Manipulating the role of cognitive control while taking the implicit association test

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t a r t i c l e i n f o The Implicit Association Test (IAT) is one of the most widely used methods for measuring attitudes in the be-havioral and social sciences. Recent studies have found that individual differences in cognitive control correlate with IAT scores. However, these studies did not collect independent measures of attitude, which makes it difficult to isolate the construct of attitude separate from cognitive control. Furthermore, no study has examined whether the role of cognitive control can be manipulated, which is necessary to establish a causal link between cognitive control and IAT performance. By collecting independent measures of attitude (explicit attitude ratings and the Affect Misattribution Procedure: AMP), Experiment 1 factored out the role of attitude for two different IATs and still found a relationship between IAT scores and cognitive control (Stroop and stop-signal). Experiments 2 and 3 manipulated the role of cognitive control through instructions and feedback regarding the race IAT's measurement goal. These manipulations increased average IAT scores (i.e., stronger preference for whites), increased the relationship with cognitive control (Stroop), and decreased the relationship with attitude (AMP). These results demonstrate that cognitive control influences IAT performance rather than merely correlating with IAT performance. Introduction Over the last decade, there has been a rapid increase in the use of implicit measures in psychological research, especially for the measurement of attitudes. The popularity of implicit measures is due in large part to the recognition that explicit measures are prone to a variety of response biases. This is especially true when the attitudes being assessed are socially unacceptable, such as racial prejudice. Responses to explicit measures (e.g., survey response scales) might be disingenu-ous, but responses to implicit measures are less susceptible to fakery because they measure automatic or reflexive responses elicited by stimuli that are congruent or incongruent with one's attitudes. Specifically, implicit measures assess attitudes by tapping associations between the relevant group or category (e.g., insects) and the affect associated with that group or category (e.g., insects are bad). These associations can be viewed either as implicit attitudes (Greenwald et al., 2002) or as the implicit …