188–219.  https://doi.org/10.1080/03610730802070068.CrossRefPubMedPubMedCentralGoogle Scholar
  6. Bogg, T., & Lasecki, L. (2015). Reliable gains? Evidence for substantially underpowered designs in studies of working memory training transfer to fluid intelligence. Frontiers in Psychology, 5.  https://doi.org/10.3389/fpsyg.2014.01589.
  7. Borella, E., Carretti, B., Riboldi, F., & De Beni, R. (2010). Working memory training in older adults: evidence of transfer and maintenance effects. Psychology and Aging, 25(4), 767–778.  https://doi.org/10.1037/a0020683.CrossRefPubMedGoogle Scholar
  8. Borella, E., Carretti, B., Cantarella, A., Riboldi, F., Zavagnin, M., & De Beni, R. (2014). Benefits of training visuospatial working memory in young-old and old-old. Developmental Psychology, 50(3), 714–727.  https://doi.org/10.1037/a0034293.CrossRefPubMedGoogle Scholar
  9. Brehmer, Y., Westerberg, H., & Bäckman, L. (2012). Working-memory training in younger and older adults: training gains, transfer, and maintenance. Frontiers in Human Neuroscience, 6.  https://doi.org/10.3389/fnhum.2012.00063.
  10. 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.  https://doi.org/10.1111/j.2044-8260.1982.tb01421.x.CrossRefPubMedGoogle Scholar
  11. Brose, A., Schmiedek, F., Lövdén, M., & Lindenberger, U. (2012). Daily variability in working memory is coupled with negative affect: the role of attention and motivation. Emotion, 12(3), 605–617.  https://doi.org/10.1037/a0024436.CrossRefPubMedGoogle Scholar
  12. Buitenweg, J. I. V., Murre, J. M. J., & Ridderinkhof, K. R. (2012). Brain training in progress: a review of trainability in healthy seniors. Frontiers in Human Neuroscience, 6, 183.  https://doi.org/10.3389/fnhum.2012.00183.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Bürki, C., Ludwig, C., Chicherio, C., & de Ribaupierre, A. (2014). Individual differences in cognitive plasticity: an investigation of training curves in younger and older adults. Psychological Research, 78(6), 821–835.  https://doi.org/10.1007/s00426-014-0559-3.CrossRefPubMedGoogle Scholar
  14. Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42(1), 116–131.  https://doi.org/10.1037/0022-3514.42.1.116.CrossRefGoogle Scholar
  15. Clark, C. M., Lawlor-Savage, L., & Goghari, V. M. (2017). Working memory training in healthy young adults: support for the null from a randomized comparison to active and passive control groups. PLoS One, 12(5), 1–25.  https://doi.org/10.1371/journal.pone.0177707 May.CrossRefGoogle Scholar
  16. Costa, P. T., & McCrae, R. R. (1992). Revised NEO personality inventory (NEO PI-R) and NEP five-factor inventory (NEO-FFI): professional manual. Odessa: Psychological Assessment Resources.Google Scholar
  17. Cumming, G. (2011). Understanding the new statistics: effect sizes, confidence intervals, and meta-analysis. New York: Routledge.Google Scholar
  18. Curran, P. J., Obeidat, K., & Losardo, D. (2010). Twelve frequently asked questions about growth curve modeling. Journal of Cognition and Development, 11(2), 121–136.  https://doi.org/10.1080/15248371003699969.CrossRefPubMedPubMedCentralGoogle Scholar
  19. De Simoni, C., & von Bastian, C. C. (2017). Process-specific effects of working memory training.Google Scholar
  20. Deci, E. L., & Ryan, R. M. (2016). Intrinsic motivation inventory. Retrieved from http://selfdeterminationtheory.org/intrinsic-motivation-inventory/.
  21. Dienes, Z. (2014). Using Bayes to get the most out of non-significant results. Frontiers in Psychology, 5.  https://doi.org/10.3389/fpsyg.2014.00781.
