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


Guye, Sabrina; De Simoni, Carla; von Bastian, Claudia C (2017). Do Individual Differences Predict Change in Cognitive Training Performance? A Latent Growth Curve Modeling Approach. Journal of Cognitive Enhancement, 1(4):374-393.

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.

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.

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Additional indexing

Item Type:Journal Article, not_refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
08 Research Priority Programs > Dynamics of Healthy Aging
Dewey Decimal Classification:150 Psychology
Uncontrolled Keywords:DoktoratPsych Erstautor
Language:English
Date:1 December 2017
Deposited On:12 Dec 2018 16:26
Last Modified:08 May 2019 12:49
Publisher:Springer
ISSN:2509-3304
OA Status:Closed
Publisher DOI:https://doi.org/10.1007/s41465-017-0049-9

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