Women Leaders in Academic Health Sciences: Institutional Transformation Required

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Women Leaders in Academic Health Sciences: Institutional Transformation Required Molly Carnes, MD, MS Professor, Depts Medicine, Psychiatry, and Industrial & Systems Engineering University of Wisconsin Director, Women Veterans Health William S. Middleton Veterans Hospital

What we believed... That the lack of women leaders in any field would fix itself when the pipeline was full That if women just behaved like men, they would succeed at the same rate That the workplace was a meritocracy where women s and men s accomplishments would be viewed and rewarded equally

What we now know... That unconscious gender-based assumptions and stereotypes are deeply embedded in the patterns of thinking of both men and women That women and work performed by women consistently receive lower evaluations than men and work performed by men (by both men and women evaluators) That such biases produce cumulative disadvantages that impede women s progress toward leadership

How do we know this? 51% of the population; never a woman President 16% of seats in the 109 th U.S. Congress (16/100 Senate; 71/435 House) 35% women medical students since 1985; only 10% of chairs in AMCs are women (AAMC, 2005-6) Women on Editorial Boards of major medical journals: JAMA 6/24 (25%); NEJM 4/16 (25%) Heads of NIH Institutes & Centers: 6/27 (22%) Women s continued invisibility in clinical research (despite NIH Revitalization Act in 1993)

Women s continued invisibility in clinical research Wooley and Simon, NEJM 343:1942-1950 2000 review on managing depression in medical outpatients No mention of: greater prevalence in women; postpartum depression; safety of antidepressants during pregnancy or nursing; how to counsel women on rx who want to get pregnant; childhood sexual abuse, domestic violence, or sex and gender-based harassment in the work place as risk factors Wing et al NEJM 348:583-92 2003 Favors ACE ACE vs diuretic for HT in elderly outpatients results in older women ignored; CVE/death results extrapolated to the elderly McFalls et al NEJM 351:2795-804 2004 1 st CVE/death RCT CABG before elective vascular surgery 98% men Death results extrapolated to patients Favors diuretic 0.2 1.0 5.0 Women Men

Inadequate compliance with NIH guidelines to include women in clinical trials NIH Revitalization Act of 1993 NIH required to include women; other fed agencies followed 9 high impact medical journals in 2004 46 studies, not sex-specific 70% enrolled 30% women 40 (87%) did not report outcomes by sex or include sex as a covariate in modeling None acknowledged limits of generalizability (including 7 studies with <20% women) Geller et al., JWH 15:1123-1131, 2006

Review of some of the evidence WISELI.engr.wisc.edu click on Library; extensive annotated bibliography

UW Gender Climate Survey: Foster et al. Acad Medicine, 2001 836 Med Sch faculty; 61% response Example of climate questions: Are you aware of informal networking which systematically (even if not purposely) excludes faculty members on the basis of gender? Yes: 24% women; 6% men (p <.001)

UW Gender Climate Survey Gender differences in responses (p<.001) I feel like a welcome member of the academic community I feel my advice is sought My career is not taken seriously I have observed situations in which women are denigrated based on their gender Perceived obstacles to academic success women 2-3X men

Swedish Postdoc study Wenneras and Wold, Nature, 1997 114 applications for prestigious research postdocs to Swedish MRC (52 women) Reviewers scores vs standardized metric from publication record = impact points Women consistently reviewed lower, especially in competence Women had to be 2.5x as productive as men to get the same score To even the score, women needed equivalent of 3 extra papers in a prestigious journal like Science or Nature

Wenneras and Wold, Nature, 1997 Competence score 3 2.9 2.8 2.7 2.6 2.5 2.4 2.3 2.2 2.1 2 men women 0-19 20-39 40-59 60-99 >99 Total impact points

Gender and Behavior DESCRIPTIVE: How men and women actually behave PRESCRIPTIVE: Subconscious assumptions about the way men and women in the abstract ought to behave: Women: Nurturing, communal, nice, supportive, helpful, sympathetic Men: Decisive, inventive, strong, forceful, independent RELEVANT POINTS: Leaders: Decisive, inventive, strong, independent Social penalties for violating prescriptive gender assumptions

Penalties for success: Reactions to women who succeed at male gender-typed tasks Heilman et al., J Applied Psychol 89:416-27, 2004 48 subjects (20 men) Job description; Assist VP; products made suggested male (e.g. engine parts, fuel tanks). Male and female rated in two conditions: Performance clear Performance ambiguous

Achievement-related Characteristics: Unambitious - ambitious Passive - active Indecisive - decisive Weak - strong Gentle - tough Timid - bold Unassertive - assertive Competence Score: Competent - incompetent Productive - unproductive Effective - ineffective Interpersonal Hostility: Abrasive - not abrasive Conniving - not conniving Manipulative - not manipulative Not trustworthy - trustworthy Selfish - not selfish Pushy - accommodating Likeability: Likeable - not likeable How much do you think you would like to work with this person? Very much - not at all Comparative Judgment: Who is more likeable? Who is more competent?

