Survey-software implicit association tests: A methodological and empirical analysis
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Survey-software implicit association tests: A methodological and empirical analysis Thomas P. Carpenter 1 & Ruth Pogacar 2 & Chris Pullig 3 & Michal Kouril 4,5 & Stephen Aguilar 6 & Jordan LaBouff 7 & Naomi Isenberg 1 & Alek Chakroff 8
# The Psychonomic Society, Inc. 2019
Abstract The implicit association test (IAT) is widely used in psychology. Unfortunately, the IAT cannot be run within online surveys, requiring researchers who conduct online surveys to rely on third-party tools. We introduce a novel method for constructing IATs using online survey software (Qualtrics); we then empirically assess its validity. Study 1 (student n = 239) revealed good psychometric properties, expected IAT effects, and expected correlations with explicit measures for survey-software IATs. Study 2 (MTurk n = 818) showed predicted IAT effects across four survey-software IATs (ds = 0.82 [Black–White IAT] to 2.13 [insect–flower IAT]). Study 3 (MTurk n = 270) compared survey-software IATs and IATs run via Inquisit, yielding nearly identical results and intercorrelations that would be expected for identical IATs. Survey-software IATs appear to be reliable and valid, offer numerous advantages, and make IATs accessible for researchers who use survey software to conduct online research. We present all the materials, links to tutorials, and an open-source tool that rapidly automates survey-software IAT construction and analysis. Keywords Implicit association test . Online research . Implicit measures
The past two decades have seen widespread use of the implicit association test (IAT; Greenwald, McGhee, & Schwartz, 1998). The IAT assesses mental associations via a stimulussorting task (e.g., valenced associations with race, gender, etc.) and predicts cognition, affect, and behavior (Greenwald, Poehlman, Uhlmann, & Banaji, 2009). The IAT has had a major impact on psychology, spawning a vast literature and making contributions to areas such as prejudice
* Thomas P. Carpenter [email protected] 1
Seattle Pacific University, Seattle, WA, USA
2
University of Calgary, Calgary, Alberta, Canada
3
Baylor University, Waco, TX, USA
4
Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
5
University of Cincinnati College of Medicine, Cincinnati, OH, USA
6
University of Southern California, Los Angeles, CA, USA
7
University of Maine, Orono, ME, USA
8
Harvard University, Cambridge, MA, USA
(Fazio & Olson, 2003), preference (Friese, Wänke, & Plessner, 2006), politics (Nosek, Banaji, & Greenwald, 2002), morality (Marquardt & Hoeger, 2009), suicidality (Nock et al., 2010), and personality (Fatfouta & SchröderAbé, 2018). Trends indicate that usage is likely to increase in the coming years (Greenwald & Banaji, 2017). The past decade has also seen the proliferation of online data collection. Online studies allow easy access to large, high-powered samples (Buhrmester, Talaifar, & Gosling, 2018; Paolacci & Chandler, 2014). Unfortunately, online platforms favor self-report methods, offering limited options for researchers who wish t
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