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A Diffusion Model Approach for Understanding the Impact of 17 Interventions on the Race Implicit Association Test

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posted on 2020-12-02, 18:21 authored by Jessica RöhnerJessica Röhner, Calvin K. Lai

Performance on implicit measures reflects construct-specific and non-construct-specific processes. This creates an interpretive issue for understanding interventions to change implicit measures: change in performance could reflect changes in the constructs-of-interest or changes in other mental processes. We re-analyzed data from six studies (N = 23,342) to examine the process-level effects of 17 interventions and one sham intervention to change race Implicit Association Test (IAT) performance. Diffusion models decompose overall IAT performance (D-scores) into construct-specific (ease of decision-making), and non-construct-specific processes (speed-accuracy tradeoffs, non-decision-related processes like motor execution). Interventions that effectively reduced D-scores changed ease of decision-making on compatible and incompatible trials. They also eliminated differences in speed-accuracy tradeoffs between compatible and incompatible trials. Non-decision-related processes were impacted by two interventions only. There was little evidence that interventions had any long-term effects. These findings highlight the value of diffusion modeling for understanding the mechanisms by which interventions affect implicit measure performance.


Declaration of conflicts of interest

The authors declare no conflicts of interest.

Corresponding author email

Lead author country

  • Germany

Lead author job role

  • Other

Lead author institution

Otto-Friedrich-Universität Bamberg

Human Participants

  • Yes


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