Characterizing implicit mental health associations across clinical domains

Abstract

Background and objectivesImplicit associations are relatively uncontrollable associations between concepts in memory. The current investigation focuses on implicit associations in four mental health domains (alcohol use, anxiety, depression, and eating disorders) and how these implicit associations: a) relate to explicit associations and b) self-reported clinical symptoms within the same domains, and c) vary based on demographic characteristics (age, gender, race, ethnicity, and education). MethodsParticipants (volunteers over age 18 to a research website) completed implicit association (Implicit Association Tests), explicit association (self + psychopathology or attitudes toward food, using semantic differential items), and symptom measures at the Project Implicit Mental Health website tied to: alcohol use (N = 12,387), anxiety (N = 21,304), depression (N = 24,126), or eating disorders (N = 10,115). ResultsWithin each domain, implicit associations showed small to moderate associations with explicit associations and symptoms, and predicted self-reported symptoms beyond explicit associations. In general, implicit association strength varied little by race and ethnicity, but showed small ties to age, gender, and education. LimitationsThis research was conducted on a public research and education website, where participants could take more than one of the studies. ConclusionsAmong a large and diverse sample, implicit associations in the four domains are congruent with explicit associations and self-reported symptoms, and also add to our prediction of self-reported symptoms over and above explicit associations, pointing to the potential future clinical utility and validity of using implicit association measures with diverse populations.