Unconscious Bias in the Medical Workplace

Alan Wasserstein, MDUniversity of Pennsylvania

February 2, 2016

Conscious and unconscious bias

• Conscious (or explicit) bias has declined in the US in the past 50 years – in a 2007 survey, 13% of whites self-identified as racially biased

• But a majority has unconscious (or implicit) bias, bias that expresses itself in behaviors rather than verbally, in feelings of anxiety and discomfort rather than in words of hatred or contempt

Impact of unconscious bias in medicine

• Hiring and promotions in academic medicine

• Racial and gender disparities in medical care

Outline of this talk

• The social psychology of unconscious bias

• Measuring unconscious bias• Unconscious bias and promotion

(mostly gender)• Unconscious bias and health disparities

(mostly race)• Overcoming unconscious bias

Some principles of social psychology

Schemas

--deeply embedded generalizations about the environment--organizes and simplifies complex situations and gives people control. --adaptive (evolutionarily useful). Help to make quick decisions

Definition stereotyping

Using social categories (e.g. race, sex, or gender orientation) to characterize and make judgments about others

More about schemas

≠Conscious beliefs

Unconscious reactions & behavior

Verbal

Positives

Nonverbal

Negatives

Explicit cognition

Slow-learningFast-binding

Implicit cognition

Early determination of unconscious schemas

Examples:--watching mommy serve daddy at the dinner table, watching daddy pay the check at a restaurant --firmly embedded before age 5

Outgroups vs Ingroups

• Simply dividing people into us vs. them leads to bias. People divided randomly into workgroups feel their group is outperforming the other groups!

• People are most comfortable with people like themselves.

• Members of out-groups are likely to be seen as homogeneous (stereotyping), in-groups as individuals

In-groups and out-groups

• Healthcare providers are likely to be white and middle or upper class.

• They are likely to be more comfortable with people like themselves

• They are likely to have implicit biases toward minorities and the poor

Familiar explicit biases

– Women: Communal traits - nurturing, nice, supportive, helpful, sympathetic

– Men: Agentic traits - decisive, inventive, strong, forceful, independent

– White: Educated, intelligent, successful, adherent

– Black or other minority: Poor, uneducated, aggressive, lazy, non-adherent

Manifestations of implicit bias

• More behavioral rather than verbal, such as measures of interest (eye contact) or anxiety (eye blinking)

• Implicit bias is expressed and perceived outside of conscious awareness

A theory of racial misunderstanding

• Blacks have heightened attentiveness and sensitivity to nonverbal cues of bias

• Whites are unconscious of their bias and explicitly try to be “colorblind” about race, but their unconscious bias may manifest in nonverbal behaviors

• No wonder blacks don’t trust whites and, more than whites, believe that racism remains a significant problem

The Goldberg Paradigm (1968)

Student participants evaluated identical essays, differing only in the name of the author: male or female. ‘Women’ received lower evaluations unless the essay was on a feminine topic.

CAGeorge

Mary

Evaluation of Identical Resumes: Race

• Applicants with African-American-sounding names had to send 15 resumes to get a callback, versus 10 for White-sounding names

• “White” names yielded as many callbacks as “Black” names with 8 additional years of experience

• The higher the resume quality, the larger the gap

Greg

Jamal

Bertrand & Mullainathan (2004) Poverty Action Lab, 3, 1-27.

Teacher evaluations• Four on-line course discussion groups,

two led by a man and two by a woman• In two of the groups, the discussion

leader identified him- or herself as of opposite gender

• There was no difference in course ratings between the male and female teachers

• Student ratings higher for the “man”•

Symphony orchestra auditions

Blinded auditions have increased representation of women

Measuring unconscious bias

Unconscious (implicit) bias can be measured with widely available web-based tools and is widespread, despite a decline in self-reported (conscious or explicit) bias and increase in egalitarian and unprejudiced conscious beliefs

Basis of the implicit association test

“The IAT asks you to pair two concepts (e.g., young and good, or elderly and good). The more closely associated the two concepts are, the easier it is to respond to them as a single unit. So, if young and good are strongly associated, it should be easier to respond faster when you are asked to give the same response (i.e. the 'E' or 'I' key) to these two. If elderly and good are not so strongly associated, it should be harder to respond fast when they are paired. This gives a measure of how strongly associated the two types of concepts are. The more associated, the more rapidly you should be able to respond.”

