Best research practices for using the Implicit Association Test

Anthony G Greenwald, Miguel Brendl, Huajian Cai, Dario Cvencek, John F Dovidio, Malte Friese, Adam Hahn, Eric Hehman, Wilhelm Hofmann, Sean Hughes, Ian Hussey, Christian Jordan, Teri A Kirby, Calvin K Lai, Jonas W B Lang, Kristen P Lindgren, Dominika Maison, Brian D Ostafin, James R Rae, Kate A RatliffAdriaan Spruyt, Reinout W Wiers

Research output: Contribution to journalArticlepeer-review

Abstract

Interest in unintended discrimination that can result from implicit attitudes and stereotypes (implicit biases) has stimulated many research investigations. Much of this research has used the Implicit Association Test (IAT) to measure association strengths that are presumed to underlie implicit biases. It had been more than a decade since the last published treatment of recommended best practices for research using IAT measures. After an initial draft by the first author, and continuing through three subsequent drafts, the 22 authors and 14 commenters contributed extensively to refining the selection and description of recommendation-worthy research practices. Individual judgments of agreement or disagreement were provided by 29 of the 36 authors and commenters. Of the 21 recommended practices for conducting research with IAT measures presented in this article, all but two were endorsed by 90% or more of those who felt knowledgeable enough to express agreement or disagreement; only 4% of the totality of judgments expressed disagreement. For two practices that were retained despite more than two judgments of disagreement (four for one, five for the other), the bases for those disagreements are described in presenting the recommendations. The article additionally provides recommendations for how to report procedures of IAT measures in empirical articles.

Original languageEnglish
JournalBehavior Research Methods
Early online date13 Sep 2021
DOIs
Publication statusE-pub ahead of print - 13 Sep 2021

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