seX & whY Episode 3: Priming and Performance

Jeannette WolfePodcast EpisodesLeave a Comment

Show Notes for Podcast Three of Sex & Why
“Behavior” Pod
Hosts: Jeannette Wolfe and Simon Carley

Topic: Unconscious Bias

Major Question: Can unconscious cues cause changes in behavior and performance?

Riskin Study

Examined the effect of rude statements on team diagnostic and procedural performance.

What they did: Had NICU providers (nurses and doctors) first go through a simulation and then attend a workshop on team “reflexivity” (i.e. team training). The workshop was taught by a neonatologist who said that he was “collaborating” with an American expert who was ostensibly watching via webcam.

At the end of the workshop, the coordinating neonatologist told the teams that the expert wanted to greet them and he then “dialed” up the expert (in reality this triggered a prerecorded message). The groups were randomized to hear either a neutral message in which the expert commented that he had been working with a lot of Israeli hospitals, or a rude message in which the expert commented that he had “observed a number of groups from other hospitals in Israel and compared with the participants he had observed elsewhere, he was not impressed with the quality of medicine in Israel.”

Both groups then underwent a standardized written and procedural simulation case involving a neonate with rapidly progressing necrotizing enterocolitis. Ten minutes into the simulation the American “expert” spoke again with the control group hearing another neutral comment and the rude group hearing that although the expert liked some of what he saw during his visit to Israel that he hoped that he would not get sick in Israel and implied that most “wouldn’t last a week” in his own department. The teams then continued to complete the case.

The simulations of both the control and rude teams were then evaluated by blinded observers who reviewed written documents and team videos. Participants were rated on diagnostic performance, procedural performance, information sharing and help-seeking.

Results: 33 NICU providers were randomized to control group and 39 to rude statement group forming a total of 24 teams.

Diagnostic and procedural performance along with information sharing and help seeking behavior declined statistically significantly in the rude group.

Table 1

Statistically significant differences in procedure performance

Procedure Control-neutral phone calls

Mean (1-5 scale)

Intervention- rude phone calls P value
resuscitation performed well 3.05 2.49 .002
Verified tube placement well 3.56 2.85 .0005
Ventilated well 3.43

 

3.01 .002
Asked for right lab tests 3.78 3.24 .01
Good general technical skills 3.17 2.61 .002
Overall procedure 3.26 2.77 .0002

 

 

Table 2

Statistically significant differences in diagnostic performance

Variable Control- neutral phone calls Intervention-rude phone calls P value
Diagnosed shock 2.88 2.08 .003
Diagnosed NEC 3.08 2.62 .041
Diagnosed deterioration 4.05 3.54 .006
Suspected bowel perf 2.6 1.94 .012
Diagnosed cardiac tamponade 3.18 2.15 .001
Overall Diagnostic 3.18 2.65 .0003

Theory behind findings- At individual level rudeness can impair access to working memory (which is important for analysis, planning, and execution) which can then contribute to suboptimal task execution. At the team level, performance is further decreased because less information is shared (potentially limiting diagnostic considerations) and procedures may become more difficult because individuals stop asking for help.

Ultimately this study suggests that when an attribute (in this case being an Israeli physician/nurse) is challenged, behavior can be impacted. This has huge implications for how physician professionalism can directly affect patient care.

Shih Study:

This study is wonderful in its simplicity, it takes individuals who possess two attributes that are associated with opposing stereotypes (in this case Asian and female) and asks if their behavior (performance on a math test) is able to be manipulated depending upon which attribute is subtly cued.

Shih asked a group of Asian college females to take a math test. Prior to taking the test she randomized the women into three groups.  In the first group, participants were subtly primed to identify with their “female” identity by asking them gender demographics and targeted questions about single sex versus coed dorm living. In the next group, women had their ethnic identity triggered by asking about relatives and languages spoken at home. And in the final group women were asked generic questions that avoided implicit triggering of either gender or ethnic attributes. The measured outcome was accuracy= number of test questions right/number attempted

Results: Women who had their Asian identity triggered scored highest on the tests, the neutral group scored in the middle and the female identity primed scored the worst with statistical difference (p<.05) between ethnic and female triggered scores.   (Of note, the mean SAT scores for Asian women in the study was 750 with the general average scores that year being 508)

Importantly in this study results showed:

  • the women were unaware of both the specific attribute that was being primed or the purpose of the study
  • no difference in motivation (i.e. Asian group did not consciously try harder)
  • no difference b/w the three groups in believe of how well they did
  • no difference b/w the three groups in their overall assessment of math competency

Maass study:

This is one of my favorite studies because it objectively shows that subtle gender cues or “primes” can actually trigger significant differences in performance.

