Implicit association tests for all: Using iatgen for non-English and offline samples
Abstract
The Implicit Association Test (IAT) has become an invaluable tool for researchers in many fields. The IAT is a sorting task that measures the strength of automatic associations between targets (e.g., flowers / insects) and attributes (e.g., pleasant / unpleasant). Several programs exist to create and run IAT studies, and each has unique advantages and disadvantages. Yet most share the same limitations: being general-purpose data collection tools that require time to master, requiring extra steps to run online (e.g., deploying a web server), and having no IAT-data analysis features. This increases researcher reliance on pre-made templates that typically operate only in English and are difficult to translate. Iatgen addresses some of these issues by allowing researchers to design and analyze IATs through a simple web-interface, to easily combine IATs with experimental manipulations or other measures in Qualtrics, and to analyze data using the same web-interface. However, until recently, the problem of monolingual, English-only capability remained. In this paper, we introduce iatgen’s new translation functionality, which allows users to create non-English IATs using the web-based iatgen Shiny app and the tr.iatgen R package. Users are invited to contribute to the translation repository in GitHub by submitting and reviewing IAT translations. We also describe a method for deploying Qualtrics-based IATs in offline environments. We hope this increased functionality will facilitate cross-cultural research and reduce the negative effects of disproportionately Western, educated, industrialized, rich, and democratic (WEIRD) samples.
Article Details
Authors (7)
João O. Santos
Emerson Do Bú
Tomohiro Hara
Cristina Mendonça
Sara Hagá
Ruth Pogacar
Michal Kouril