Implementing multiple implicit association tests in Qualtrics: A guide and demonstration using balanced identity design theory

Interest in implicit processes, such as attitudes and identities, has grown in behavioral sciences since Greenwald and colleagues (1998) developed and introduced the Implicit Association Test (IAT). The IAT was developed to measure these processes, which has become more accessible with the popularity of Qualtrics as a data collection tool, especially through methods and code provided by Carpenter et al. (2019). They demonstrated how to construct a single IAT for use on the Qualtrics platform, providing research resources for creating IATs to examine concept-pair associations. However, there is no guidance on constructing multiple IATs on survey software platforms for research that requires two or more IATs in a single study. This paper extends Carpenter et al.'s (2019) work by outlining the process of developing, implementing, and utilizing multiple IATs within a single Qualtrics survey. We provide a tutorial using examples from our research using the Balanced Identity Design (BID) framework, including step-by-step written and visual instructions and templates, instructions for planning and building multiple IATs and dynamically presenting them in a single Qualtrics survey and code for processing IAT data. We also demonstrate the utility of the multiple IAT approach by reporting a short study utilizing BID theory wherein we measure implicit racial/ethnic identity, STEM identity, and race/ethnicity-STEM associations in a single study via three IATs.