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Enhancing the Implicit Association Test: A Four-Step Model to Find Appropriate Stimuli

In: Information Systems and Neuroscience

Author

Listed:
  • Gerhard Brenner

    (University of Applied Sciences)

  • Monika Koller

    (WU Vienna)

  • Peter Walla

    (Webster Vienna Private University
    Newcastle University
    University of Vienna)

Abstract

The Implicit Association Test (IAT) is a promising tool to assess implicit attitudes. Next to neuroscientific methods applied within the field of NeuroIS the IAT helps to overcome limits of traditional approaches, such as self-report studies. Introduced 20 years ago, it has been developed further within subsequent years. However, hardly any attention has been paid to optimize the stimuli sets. This is unfortunate, as if the time span participants need to decode the stimuli varies across the IAT, or if the subjects do not understand the stimuli equally, reaction times can be biased. As an IAT includes 120 measuring points per subject such biases might potentiate across all participants. The results might be biased and neither the researchers nor the participants would recognize such confounding effects. Thus, we focus on the time span between stimulus onset and response and develop a four-step model to create an optimized stimuli set including (1) brainstorming, (2) forming & performing (i.e. pretesting), (3) backward-brainstorming and (4) informing & interviewing.

Suggested Citation

  • Gerhard Brenner & Monika Koller & Peter Walla, 2019. "Enhancing the Implicit Association Test: A Four-Step Model to Find Appropriate Stimuli," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph (ed.), Information Systems and Neuroscience, pages 111-118, Springer.
    • Handle: RePEc:spr:lnichp:978-3-030-01087-4_13
    DOI: 10.1007/978-3-030-01087-4_13
    as

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