June 18, 2009
In the decade since the Implicit Association Test was introduced, its most surprising and controversial finding is its indication that about 70 percent of those who took a version of the test that measures racial attitudes have an unconscious, or implicit, preference for white people compared to blacks. This contrasts with figures generally under 20 percent for self report, or survey, measures of race bias.
A new study published this week validates those findings, showing that the Implicit Association Test, a psychological tool, has validity in predicting behavior and, in particular, that it has significantly greater validity than self-reports in the socially sensitive topics of race, gender, ethnicity, sexual orientation and age.
The research, published in The Journal of Personality and Social Psychology, is an overview and analysis of 122 published and unpublished reports of 184 different research studies. In this analysis, 85 percent of the studies also included self-reporting measures of the type generally used in surveys. This allowed the researchers, headed by University of Washington psychology Professor Anthony Greenwald, to compare the test's success in predicting social behavior and judgment with the success of self-reports. . .
The research looked at studies covering nine different areas – consumer preference, black-white interracial behavior, personality differences, clinical phenomena, alcohol and drug use, non-racial intergroup behavior, gender and sexual orientation, close relationships and political preferences.
Findings also showed that:
- Across all nine of these areas, measures of the test were useful in predicting social behavior.
- Both the test, which is implicit, and self-reports, which are explicit, had predictive validity independent of each other. This suggests the desirability of using both types of measure in surveys and applied research studies.
- In consumer and political preferences both measures effectively predicted behavior, but self-reports had significantly greater predictive validity.
Read the full story.
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