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Best research practices for using the Implicit Association Test
Open accessAbstract
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.
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“Finally, these attitudes may be explicit (consciously accessible and measurable by self-report) or implicit (largely unconscious and testable through indirect measures (e.g., Implicit Association tasks (IAT), Greenwald et al., 2022)).”
From Are Attributions of Consciousness to AI Chatbots Epistemically Innocent? (2026) · cites this paper as Greenwald et al., 2022
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Metadata
- Authors
- Greenwald, A. G., Brendl, M., Cai, H., Cvencek, D., Dovidio, J. F., Friese, M., Hahn, A., Hehman, E., Hofmann, W., Hughes, S., Hussey, I., Jordan, C., Kirby, T. A., Lai, C. K., Lang, J. W. B., Lindgren, K. P., Maison, D., Ostafin, B. D., Rae, J. R., Ratliff, K. A., Spruyt, A., & Wiers, R. W.
- Affiliations
- University of Washington (US)
- Chinese Academy of Sciences (CN)
- Yale University (US)
- Saarland University (DE)
- University of Cologne (DE)
- McGill University (CA)
- Ruhr University Bochum (DE)
- Ghent University (BE)
- Wilfrid Laurier University (CA)
- University of Exeter (GB)
- Washington University in St. Louis (US)
- University of Warsaw (PL)
- University of Groningen (NL)
- University of Massachusetts Amherst (US)
- University of Florida (US)
- University of Amsterdam (NL)
- Corresponding author
- Greenwald, Anthony G.
- ORCID
- Venue
- Behavior Research Methods
- Published
- 2021-09-13
- Volume
- 54
- Issue
- 3
- Pages
- 1161-1180
- ISSN
- 1554-351X (ISSN-L)
- 1554-3528
- PMC
- PMC9170636
- OpenAlex
- W3200635405
- Cited by
- 209
- References
- 66
- Citations by year
- 2026: 49 · 2025: 51 · 2024: 50 · 2023: 37 · 2022: 20
- FWCI
- 37.07
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Behavior Research Methods (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Kölner Universitäts PublikationsServer (Universität zu Köln) (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion, cc-by)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (acceptedVersion, cc-by)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion, cc-by)
- BORIS (University Library Bern) (submittedVersion, cc-by)
- edoc (University of Basel) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Open Research Exeter (University of Exeter) (submittedVersion, cc-by)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Economic and Social Research Council (ES/S00274X/1)
- Topics
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Sociology and Political Science › Racial and Ethnic Identity Research
- Keywords
- Implicit Association Test, implicit bias, implicit attitudes, stereotypes, research best practices, measurement validity, reporting procedures
- MeSH terms
- Association, Attitude, Humans
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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