Table 1 describes demographic characteristics of the participants stratified by whether they were randomly assigned a black or white patient. Participants assigned black vs white patients did not differ significantly, except that first- and second-year residents were more likely to be assigned white patients. Year of residency did not have any significant effect on either likelihood of recommending thrombolysis (chi-square P = .98) or on IAT scores however. Table 1 shows mean IAT scores for all three IATs by participants’ demographic characteristics. Physician race was the only consistent demographic predictor of IAT scores. Black physicians had mean scores on all three IATs near zero, whereas all other groups had scores in the positive, prowhite range. Emergency medicine residents also had somewhat less prowhite IAT sores on the general cooperativeness IAT. There was no difference in the IAT scores of participants randomized to black versus white patient vignettes.
Physicians’ Explicit and Implicit Racial Biases
On the measures of explicit bias, participants expressed equal preference for black and white Americans on the 5-point scale of race preference (mean difference = 0.03, P = .36) and on the 10-point thermometer scale measuring warmth toward black and white Americans separately (mean difference = 0.04, P = .61). They reported black and white patients to be equally cooperative on a 5-point scale of cooperativeness with medical procedures (mean difference = 0.01, P = 1.00) and on a 10-point thermometer scale measuring cooperativeness separately for black and white patients (mean difference = 0.08, P = .49).
On the measures of implicit bias, all three IATs showed statistically significant effects (P < .001), with stronger associations of negative attributes (e.g., bad and uncooperative) to blacks than to whites. Figure 2 displays a graph of the magnitude of physicians’ bias on the 4 explicit measures (top half) and 3 implicit measures (bottom half). Because measures of explicit bias (5- and 10-point scales) and implicit bias (reaction time scores ranging from −1.01 to +1.35) were on different scales, the magnitude of physicians’ bias across the seven measures could only be directly compared by converting them all to the same metric—Cohen’s effect size d. Cohen’s d is conceptually defined as the magnitude of an effect independent of sample size (see conversion formula at the bottom of Fig. 2) and is widely used in empirical research and meta-analysis in the behavioral sciences. Cohen’s d values range in size from small (0.20), to medium (0.50), and large (0.80).25 As shown in Figure 2, none of the explicit effects approached the cutoff for a small effect. In contrast, all of the implicit effects were medium or large in magnitude.
Aggregate scores on the three separate IATs were all somewhat correlated (average pairwise correlation r = .32, P = .001). We found some correlation between implicit bias (IAT score) and explicit bias (composite 5-point scale and 10-point feeling thermometer) for general racial preference (r = .28, P = .001) and no correlation for cooperativeness with medical procedures (r = .05, P = .50).
Diagnosis of CAD and Treatment with Thrombolysis
On a scale from 1 (less than 20% likely) to 5 (more than 80% likely), physicians were more likely to diagnose black patients (M = 4.08) than white patients (M = 3.71) with CAD as a cause of their chest pain (P = .02). However, participants were equally likely to give thrombolysis for black (52%) and white (48%) patients (chi-square P = .68). In absolute numbers 29.8% (33/112) of physicians who saw a white patient vignette thought he was very likely to have CAD versus 40.1% (43/108) for black patients. Within this subgroup 58.2% of physicians were very likely to offer white patients thrombolysis versus 42.7% for black patients (P = .12) (results not shown). Using the delta score (z-score relating likelihood of diagnosis and treatment) we were able to adjust for covariates and show a racial disparity in thrombolysis relative to CAD diagnosis. For blacks, delta was 0.11, indicating lower likelihood of thrombolysis relative to the physician’s perception of the likelihood of acute myocardial infarction. For whites, delta was −0.14, indicating higher likelihood of thrombolysis (P = .06).
Implicit (But Not Explicit) Bias Predicts Differences in Physicians’ Thrombolysis Decisions
Physicians’ explicit (self-reported) attitudes toward patients (preference) or stereotypes about cooperativeness by race did not influence their decision to give thrombolysis for black versus white patients. A moderated multiple linear regression analysis showed no evidence of an interaction between self-reported attitude and patient race on thrombolysis recommendation (P = .82) (results not shown). This result remained nonsignificant after controlling for physicians’ implicit bias, race, sex, socioeconomic status (SES), and belief in thrombolysis effectiveness (P = .64).
Physicians’ implicit biases, however, showed strong associations with their decisions to give thrombolysis. Figure 3 illustrates how each of the three IAT results and the combined IAT composite predicted thrombolysis decisions for black and white patients. Subpanel A shows that as the degree of antiblack bias on the race preference IAT increased, recommendations for thrombolysis for black patients decreased. The interaction between implicit antiblack bias and patient race on treatment recommendation was significant (P = .009). After controlling for physicians’ explicit race bias, race, sex, SES, and belief in thrombolysis effectiveness, the interaction effect of patient race and thrombolysis remained significant. A composite IAT measure combining all three IATs (race, attitude, and stereotypes) showed the same pattern (subpanel D) and was statistically significant both with and without the covariates included in the model (P = .04). The same general pattern also held for the medical cooperativeness IAT (subpanel C); however, the interaction was not statistically significant (P =.21).
Participants Who Were Aware of the Study’s Purpose
Results presented above excluded the 67 participants who reported some awareness of the nature of the study. Additional analyses including these 67 aware physicians demonstrated a two-way interaction between awareness and IAT score on thrombolysis recommendation (P = .001) (Fig. 4). As unaware physicians’ bias on the composite IAT variable increased, their likelihood of recommending thrombolysis to black patients decreased, as described above. In contrast, increase in bias among aware physicians was associated with more thrombolysis for black patients. All P values remained significant after adjusting for covariates and the same general pattern held for all three IATs.
Before completing the IAT section of the study, 60.5% of physicians agreed or strongly agreed with the statement: “Subconscious biases about patients based on their race may affect the way I make decisions about their care without my realizing it.” When shown the same statement after taking the IATs, 71.6% of physicians agreed or strongly agreed with this statement (difference in mean 5-point score = 0.33, P < .001 by paired t test). Meanwhile 74.8% felt that taking IATs is a worthwhile experience for physicians, and 76.1% felt that learning more about unconscious biases could improve their care of patients.