Take the IAT

https://implicit.harvard.edu/implicit/

Bias identified by IAT

Banaji, a social psychologist at Harvard, has found the majority of all subjects test as biased against people who are black, gay, elderly, and Arab Muslim.

Whites largely show preference for whites. But many others exhibit bias against their own group:

About half of blacks test negative toward blacks; 36 percent of Arab Muslims test negative to Arab Muslim; and 38 percent of gays show an automatic preference for heterosexuals.

This observation fits with the fact that women, like men, evaluate women’s performances or dossiers lower than men’s.

Boarding buses with fare cards out of money

• Bus drivers were twice as willing to let white testers ride free as black testers (72% versus 36% of the time). Bus drivers showed relative favoritism toward testers who shared their race, but even black drivers still favored white testers over black testers (allowing free rides 83% versus 68% of the time).

Problems with the test

• Reproducibility• Order effect• In-group influence

The most important question:

Does the implicit association test correlate with behavior in the real world?

“Shooter Bias” studies

• 2005: 50 police patrol officers, mostly white, in computer simulated shoot-don’t shoot scenarios. Some officers were more likely to shoot unarmed black than unarmed white suspects. With training or repeated trials they were able to eliminate this bias

Shooter bias, continued

• 2009: 237 police officers, diverse jobs, mostly white, and community controls. Police were slower to make correct decisions when faced with unarmed black or armed white men, but showed no bias in the decision to shoot. Community controls showed a clear tendency to shoot at black targets.

• “We have tested thousands of subjects with consistent results. Only police officers showed no bias in the decision to shoot.” – lead investigator, cited in The New York Times

• Note the discrepancy between rapidity of association (as in the implicit association test) and the decision to shoot. Raising the question of relevance of the IAT to the real world, and of the benefit of training

Does the IAT indicate that you are “prejudiced”?

Using and Misusing the IAT

To guide personal decisions, e.g., should I go into science

To guide judgments about others, e.g., should that person be excluded from a hiring, promotion or awards decision

Unconscious bias and hiring and promotions in medicine

The glass ceiling at an Ivy League medical school: proportion of

women faculty by rank

• Assistant professor: 38%

• Associate professor: 26%

• Professor: 15%

Glass ceiling for women or minorities…..

….Glass escalator for men or majorities

The importance of diversity

• Equity and justice• Broaden the talent pool from which to recruit• Diverse groups are more creative and

effective than homogeneous groups

Racial Diversity and Jury Deliberations

Sommers (2006) Journal of Personality and Social Psychology, 90 (4), 597-612.

Schemas bias evaluation of performance

• Women and (past) work performed by women typically receive lower evaluations than men and work performed by men (by both men and women evaluators).

• Lower expectations of (future) professional competence bias interpretation of actual performance.

Lowered success rate

Evaluation bias

Performance is underestimated

Accumulation of disadvantage

Gender / race

schemasLack of

critical mass

Self-reinforcing cycle(from U Mich website)

Computer simulation of cumulative advantage in an organization

• 8 levels: 500 employees at bottom; 10 at top; 50% favored and 50% unfavored

• Evaluation scores normally distributed; highest scores promoted

• 15% attrition until organization staffed with all new employees

• “Bias” points given to favored group:– 5% = 29% less favored group at top; 58% bottom– 1% = 35% less favored group at top; 53% at bottom(The favored group could be men, whites, higher

socioeconomic status, LGBT, etc.)

Martell RF et al. Male-female differences: A computer simulation. Am Psychol 1996;51:157-158

Trivial bias may have large effect on disfavored groups within

organizations

0

10

20

30

40

50

60

70

1 2 3 4 5 6 7 8

0%1%5%

Level

% W

Wenneras and Wold, Nature, 1997

22.12.22.32.42.52.62.72.82.93

0-19 20-39 40-59 60-99 >99Total impact points

Com

pete

nce

scor

e

menwomen

Subtle gatekeeping bias

Shorter (less persuasive)

More with minimal assurance

More with gender terms : “intelligent young lady”; “insightful woman”

More stereotypic adjectives : “Compassionate,” “related well…” versus

“successful,” “accomplished”

More with grindstone adjectives : “hardworking,” “dependable,”

“conscientious”

Fewer standout adjectives : “outstanding,” “excellent”

More faint praise : “It’s amazing how much she has accomplished.”

More doubt raisers : “It appears her health is stable.”

Trix F, Psenka C. Exploring the color of glass: Letters of recommendation for female and male medical faculty. Discourse & Soc 2003;14:191-220.