Performance clear Results Competence comparable Achievement-related characteristics comparable Women less liked Women more hostile Performance ambiguous Likeability and hostility comparable Men more competent Men more achievement-related characteristics

Study 2 women only less liked in male gender type jobs Study 3 Likeability and competence independently linked to recommendation for organizational rewards Only women were deemed unlikeable for being competent at their job!

Subtle gatekeeping bias Trix and Psenka, Discourse & Soc 14:191 2003 312 letters of rec for medical faculty hired at large U.S. medical school Letters for women vs men: Shorter 15% vs 6% of minimal assurance 10% vs 5% with gender terms (e.g. intelligent young lady ; insightful woman ) 24% vs 12% doubt raisers Stereotypic adjectives: Compassionate, related well vs successful, accomplished 34% vs 23% grindstone adjectives Fewer standout adjectives ( outstanding excellent )

Semantic realms following possessive (e.g. her training ; his research ) 60 50 40 30 20 10 Female Male 0 Career Skills/Abil Research Applic Teaching Training

Distinctive semantic realms following possessive 25 20 15 10 Female Male 5 0 Personal Pubs CV Patients Colleagues

Nonverbal responses to leaders Butler & Geis, J Pers Soc Psychol, 1990 168 intro psych students naive; 8 adv students confederates (50% F) Task = rank 9 objects for survival Groups of 4; trained, scripted, rehearsed 28 groups (solo leader, non-leader, coleader) Evaluators behind 2-way glass recorded nonverbal affective responses to leaders Impressions of people in different roles

Nonverbal responses to leaders Butler & Geis, J Pers Soc Psychol, 1990 Women leaders fewer pleased and more displeased responses for same initiatives Competence evals equal Assigned gender-stereotyped traits Conclusion: deference is still normative for women in mixed-sex task discussions

Gender Differences Among Physician- Scientists in Self-Assessed Abilities to Perform Clinical Research Bakken et al., Acad Med, 2003 Women (n=28) entering a program to train clinical investigators scored lower than men (n=29) on 22/35 competencies significantly lower on spend sufficient time developing and advancing one s own area of scientific research. Following 3 d workshop, gender difference increased; women lower on 34/35, sign. for 7

Pre-training difference in mean ratings of men and w omen for each objective on the self-assessment (n=57). 0.6 0.4 7 8 Mean Difference 0.2 0-0.2-0.4 1 2 3 4 5 6 9 10 11 12 13 14 15 16 17 18 19 20 23 24 25 26 27 28 29 30 31 32 33 34 35 22 21-0.6 Objective Num ber

0.1 0 9 29 Mean difference in ratings (w om en-m en) -0.1-0.2-0.3-0.4-0.5-0.6-0.7 1 2 3 4 5 6 7 8 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 30 31 32 33 34 35-0.8 Objective num ber

Computer simulation of cumulative advantage for men in an organization Martell et al. Am Psychol 51:157-8 1996 8 levels: 500 employees at bottom; 10 at top; 50% women Eval scores normally distrib; highest scores promoted 15% attrition until organization staffed with all new employees Bias points given to favor men: 5% = 29% women at top; 58% bottom 1% = 35% women at top; 53% at bottom

How trivial bias works against women within organizations % W 70 60 50 40 30 20 10 0% 1% 5% 0 1 2 3 4 5 6 7 8 Level

How can we ensure that all the best talent has equal opportunity to become leaders?

What needs to be done? Take the focus off fixing the women Must be framed as institutional issues, bad science, waste of human capital Commitment at the highest levels of leadership is essential The first step is to get everyone to at least acknowledge that we all have biases and assumptions

Intentional behavioral change required: Lessons from smoking cessation Five stages of change identified: Precontemplation: Smoking is not a problem and I enjoy it! Contemplation: I am worried that smoking is bad for my health and I want to quit. Planning: I am going to buy a nicotine patch and quit on my birthday. Action: I quit! Maintenance: Whenever I feel like a smoke, I take a walk.