  22. Dougherty, M. R., Hamovitz, T., & Tidwell, J. W. (2016). Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: support for the null. Psychonomic Bulletin & Review, 23(1), 306–316.  https://doi.org/10.3758/s13423-015-0865-9.CrossRefGoogle Scholar
  23. Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92(6), 1087–1101.  https://doi.org/10.1037/0022-3514.92.6.1087.CrossRefPubMedGoogle Scholar
  24. Dweck, C. S. (2000). Self-theories: their role in motivation, personality, and development. Philadelphia: Psychology Press.Google Scholar
  25. Fleischhauer, M., Enge, S., Brocke, B., Ullrich, J., Strobel, A., & Strobel, A. (2010). Same or different? Clarifying the relationship of need for cognition to personality and intelligence. Personality and Social Psychology Bulletin, 36(1), 82–96.  https://doi.org/10.1177/0146167209351886.CrossRefPubMedGoogle Scholar
  26. Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198.  https://doi.org/10.1016/0022-3956(75)90026-6.CrossRefPubMedGoogle Scholar
  27. Graham, E. K., & Lachman, M. E. (2012). Personality stability is associated with better cognitive performance in adulthood: are the stable more able? The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 67(5), 545–554.  https://doi.org/10.1093/geronb/gbr149.CrossRefPubMedCentralGoogle Scholar
  28. Grimm, K. J., Ram, N., & Estabrook, R. (2017). Growth modeling: structural equation and multilevel modeling approaches. New York: Guilford Press.Google Scholar
  29. Guye, S., & von Bastian, C. C. (2017). Working memory training in older adults: evidence for the absence of transfer. Psychology and Aging.  https://doi.org/10.1037/pag0000206.
  30. Guye, S., Röcke, C., Mérillat, S., von Bastian, C. C., & Martin, M. (2016). Adult lifespan. In T. Strobach & J. Karbach (Eds.), Cognitive training: an overview of features and applications (pp. 45–55). Berlin: Springer.CrossRefGoogle Scholar
  31. Halsey, L. G., Curran-Everett, D., Vowler, S. L., & Drummond, G. B. (2015). The fickle P value generates irreproducible results. Nature Methods, 12(3), 179–185.  https://doi.org/10.1038/nmeth.3288.CrossRefPubMedGoogle Scholar
  32. Hill, B. D., Foster, J. D., Elliott, E. M., Shelton, J. T., McCain, J., & Gouvier, W. D. (2013). Need for cognition is related to higher general intelligence, fluid intelligence, and crystallized intelligence, but not working memory. Journal of Research in Personality, 47(1), 22–25.  https://doi.org/10.1016/j.jrp.2012.11.001.CrossRefGoogle Scholar
  33. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.  https://doi.org/10.1080/10705519909540118.CrossRefGoogle Scholar
  34. Ishihara, S. (1917). Tests for colour blindness. Tokyo: Handaya Hongo Harukichi.Google Scholar
  35. 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 of the United States of America, 105(19), 6829–6833.  https://doi.org/10.1073/pnas.0801268105.CrossRefPubMedPubMedCentralGoogle Scholar
  36. Jaeggi, S. M., Buschkuehl, M., Shah, P., & Jonides, J. (2014). The role of individual differences in cognitive training and transfer. Memory & Cognition, 42(3), 464–480.  https://doi.org/10.3758/s13421-013-0364-z.CrossRefGoogle Scholar
  37. Jopp, D., & Hertzog, C. (2007). Activities, self-referent memory beliefs, and cognitive performance: evidence for direct and mediated relations. Psychology and Aging, 22(4), 811–825.  https://doi.org/10.1037/0882-7974.22.4.811.CrossRefPubMedGoogle Scholar
  38. Jopp, D., & Hertzog, C. (2010). Assessing adult leisure activities: an extension of a self-report activity questionnaire. Psychological Assessment, 22(1), 108–120.  https://doi.org/10.1037/a0017662.CrossRefPubMedPubMedCentralGoogle Scholar