Authors reviewed 312 letters of recommendation for medical faculty hired at large U.S. medical school. Letters for women vs men:

Semantic realms following possessive (e.g. “her training”; “his research”)

0

10

20

30

40

50

60

TrainingTeachingApplicResearchSkills/AbilCareer

FemaleMale

Distinctive semantic realms following possessive (continued)

0

5

10

15

20

25

Personal

PubsCV Patients

Colleagues

FemaleMale

Shifting standards

People shift standards to justify a “reasonable” choice:

• Subjects told to choose between two candidates on basis of education and experience; one candidate had more education and one had more experience

• When given only initials, candidate with more education was chosen 76% of the time and education was rated most important (48%)

Shifting standards (cont’d)

• When male name was given to candidate with more education, male was again preferred by 75%

• But when female name was given to the resume with more education and male name to the resume with more experience, less than half the evaluators picked the person with more education (43%) and less than a quarter said that education was the most important characteristic (22%)

Norton MI, Vandello JA, Darley JM. Casuistry and social category bias. J Pers & Soc Psych 2004;87:817-831.

Having time to focus reduces activation of schema

People are more likely to stereotype when they are distracted, tired, rushed, or otherwise cognitively burdened:

Dossiers of men and women:

- rated comparably during low attentional demand

- but men’s dossiers rated higher than women’s during high attentional demand

Conclusion:

When multi-tasking and pressed for time, evaluation defaults to prescriptive beliefs

Martell RF et al. Male-female differences: A computer simulation. Am Psychol 1996;51:157-158.

Ambiguous qualifications and selection decisions

Dovidio and Gaertner 2000

• White students in 1999 reported less racial prejudice than in 1989

• In both time periods, they recommended whites and blacks equally often when qualifications were clearly strong or weak

• When qualifications were ambiguous, they recommended whites more often

NIH Pioneer Awards, First Round: What went wrong

In the first year of the NIH Director’s Pioneer Awards, only men were chosen. Why?

• No face-to-face discussion about applicants• Subjective assessment of “leadership,” “potential,” and “risk

taking” • Emphasis on self-promotion: in-person presentations • Weight given to letters of recommendation• Time pressure on evaluators• 60/64 judges were men

FYI: 20% of applicants, 13% of those who underwent external scientific review, 2 of 21 finalists, and 0 of 9 awardees were women.

Carnes M, Geller S, Fine E, Sheridan J, Handelsman J. J Women’s Health 2005;14(8): 684-691.

NIH Pioneer Awards, second round:What went right

Second year of Pioneer Awards, 5 of 13 awardees were women. Why?

1. Reduced time pressure on reviewers.

2. Removed references to ‘high-risk’ research, ‘intrinsic’ leadership, and ‘potential’

3. Higher proportion women in applicant pool – 26%

4. More women on the review committee.

5. Women were specifically encouraged to apply.

* Carnes M. Nature 2006;442(24):868.

Health care disparities

Evidence of Racial/Ethnic Differencesin Cardiac Care, 1984-2001

68 studies find racial/ethnic differences in

care (84%)

11 studies find no

racial/ethnic differences in

care(14%)

2 studies find the

racial/ethnic minority group more likely to

receive appropriate care (2%)

All Studies (n=81)

Strong Studies (n=44)

Strong Clinical Studies (n=24)

39 studies find racial/ethnic differences in

care (89%)

20 studies find racial/ethnic differences in care (83%)

4 studies find no

racial/ethnic differences in

care(9%)

1 study finds the

racial/ethnic minority group more likely to

receive appropriate care (2%)

4 studies find no

racial/ethnic differences in

care(17%)

Source: Kaiser Family Foundation/American College of Cardiology Foundation, Racial/Ethnic Differences in Cardiac Care:The Weight of the Evidence, 2002.

A seminal study• At a national meeting, primary care

physicians were shown videotapes of actors complaining of chest pain.