As applied to diversity in leadership Precontemplation Individual statements We ve always done it this way, and it seems to work just fine. We can t afford to lower our standards just to be politically correct. Institution behaviors No forums for dialogue promoted despite visible absence of diverse leaders No resources committed to solutions Decision-making committees continue to be established without women or minority members Carnes et al. J Women s Health 14:471, 2005

Contemplation Individual statements If we want to keep the best and brightest in our field, we must figure out a way to keep the women from leaving. Diversity is excellence and we want our institution to be a leader in this area of social change. Institution behaviors Workshops convened to stimulate discussion Task force charges with reviewing local data Preparation I am attending a national workshop on diversity I am reading Why So Slow? By Valian and Diversifying the Faculty by Turner A strategic plan for diversity is developed Institutional resources are committed to the issues (e.g. speakers, conference) Workshops developed to train search committees

Action Individual statements I hired my first woman postdoctoral fellow. I called the program chair and complained that there were no women speakers Institution behaviors Women chair hired Number of minority faculty reaches targeted goal Maintenance I am always in the recruiting mode for talented women and minority applicants I am proud of the advances our school has made in the hiring and promotion of women. Institutional data is monitored and made public Leaders interview women and minority faculty who leave or turn down offers

Goal: Healthy Environment for All If we can change the cultural norms for a powerfully addicting substance, we can change the cultural norms for leadership

Challenges Institutions exist in the context of broader culture As such, gender issues require continued monitoring and active, conscious strategies to maintain gender equity Very narrow range of behaviors allowed women in professional settings

Opportunities As the first lower status minority entering traditionally male professions, women have tremendous opportunity to move ahead as a diversified minority Gender equity in our fields can become an accepted area of research Re-examine effectiveness of current models of pedagogy for all students

Bottom line We need women s intellectual capital We need to change cultural norms of leadership just as we have for smoking!

Sexist discrimination still exists it is just less blatant than in the past when discrimination could be measured in terms of deeds done, such as openly verbalized policies of gender exclusion. Now discrimination takes the form of deeds undone collaborations not offered, acknowledgments unvoiced, introductions not made, opportunities withheld. Because these are omissions rather than commissions, they go unnoticed. What s Holding You Back? Linda Austin, MD; 2000

Having time to focus on applicant evaluation reduces activation of gender schema Martell RF. J Applied Soc Psychol, 21:1939-60, 1991 202 undergrads (77 male, 125 female) Subjects randomly assigned to 1 of 8 experimental conditions (2x2x2 factorial): Male or female version of police officer s performance Hi or low attentional demands (concurrent task demand and time pressure) Hi or low memory demand 9-point graphic rating scales Competence, job performance, potential for advancement, likely future success Adjective scales of gender-related attributes (e.g. dominantsubmissive, strong-weak) Likeable - not-likeable; funny not funny

No effect of evaluator sex No impact of memory demand on evaluation Men and women rated comparably during low attentional demand Hi attentional demand: Men rated higher than women Men rated higher than men during low attentional demand (women same) Conclusion: when multi-tasking and pressed for time, evaluation defaults to prescriptive gender characteristics Martell RF. J Applied Soc Psychol, 21:1939-60, 1991

Mental imagery can moderate implicit gender stereotypes Blair et al. J Pers and Soc Psychol 81:828, 2001 Conducted 5 experiments on undergrads Measured implicit stereotypes 3 ways, before and after intervention Counterstereotype imagery ( imagine a strong woman ), stereotype imagery ( imagine a storybook princess or Victorian woman ), neutral (imagine a house) Significant reduction in measures associated with unconscious gender assumptions following counterstereotype imagery

Images of admired and disliked individuals combat automatic attitudes Dasgupta & Greenwald J Pers & Soc Psych 81:800, 2001 Pictures of 40 well known individuals; 10 each in 4 categories or flowers: Admired black (e.g. Denzel Washington) Admired white (e.g. Tom Hanks) Disliked black (e.g. Mike Tyson) Disliked white (e.g. Jeffrey Dahmer) Implicit Association test: white preference effect sign smaller after positive black exemplars (immediately and at 24 h) Repeated with young and old - same

To be sure, women need to better understand the mechanisms of hiring, funding, and promotion; that is, how to play the game. But the game itself has to be purged of cloning, patronage, and outright discrimination if transparency in hiring and promotion is to become the rule. Tobias S, M Urry, A Venkatesan. (2002 May 17). Physics: For women, the Last Frontier. Science. Vol 296 www.sciencemag.org

Computer simulation of cumulative advantage for men in an organization Martell et al. Am Psychol 51:157-8 1996 8 levels: 500 employees at bottom; 10 at top; 50% women Eval scores normally distrib; highest scores promoted 15% attrition until organization staffed with all new employees Bias points given to favor men: 5% = 29% women at top; 58% bottom 1% = 35% women at top; 53% at bottom

How trivial bias works against women within organizations % W 70 60 50 40 30 20 10 0% 1% 5% 0 1 2 3 4 5 6 7 8 Level

Recommendations Acknowledge that we all have biases and assumptions Examine language at gatekeeping junctures for evidence of semantic priming and linguistic expectancy bias Describe desired behaviors in specific, concrete terms to avoid transmitting stereotypes Continue to raise awareness of the fact that: fixing the women is not enough to achieve gender equity it is not good science to exclude women or to fail to note the limits of generalizability and it is potentially harmful to women s health