Skip to Main content Skip to Navigation
Reports

Detecting Attitude Change with the Implicit Association Test

Abstract : The Implicit Association Test and its variants have become pervasive measures of attitudes in a variety of domains and contexts. In two experiments, we provide evidence that a recent variant, the Personalized IAT developed by Olson and Fazio (2004) may more accurately detect changes in personal attitudes than the conventional Traditional IAT devised by Greenwald, McGhee, and Schwartz (1998). Our findings suggest that the Personalized IAT may be more sensitive to detecting attitude changes than the Traditional IAT because it is less affected by extrapersonal associations (i. e. salient associations not contributing to personal evaluations of the object). More generally, this research suggests that for attitude domains characterized by potentially strong extrapersonal associations, using the Personalized and Traditional IATs may provide researchers with complementary insights about knowledge structures.
Document type :
Reports
Complete list of metadatas

https://hal-hec.archives-ouvertes.fr/hal-00580139
Contributor : Antoine Haldemann <>
Submitted on : Saturday, March 26, 2011 - 2:01:46 PM
Last modification on : Thursday, January 11, 2018 - 6:19:32 AM

Identifiers

  • HAL Id : hal-00580139, version 1

Collections

Citation

Sandor Czellar, Russell H. Fazio. Detecting Attitude Change with the Implicit Association Test. 2008. ⟨hal-00580139⟩

Share

Metrics

Record views

157