• Though the correct diagnosis of CAD was made, blacks and women were less likely to be referred for further testing

• Unconscious bias was not measured. A role for over-application of population statistics was likely, at least for women– Schulman, et al NEJM, 1999

Causes of health disparities

• Socioeconomic differences, with differential access to care and reduced health literacy

• Differential exposure to health hazards or stressors

• Differences in health-related behaviors• Explicit and implicit provider bias

4 ways clinicians can be biased

• Use stereotypes to make clinical decisions

• Differential weight of findings depending on patient history and appearance

• Overt moral rationing: conscious decisions based on estimate of adherence, social support, etc

• Unconscious behaviors affecting patient decisions, adherence, satisfaction

Physician bias, explicit and implicit

• Physicians have little explicit racial bias, but they do have explicit bias about adherence among blacks

• Physician implicit bias has been linked to treatment decisions in clinical vignettes and may affect doctor-patient communication and in real life

• Implicit bias is harder to consciously control than explicit bias

Why healthcare providers default to stereotypes

• Stereotypes are labor-saving shortcuts in clinical decision-making

• Seeing people as individuals takes extra cognitive work

• More likely to default to stereotypes if we are busy with other tasks, distracted, tired, under time pressure, or anxious

• These are our normal working conditions

“Racial profiling” (i.e. population statistics) is a

clinical tool• Medical education and tradition have

encouraged stereotyping• Role of age, race and gender in medical

diagnosis: population statistics are overapplied and function much like stereotypes (racial and gender profiling)

Examples of bias leading to disparities

• Providers rated their black patients as less educated and in less demanding careers though the medical record explicitly indicated education and occupation were equal to whites

• In another study, providers rated black patients more likely to abuse drugs independent of age, gender, income, acuity

• In a third study blacks were less likely to get CABG when controlling for other factors; only race could be implicated

Unconscious bias influencing medical decision-making

A negative IAT/vignette study

• 215 Johns Hopkins acute care surgical clinicians (attending, fellow, resident). Responses to eight clinical vignettes were compared with IAT scores

• There was NO association in multivariable analysis of unconscious race or social class bias on IAT with vignette-based clinical assessments– JAMA Surgery 2015;150:457-464

Pediatric case vignettes• 95 pediatricians, 58% response rate, 65

% women. 4 case vignettes on UTI, ADHD, asthma, and post-operative pain

• There was no correlation of IAT scores with racial preference in the vignettes EXCEPT in post op pain, where pro-White bias on the IAT correlated with lower likelihood of giving narcotics to a black 14 yo in the ED

- Sabin et al, Am J Public Health, 2012

Conclusion: conflicting evidence of role of implicit

bias in vignette studies

Physician implicit bias and outcomes of care

• 138 PCPs and 4794 patients with HTN• Black pts had treatment intensification

equivalent to whites but lower adherence and worse HTN

• Latino pts had equivalent treatment intensification, lower adherence, but similar HTN to whites (?)

• No correlation of clinician implicit bias with any outcome

Minority perceptions of care

• Minorities judge that their care is inferior to whites’

• Minorities rate interpersonal quality of care more negatively than do whites

• Minorities experience poorer communication with physicians, particularly in race-discordant relationships

When counseled on options for treatment of lung cancer,

black patients were more likely than white patients to

feel…• Less supportiveness• Less partnership• Less information received• Less trust

– Gordon et al, J Clin Oncol 2006

When treated by black doctors, black patients are…

• More satisfied with the encounter and with their medical care

• More likely to schedule and keep appts

Implicit bias and perceptions of care

• 134 clinicians and 2908 patients• Low clinician explicit bias• Clinicians with more implicit bias were

rated lower in patient centered care by black compared to white patients

• Latinos rated clinicians lower than did blacks and whites but there was no relation to implicit bias– Blair et al, Ann Fam Med 2013

Another study of implicit bias and patient perceptions

• 40 PCPs and 269 patients in urban community practices

• IATs for race and for adherence by race• Audiotape measures of visit

communication and patient ratings– Cooper et al, Am J Public Health, 2012

Increased race bias was associated with:

---for blacks: less happy with the visit and less perceived respect from the clinician; less liking of, confidence in, and recommending of the clinician --for whites: increased perceived respect and believing they are liked, but less perceiving clinician as participatory

Increased adherence stereotyping was associated

with:• For blacks: longer visits and slower

pace of dialogue, less patient centered dialogue, lower trust and confidence in clinician

• For whites: shorter visits, more rapid pace of dialog, less clinician verbal dominance, more patient centered dialog

• For both, less involvement in decisions

• “Blacks are at greater risk than whites for narrowly biomedically focused visits with restricted patient input in the psychosocial and lifestyle realm.”