  39. 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.  https://doi.org/10.1111/j.1467-7687.2009.00846.x.CrossRefPubMedGoogle Scholar
  40. Karbach, J., & Verhaeghen, P. (2014). Making working memory work: a meta-analysis of executive-control and working memory training in older adults. Psychological Science, 25(11), 2027–2037.  https://doi.org/10.1177/0956797614548725.CrossRefPubMedPubMedCentralGoogle Scholar
  41. Katz, B., Jones, M. R., Shah, P., Buschkuehl, M., & Jaeggi, S. M. (2016). Individual differences and motivational effects in cognitive training research. In T. Strobach & J. Karbach (Eds.), Cognitive training: an overview of features and applications (pp. 157–166). Berlin: Springer.CrossRefGoogle Scholar
  42. Kelly, M. E., Loughrey, D., Lawlor, B. A., Robertson, I. H., Walsh, C., & Brennan, S. (2014). The impact of cognitive training and mental stimulation on cognitive and everyday functioning of healthy older adults: a systematic review and meta-analysis. Ageing Research Reviews, 15, 28–43.  https://doi.org/10.1016/j.arr.2014.02.004.CrossRefPubMedGoogle Scholar
  43. Kenny, D. A., Kaniskan, B., & McCoach, D. B. (2015). The performance of RMSEA in models with small degrees of freedom. Sociological Methods & Research, 44(3), 486–507.  https://doi.org/10.1177/0049124114543236.CrossRefGoogle Scholar
  44. Kirk, N. W., Fiala, L., Scott-Brown, K. C., & Kempe, V. (2014). No evidence for reduced Simon cost in elderly bilinguals and bidialectals. Journal of Cognitive Psychology, 26(6), 640–648.  https://doi.org/10.1080/20445911.2014.929580.CrossRefPubMedPubMedCentralGoogle Scholar
  45. Kliegl, R., Smith, J., & Baltes, P. B. (1990). On the locus and process of magnification of age differences during mnemonic training. Developmental Psychology, 26(6), 894–904.  https://doi.org/10.1037/0012-1649.26.6.894.CrossRefGoogle Scholar
  46. Kline, R. B. (2016). Mean structures and latent growth models. In Principles and practice of structural equation modeling (4th ed., pp. 369–393). New York: Guilford Press.Google Scholar
  47. Könen, T., & Karbach, J. (2015). The benefits of looking at intraindividual dynamics in cognitive training data. Frontiers in Psychology, 6, 615.  https://doi.org/10.3389/fpsyg.2015.00615.PubMedPubMedCentralGoogle Scholar
  48. Lampit, A., Hallock, H., & Valenzuela, M. (2014). Computerized cognitive training in cognitively healthy older adults: a systematic review and meta-analysis of effect modifiers. PLoS Medicine, 11(11), e1001756.  https://doi.org/10.1371/journal.pmed.1001756.CrossRefPubMedPubMedCentralGoogle Scholar
  49. Lewandowsky, S. (2011). Working memory capacity and categorization: individual differences and modeling. Journal in Experimental Psychology: Learning, Memory, and Cognition, 37(3), 720–738.  https://doi.org/10.1037/a0022639.Google Scholar
  50. Lewandowsky, S., Oberauer, K., Yang, L.-X., & Ecker, U. K. H. (2010). A working memory test battery for MATLAB. Behavior Research Methods, 42(2), 571–585.  https://doi.org/10.3758/BRM.42.2.571.CrossRefPubMedGoogle Scholar
  51. Lövdén, M., Brehmer, Y., Li, S.-C., & Lindenberger, U. (2012). Training-induced compensation versus magnification of individual differences in memory performance. Frontiers in Human Neuroscience, 6, 141.  https://doi.org/10.3389/fnhum.2012.00141.CrossRefPubMedPubMedCentralGoogle Scholar
