OBJECTIVE: Racial and ethnic disparities are well documented in psychiatry, yet suboptimal understanding of underlying mechanisms of these disparities undermines diversity, inclusion, and education efforts. Prior research suggests that implicit associations can affect human behavior, which may ultimately influence healthcare disparities. This study investigated whether racial implicit associations exist among medical students and psychiatric physicians and whether race/ethnicity, training level, age, and gender predicted racial implicit associations. METHODS: Participants completed online demographic questions and 3 race Implicit Association Tests (IATs) related to psychiatric diagnosis (psychosis vs. mood disorders), patient compliance (compliance vs. non-compliance), and psychiatric medications (antipsychotics vs. antidepressants). Linear and logistic regression models were used to identify demographic predictors of racial implicit associations. RESULTS: The authors analyzed data from 294 medical students and psychiatric physicians. Participants were more likely to pair faces of Black individuals with words related to psychotic disorders (as opposed to mood disorders), non-compliance (as opposed to compliance), and antipsychotic medications (as opposed to antidepressant medications). Among participants, self-reported White race and higher level of training were the strongest predictors of associating faces of Black individuals with psychotic disorders, even after adjusting for participant's age. CONCLUSIONS: Racial implicit associations were measurable among medical students and psychiatric physicians. Future research should examine (1) the relationship between implicit associations and clinician behavior and (2) the ability of interventions to reduce racial implicit associations in mental healthcare.
OBJECTIVE: Racial and ethnic disparities are well documented in psychiatry, yet suboptimal understanding of underlying mechanisms of these disparities undermines diversity, inclusion, and education efforts. Prior research suggests that implicit associations can affect human behavior, which may ultimately influence healthcare disparities. This study investigated whether racial implicit associations exist among medical students and psychiatric physicians and whether race/ethnicity, training level, age, and gender predicted racial implicit associations. METHODS: Participants completed online demographic questions and 3 race Implicit Association Tests (IATs) related to psychiatric diagnosis (psychosis vs. mood disorders), patient compliance (compliance vs. non-compliance), and psychiatric medications (antipsychotics vs. antidepressants). Linear and logistic regression models were used to identify demographic predictors of racial implicit associations. RESULTS: The authors analyzed data from 294 medical students and psychiatric physicians. Participants were more likely to pair faces of Black individuals with words related to psychotic disorders (as opposed to mood disorders), non-compliance (as opposed to compliance), and antipsychotic medications (as opposed to antidepressant medications). Among participants, self-reported White race and higher level of training were the strongest predictors of associating faces of Black individuals with psychotic disorders, even after adjusting for participant's age. CONCLUSIONS: Racial implicit associations were measurable among medical students and psychiatric physicians. Future research should examine (1) the relationship between implicit associations and clinician behavior and (2) the ability of interventions to reduce racial implicit associations in mental healthcare.
Entities:
Keywords:
Health disparities; Implicit Association Test; Mood disorder; Psychosis; Race implicit bias; Racial discrimination; Treatment adherence
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