• Many studies have shown that patient centered communication is associated with trust, recall of information, adherence, satisfaction, continuity of care, and outcomes

Conclusion

• The theoretical case for a role of implicit bias in healthcare disparities is excellent

• Vignette studies are contradictory• There is little evidence, so far, of effect

on clinical decisions in practice• Effects of implicit bias on doctor-patient

communications are very suggestive and predict an effect on outcomes (though that has not yet been shown)

Mitigating unconscious bias

Mitigating the influence of schemas

People can learn to reduce their reliance on schemas, e.g. by conscious effort or by using imagery

Heilman ME. The impact of situational factors on personnel decisions concerning women: varying the sex composition of the applicant pool. Organizational Behavior & Human Performance 1980;26:386-395. Sackett PR, Dubois CL, Noe AW. Tokenism in performance evaluation: the effects of work group representation on male-female and white-black differences in performance ratings. J Applied Psych 1991;76:263-267. Blair IV, Banaji MR. Automatic and controlled processes in stereotype priming. J Pers & Soc Psych 1996;70:1142-1163.

Mental imagery can moderate implicit gender stereotypes

Implicit association test before and after intervention:– Counterstereotype imagery (“imagine a strong woman”),

– Stereotype imagery (“imagine a storybook princess or Victorian woman”), or

– Neutral imagery (“imagine a house”)

Results: Significant reduction in measures associated with unconscious gender assumptions following counterstereotype imagery

Blair IV, Ma JE, Lenton AP. Imagining stereotypes away: the moderation of implicit stereotypes through mental imagery. J Pers Soc Psychol. 2001;81:828–41

Images of admired and disliked individuals combat automatic attitudes

Implicit association test after pictures of 40 well known individuals; 10 each in 4 categories:

• Admired black (e.g. Denzel Washington)• Admired white (e.g. Tom Hanks)• Disliked black (e.g. Mike Tyson)• Disliked white (e.g. Jeffrey Dahmer)

White preference effect smaller after seeing positive black exemplars (immediately and at 24 h)

This is one reason we need more women and minority physicians and faculty.

Dasgupta, N., & Greenwald, A.G. ( 2001). On the malleability of automatic attitudes: Combating automatic prejudice with images of admired and disliked individuals. J Pers & Soc Psych 2001;81:800

Charles Drew MD

Barbara McClintock MD

Denzel Washington

Modifying IAT for race during medical school

• 3547 students at 49 medical schools• IATs for race compared in first and last

semesters of medical school• Modifiers of IAT:

– Completing the IAT – Hearing negative comments from superiors– Unfavorable vs very favorable contact with

African American physicians

Anecdote of a personal counterstereotype program

A white faculty member in one of our clinical departments tested strongly positive towards whites. She embarked on a program of greeting, smiling at, and engaging in conversation African Americans in diverse situations, from workplace to public transportation.

On retest she had minimal, if any, preference.

Recommendations

• Take the implicit association test!

Recommendation: empathy

Perspective and empathy: See people’s personal characteristics rather than their group membership

– Have casual conversations with patients or colleagues from other groups

– Begin clinical encounters with reference to a nonmedical subject (e.g. did you see the Phillies game last night?) – Atul Gawande

– Imagine yourself in the other’s shoes with regard to healthcare attitudes and decisions

Recommendation: group membership

• Regard yourself and the patient (or yourself and the consultant) as members of the same team, working together for the patient’s welfare– “dual identity”– shared decision making– avoiding in-group vs out-group thinking

Recommendation: create less stressful environments

• Minimize fatigue, overload, time pressure – which cause default to stereotypes– Shown to be more prevalent in settings

that predominantly treat minority patients– A task for administration as well as

individuals

Recommendations for search committees

• Use a checklist with standardized and multiple criteria for evaluation (avoid shifting standards)

• Have face to face meetings• Make sufficient time for decisions• Look for bias in letters or recommendation• Women and minorities on search committees• Expand the pool from which you recruit beyond

the usual networks• Beware relying your comfort level in the

interview

.

Conclusions

• Implicit bias probably plays a signficant role in the “glass ceiling” and in healthcare disparities

• Conscious unhurried deliberation can mitigate it, but we often don’t have time for that

• Implicit biases can also be lessened by empathy, shared decision making, and cultural competence programs

https://implicit.harvard.edu/implicit/

• Take the IAT in multiple areas to convince yourself you need to take steps to counteract your own biases.

Acknowledgements

• Dr Marjorie Bowman (Penn)• Dr. Molly Carnes (Univ of Wisconsin)• Dr. Virginia Valian (Hunter College of

CUNY)