  52. Melby-Lervåg, M., & Hulme, C. (2013). Is working memory training effective? A meta-analytic review. Developmental Psychology, 49(2), 270–291.  https://doi.org/10.1037/a0028228.CrossRefPubMedGoogle Scholar
  53. Melby-Lervåg, M., Redick, T. S., & Hulme, C. (2016). Working memory training does not improve performance on measures of intelligence or other measures of “far transfer”: evidence from a meta-analytic review. Perspectives on Psychological Science, 11(4), 512–534.  https://doi.org/10.3837/tiis.0000.00.000.CrossRefPubMedPubMedCentralGoogle Scholar
  54. Minear, M., Brasher, F., Brandt Guerrero, C., Brasher, M., Moore, A., & Sukeena, J. (2016). A simultaneous examination of two forms of working memory training: evidence for near transfer only. Memory & Cognition, 44(7), 1014–1037.  https://doi.org/10.3758/s13421-016-0616-9.CrossRefGoogle Scholar
  55. Moreau, D., Kirk, I. J., & Waldie, K. E. (2016). Seven pervasive statistical flaws in cognitive training interventions. Frontiers in Human Neuroscience, 10, 3.  https://doi.org/10.3389/fnhum.2016.00153.CrossRefGoogle Scholar
  56. Noack, H., Lövdén, M., Schmiedek, F., & Lindenberger, U. (2009). Cognitive plasticity in adulthood and old age: gauging the generality of cognitive intervention effects. Restorative Neurology and Neuroscience, 27(5), 435–453.  https://doi.org/10.3233/RNN-2009-0496.PubMedGoogle Scholar
  57. Oberauer, K. (2005). Binding and inhibition in working memory: individual and age differences in short-term recognition. Journal of Experimental Psychology: General, 134(3), 368–387.  https://doi.org/10.1037/0096-3445.134.3.368.CrossRefGoogle Scholar
  58. Paap, K. R., Johnson, H. R., & Sawi, O. (2014). Are bilingual advantages dependent upon specific tasks or specific bilingual experiences? Journal of Cognitive Psychology, 26(6), 615–639.  https://doi.org/10.1080/20445911.2014.944914.CrossRefGoogle Scholar
  59. R Core Team. (2015). R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing Retrieved from https://www.r-project.org.Google Scholar
  60. Rabbitt, P., Diggle, P., Holland, F., & McInnes, L. (2004). Practice and drop-out effects during a 17-year longitudinal study of cognitive aging. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 59(2), 84–97.  https://doi.org/10.1093/geronb/59.2.P84.CrossRefGoogle Scholar
  61. Rheinberg, F., Vollmeyer, R., & Bruns, B. D. (2001). FAM: EIn Fragebogen zur Erfassung aktueller motivation in Lern- und Leistungssituationen. Diagnostica, 47(2), 57–66.  https://doi.org/10.1026//0012-1924.47.2.57.CrossRefGoogle Scholar
  62. Rosseel, Y. (2012). lavaan: an R package for structural equation modeling. Journal of Statistical Software, 48(2).  10.18637/jss.v048.i02.
  63. Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23–74.  https://doi.org/10.1002/0470010940.Google Scholar
  64. Schmiedek, F., Lövdén, M., & Lindenberger, U. (2010). Hundred days of cognitive training enhance broad cognitive abilities in adulthood: findings from the COGITO study. Frontiers in Aging Neuroscience, 2(27), 1–10.  https://doi.org/10.3389/fnagi.2010.00027.Google Scholar
  65. Schmiedek, F., Lövdén, M., & Lindenberger, U. (2013). Keeping it steady: older adults perform more consistently on cognitive tasks than younger adults. Psychological Science, 24(9), 1747–1754.  https://doi.org/10.1177/0956797613479611.CrossRefPubMedGoogle Scholar
  66. Schmiedek, F., Lövdén, M., & Lindenberger, U. (2014). A task is a task is a task: putting complex span, n-back, and other working memory indicators in psychometric context. Frontiers in Psychology, 5.  https://doi.org/10.3389/fpsyg.2014.01475.
