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Cognitive predictors of a common multitasking ability: Contributions from working memory, attention control, and fluid intelligence.
Author(s) -
Thomas S. Redick,
Zach Shipstead,
Matthew E. Meier,
Janelle J. Montroy,
Kenny L. Hicks,
Nash Unsworth,
Michael J. Kane,
David Z. Hambrick,
Randall W. Engle
Publication year - 2016
Publication title -
journal of experimental psychology general
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.521
H-Index - 161
eISSN - 1939-2222
pISSN - 0096-3445
DOI - 10.1037/xge0000219
Subject(s) - human multitasking , psychology , psycinfo , working memory , construct (python library) , cognition , structural equation modeling , task switching , cognitive psychology , variance (accounting) , confirmatory factor analysis , executive functions , developmental psychology , computer science , neuroscience , accounting , medline , machine learning , political science , law , business , programming language
Previous research has identified several cognitive abilities that are important for multitasking, but few studies have attempted to measure a general multitasking ability using a diverse set of multitasks. In the final dataset, 534 young adult subjects completed measures of working memory (WM), attention control, fluid intelligence, and multitasking. Correlations, hierarchical regression analyses, confirmatory factor analyses, structural equation models, and relative weight analyses revealed several key findings. First, although the complex tasks used to assess multitasking differed greatly in their task characteristics and demands, a coherent construct specific to multitasking ability was identified. Second, the cognitive ability predictors accounted for substantial variance in the general multitasking construct, with WM and fluid intelligence accounting for the most multitasking variance compared to attention control. Third, the magnitude of the relationships among the cognitive abilities and multitasking varied as a function of the complexity and structure of the various multitasks assessed. Finally, structural equation models based on a multifaceted model of WM indicated that attention control and capacity fully mediated the WM and multitasking relationship. (PsycINFO Database Record

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