Using 21st c technologies to analyze the impact of racism on health: The implicit association test (IAT), web-based surveys, and explicit measures of racial discrimination

A growing body of research demonstrates links between self-reported experiences of discrimination and health. Yet is reliance on what people self-report sufficient? New research on implicit social cognition and epidemiology suggests implicit measures of discrimination could perhaps usefully be combined with explicit measures to provide a more complete picture of the effects of discrimination on health. We accordingly used the Implicit Association Test (IAT), a computer-based reaction-time methodology developed by social psychologists to study phenomena that lie outside the reaches of introspective access, in conjunction with an explicit validated “Experience of Discrimination” (EOD) self-report measure. In a pilot study of a random sample of members of a community health center, we found that: (1) the IAT and EOD were not correlated; and (2) black participants explicitly reported higher levels of discrimination against blacks as a group than for themselves personally, whereas on the IAT they showed equally high associations for discrimination against blacks as a group and themselves personally, suggesting the IAT picked up experiences of discrimination the EOD did not. We will also report preliminary results of a newly completed web-based survey investigating associations of the IAT and EOD with several measures of health status and health behaviors. Together, the results suggest that new technologies, tapping implicit cognition, can feasibly be used in epidemiologic and other population-based research and may potentially lead to new insights into the impact of discrimination on health.