  67. Schwaighofer, M., Fischer, F., & Bühner, M. (2015). Does working memory training transfer? A meta-analysis including training conditions as moderators. Educational Psychologist, 50(2), 138–166.  https://doi.org/10.1080/00461520.2015.1036274.CrossRefGoogle Scholar
  68. Schwarzer, R., & Jerusalem, M. (1995). Generalized self-efficacy scale. In J. Weinman, S. Wright, & M. Johnston (Eds.), Measures in health psychology: a user’s portfolio. Causal and control beliefs (pp. 35–37). NFER-NELSON: Windsor.Google Scholar
  69. Shah, P., Buschkuehl, M., Jaeggi, S., & Jonides, J. (2012). Cognitive training for ADHD: the importance of individual differences. Journal of Applied Research in Memory and Cognition, 1(3), 204–205.  https://doi.org/10.1016/j.jarmac.2012.07.001.CrossRefGoogle Scholar
  70. Sheikh, J. I., & Yesavage, J. A. (1986). Geriatric depression scale (GDS): recent evidence and development of a shorter version. Clinical Gerontologist, 5(1–2), 165–173.  https://doi.org/10.1300/J018v05n01.Google Scholar
  71. Shipstead, Z., Redick, T. S., & Engle, R. W. (2012). Is working memory training effective? Psychological Bulletin, 138(4), 628–654.  https://doi.org/10.1037/a0027473.CrossRefPubMedGoogle Scholar
  72. Soveri, A., Antfolk, J., Karlsson, L., Salo, B., & Laine, M. (2017). Working memory training revisited: a multi-level meta-analysis of n-back training studies. Psychonomic Bulletin & Review.  https://doi.org/10.3758/s13423-016-1217-0.
  73. Sprenger, A. M., Atkins, S. M., Bolger, D. J., Harbison, J. I., Novick, J. M., Chrabaszcz, J. R., et al. (2013). Training working memory: limits of transfer. Intelligence, 41(5), 638–663.  https://doi.org/10.1016/j.intell.2013.07.013.CrossRefGoogle Scholar
  74. Stern, E. (2017). Individual differences in the learning potential of human beings. Npj Science of Learning, 2(1).  https://doi.org/10.1038/s41539-016-0003-0.
  75. Studer-Luethi, B., Jaeggi, S. M., Buschkuehl, M., & Perrig, W. (2012). Influence of neuroticism and conscientiousness on working memory training outcome. Personality and Individual Differences, 53(1), 44–49.  https://doi.org/10.1016/j.paid.2012.02.012.CrossRefGoogle Scholar
  76. Studer-Luethi, B., Bauer, C., & Perrig, W. J. (2016). Working memory training in children: effectiveness depends on temperament. Memory & Cognition, 44(2), 171–186.  https://doi.org/10.3758/s13421-015-0548-9.CrossRefGoogle Scholar
  77. Tamez, E., Myerson, J., & Hale, S. (2012). Contributions of associative learning to age and individual differences in fluid intelligence. Intelligence, 40(5), 518–529.  https://doi.org/10.1016/j.intell.2012.04.004.CrossRefGoogle Scholar
  78. Thompson, T. W., Waskom, M. L., Garel, K.-L. A., Cardenas-Iniguez, C., Reynolds, G. O., Winter, R., et al. (2013). Failure of working memory training to enhance cognition or intelligence. PLoS One, 8(5), e63614.  https://doi.org/10.1371/journal.pone.0063614.CrossRefPubMedPubMedCentralGoogle Scholar
  79. Titz, C., & Karbach, J. (2014). Working memory and executive functions: effects of training on academic achievement. Psychological Research, 78(6), 852–868.  https://doi.org/10.1007/s00426-013-0537-1.CrossRefPubMedGoogle Scholar
  80. Tueller, S. J., Van Dorn, R. A., & Bobashev, G. V. (2016). Visualization of categorical longitudinal and times series data. Methods Report RTI Press, 1–22.  https://doi.org/10.3768/rtipress.2016.mr.0033.1602.
