According to mindset theory, students who believe their personal characteristics can change-that is, those who hold a growth mindset-will achieve more than students who believe their characteristics are fixed. Proponents of the theory have developed interventions to influence students' mindsets, claiming that these interventions lead to large gains in academic achievement. Despite their popularity, the evidence for growth mindset intervention benefits has not been systematically evaluated considering both the quantity and quality of the evidence. Here, we provide such a review by (a) evaluating empirical studies' adherence to a set of best practices essential for drawing causal conclusions and (b) conducting three meta-analyses. When examining all studies (63 studies, N = 97,672), we found major shortcomings in study design, analysis, and reporting, and suggestions of researcher and publication bias: Authors with a financial incentive to report positive findings published significantly larger effects than authors without this incentive. Across all studies, we observed a small overall effect: d¯ = 0.05, 95% CI = [0.02, 0.09], which was nonsignificant after correcting for potential publication bias. No theoretically meaningful moderators were significant. When examining only studies demonstrating the intervention influenced students' mindsets as intended (13 studies, N = 18,355), the effect was nonsignificant: d¯ = 0.04, 95% CI = [-0.01, 0.10]. When examining the highest-quality evidence (6 studies, N = 13,571), the effect was nonsignificant: d¯ = 0.02, 95% CI = [-0.06, 0.10]. We conclude that apparent effects of growth mindset interventions on academic achievement are likely attributable to inadequate study design, reporting flaws, and bias. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

For years, psychologists have wondered why people who are highly skilled in one cognitive domain tend to be skilled in other cognitive domains, too. In this article, we explain how attention control provides a common thread among broad cognitive abilities, including fluid intelligence, working memory capacity, and sensory discrimination. Attention control allows us to pursue our goals despite distractions and temptations, to deviate from the habitual, and to keep information in mind amid a maelstrom of divergent thought. Highlighting results from our lab, we describe the role of attention control in information maintenance and disengagement and how these functions contribute to performance in a variety of complex cognitive tasks. We also describe a recent undertaking in which we developed new and improved attention-control tasks, which had higher reliabilities, stronger intercorrelations, and higher loadings on a common factor than traditional measures. From an applied perspective, these new attention-control tasks show great promise for use in personnel selection assessments. We close by outlining exciting avenues for future research.

Individual differences in the ability to control attention are correlated with a wide range of important outcomes, from academic achievement and job performance to health behaviors and emotion regulation. Nevertheless, the theoretical nature of attention control as a cognitive construct has been the subject of heated debate, spurred on by psychometric issues that have stymied efforts to reliably measure differences in the ability to control attention. For theory to advance, our measures must improve. We introduce three efficient, reliable, and valid tests of attention control that each take less than 3 min to administer: Stroop Squared, Flanker Squared, and Simon Squared. Two studies (online and in-lab) comprising more than 600 participants demonstrate that the three "Squared" tasks have great internal consistency (avg. = .95) and test-retest reliability across sessions (avg. r = .67). Latent variable analyses revealed that the Squared tasks loaded highly on a common factor (avg. loading = .70), which was strongly correlated with an attention control factor based on established measures (avg. r = .81). Moreover, attention control correlated strongly with fluid intelligence, working memory capacity, and processing speed and helped explain their covariation. We found that the Squared attention control tasks accounted for 75% of the variance in multitasking ability at the latent level, and that fluid intelligence, attention control, and processing speed fully accounted for individual differences in multitasking ability. Our results suggest that Stroop Squared, Flanker Squared, and Simon Squared are reliable and valid measures of attention control. The tasks are freely available online: https://osf.io/7q598/. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A hallmark of intelligent behavior is rationality – the disposition and ability to think analytically to make decisions that maximize expected utility or follow the laws of probability. However, the question remains as to whether rationality and intelligence are empirically distinct, as does the question of what cognitive mechanisms underlie individual differences in rationality. In a sample of 331 participants, we assessed the relationship between rationality and intelligence. There was a common ability underpinning performance on some, but not all, rationality tests. Latent factors representing rationality and general intelligence were strongly correlated (r = .54), but their correlation fell well short of unity. Rationality correlated significantly with fluid intelligence (r = .56), working memory capacity (r = .44), and attention control (r = .49). Attention control fully accounted for the relationship between working memory capacity and rationality, and partially accounted for the relationship between fluid intelligence and rationality. We conclude by speculating about factors rationality tests may tap that other cognitive ability tests miss, and outline directions for further research.