Literature DB >> 32700925

A toolbox approach to improving the measurement of attention control.

Christopher Draheim1, Jason S Tsukahara1, Jessie D Martin1, Cody A Mashburn1, Randall W Engle1.   

Abstract

Cognitive tasks that produce reliable and robust effects at the group level often fail to yield reliable and valid individual differences. An ongoing debate among attention researchers is whether conflict resolution mechanisms are task-specific or domain-general, and the lack of correlation between most attention measures seems to favor the view that attention control is not a unitary concept. We have argued that the use of difference scores, particularly in reaction time (RT), is the primary cause of null and conflicting results at the individual differences level, and that methodological issues with existing tasks preclude making strong theoretical conclusions. The present article is an empirical test of this view in which we used a toolbox approach to develop and validate new tasks hypothesized to reflect attention processes. Here, we administered existing, modified, and new attention tasks to over 400 participants (final N = 396). Compared with the traditional Stroop and flanker tasks, performance on the accuracy-based measures was more reliable, had stronger intercorrelations, formed a more coherent latent factor, and had stronger associations to measures of working memory capacity and fluid intelligence. Further, attention control fully accounted for the relationship between working memory capacity and fluid intelligence. These results show that accuracy-based measures can be better suited to individual differences investigations than traditional RT tasks, particularly when the goal is to maximize prediction. We conclude that attention control is a unitary concept. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Entities:  

Mesh:

Year:  2020        PMID: 32700925     DOI: 10.1037/xge0000783

Source DB:  PubMed          Journal:  J Exp Psychol Gen        ISSN: 0022-1015


  17 in total

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9.  Do Executive Attentional Processes Uniquely or Commonly Explain Psychometric g and Correlations in the Positive Manifold? A Structural Equation Modeling and Network-Analysis Approach to Investigate the Process Overlap Theory.

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