  81. Unsworth, N., Redick, T. S., McMillan, B. D., Hambrick, D. Z., Kane, M. J., & Engle, R. W. (2015). Is playing video games related to cognitive abilities? Psychological Science, 26(6), 759–774.  https://doi.org/10.1177/0956797615570367.CrossRefPubMedGoogle Scholar
  82. Urbánek, T., & Marček, V. (2015). Investigating the effectiveness of working memory training in the context of personality systems interaction theory. Psychological Research, 80(5), 877–888.  https://doi.org/10.1007/s00426-015-0687-4.CrossRefPubMedGoogle Scholar
  83. Verhaeghen, P., & Marcoen, A. (1996). On the mechanisms of plasticity in young and older adults after instruction in the method of loci: evidence for an amplification model. Psychology and Aging, 11(1), 164–178.  https://doi.org/10.1037/0882-7974.11.1.164.CrossRefPubMedGoogle Scholar
  84. von Bastian, C. C., & Eschen, A. (2016). Does working memory training have to be adaptive? Psychological Research, 80(2), 181–194.  https://doi.org/10.1007/s00426-015-0655-z.CrossRefGoogle Scholar
  85. 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.  https://doi.org/10.1016/j.jml.2013.02.002.CrossRefGoogle Scholar
  86. von Bastian, C. C., & Oberauer, K. (2014). Effects and mechanisms of working memory training: a review. Psychological Research, 78(6), 803–820.  https://doi.org/10.1007/s00426-013-0524-6.CrossRefGoogle Scholar
  87. von Bastian, C. C., Langer, N., Jäncke, L., & Oberauer, K. (2013a). Effects of working memory training in young and old adults. Memory & Cognition, 41(4), 611–624.  https://doi.org/10.3758/s13421-012-0280-7.CrossRefGoogle Scholar
  88. von Bastian, C. C., Locher, A., & Ruflin, M. (2013b). Tatool: a Java-based open-source programming framework for psychological studies. Behavior Research Methods, 45(1), 108–115.  https://doi.org/10.3758/s13428-012-0224-y.CrossRefGoogle Scholar
  89. von Bastian, C. C., Guye, S., & De Simoni, C. (2017). How strong is the evidence for the effectiveness of working memory training? In M. F. Bunting, J. M. Novick, M. R. Dougherty, & R. W. Engle (Eds.), Cognitive and working memory training: perspectives from psychology, neuroscience, and human development. Oxford University Press. Manuscript under review.Google Scholar
  90. Wagenmakers, E.-J. (2007). A practical solution to the pervasive problems of p values. Psychonomic Bulletin & Review, 14(5), 779–804.  https://doi.org/10.3758/BF03194105.CrossRefGoogle Scholar
  91. Wetzels, R., & Wagenmakers, E.-J. (2012). A default Bayesian hypothesis test for correlations and partial correlations. Psychonomic Bulletin & Review, 19(6), 1057–1064.  https://doi.org/10.3758/s13423-012-0295-x.CrossRefGoogle Scholar
  92. Wilhelm, O., Hildebrandt, A., & Oberauer, K. (2013). What is working memory capacity, and how can we measure it? Frontiers in Psychology, 4.  https://doi.org/10.3389/fpsyg.2013.00433.
  93. Willis, S. L., & Marsiske, M. (1993). Manual for the Everyday Problems Test. University Park: Department of Human Development and Family Studies, Pennsylvania State University.Google Scholar
  94. Zimmermann, K., von Bastian, C. C., Röcke, C., Martin, M., & Eschen, A. (2016). Transfer after process-based object-location memory training in healthy older adults. Psychology and Aging, 31(7), 798–814.  https://doi.org/10.1037/pag0000123.CrossRefPubMedGoogle Scholar
  95. Zinke, K., Zeintl, M., Rose, N. S., Putzmann, J., Pydde, A., & Kliegel, M. (2014). Working memory training and transfer in older adults: effects of age, baseline performance, and training gains. Developmental Psychology, 50(1), 304–315.  https://doi.org/10.1037/a0032982.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.University Research Priority Program (URPP) “Dynamics of Healthy Aging”University of ZurichZürichSwitzerland
  2. 2.Department of PsychologyUniversity of ZurichZurichSwitzerland
  3. 3.Department of PsychologyBournemouth UniversityPooleUK
  4. 4.Department of PsychologyUniversity of SheffieldSheffieldUK

Personalised recommendations