 

What they did:  had chess players matched by ability level play three games of internet chess. Each pair was composed of a man and women who (unknowingly) played all three games of chess against each other. In the control game, each player was given a gender neutral name, in the second and third games players were given a priming statement about international chess being a male dominated game and that the researchers were evaluating potential contributing factors. Players were then told that in the last two games one game would be played against someone of their same sex and the other played against someone of the opposite sex.

Results:

42 pairs of men and women

Control game and primed game in which players believed they were playing against someone of same sex- games essentially split (i.e. no statistical difference in who won.)

Primed game in which women believed they were playing against a man: women lost 75%

So what happened here? Were men positively primed by information that suggested a natural advantage (receiving a  “stereotype lift”) and then able to play up and crush women? Or conversely, were women underperforming because they were negatively primed (experiencing a “stereotype threat”) and because in their minds the game’s stakes suddenly got raised as their performance would ultimately be compared to the stereotype? Well, the researchers believed that the differences were not because men changed their playing tactics but because women altered their game style. Instead of playing to win (goal directed), they began to play not to lose (failure avoidance) which is actually believed to be a separate motivational system. Ironically, playing more cautiously actually caused women to lose more games.

Discussion:

What we can learn from these studies: Subtle cues can affect behavior and team performance.  Unconscious bias is real and there are ways to mitigate it.

What is unconscious bias?

– A deeply rooted subliminal belief that reinforce the norms of the

dominant majority within a society

– May be at odds with conscious beliefs

– Is ubiquitous (affects both men and women)

Priming

A cue that triggers either a conscious or unconscious awareness of a specific attribute and that can subsequently affect behavior positively, negatively or not at all.

Priming variables:

Specific situation

Salience of prime:  blatant, subtle or simply “in the air” (ubiquitously present)

Number of different attributes being triggered (gender versus gender and race)

Who is triggering threat (self, in group, outgroup)

If threat is directed specifically toward self or larger group

If threat is believed to be “fixed”- (this comes out of Carol Dweck’s  Mindset work in which individuals who have a fixed mindset believe that certain abilities are innate and you either have them or don’t, versus a “flexible” mindset in which it is believed that abilities can be obtained through deliberate and consistent effort)

*** Somewhat ironic, stereotype threat appears to be most powerful in individuals who have deep associations with the specific triggered attribute and in those who are most motivated to do well.

(Hoyt 2016)

Examples of priming:

Asking demographics before testing

Comment about lack of diversity when you are only individual with specific attribute at meeting

Adverse effects of stereotype threat-

  • Underachievement

–   Loss of confidence

–   Disengagement/Avoidance

–   Adoption of “reactance” response, purposefully acting directly opposite of the expected stereotype (this may or may not be adaptive depending on situation i.e. blatantly priming can trigger a I-see-what-you-are-doing-and-I’m-not-going-to-let-you-get-away-with-it performance boost, or it can backfire as seen in some studies in which women try to negotiate similarly to men.

Theories as to why there are behavioral changes associated with unconscious bias and stereotype threat:

  • Physiological stress- decreasing working memory
  • Increasing anxiety
  • Increasing thought intrusion
  • Overthinking previously automatic behavior

Ways to decrease stereotype threat

For individuals

  • Simply recognize
    • Understanding that situational anxiety may reflect stereotype threat and not incompetence (Maas study showed that under right mindset women could perform on par with men.)
  • Separation of attribute from task
    • “X” is challenging for everyone no just people with specific trait
  • Identify with individuals with same attribute who have been successful
    • Demonstrate that success is possible
    • Buffers threat (though in certain cases can backfire if the individual cannot realistically identify with the role model leading to feelings of inadequacy.)
  • “Positively” prime yourself
    • Remember a personal experience that was associated with professional success
  • Consciously embrace a flexible mindset

For organizations

  • Validation that individual is qualified to do task
  • Create external environmental cues that welcome inclusion and create “identity” safe environment
    • Encouraging people to volunteer for “easy” leadership opportunities, emphasizing no experience is needed
    • Emboldening jr residents to step up to care for critical patients reminding them they will receive appropriate back up if needed
  • Commit to breaking down silos- in medicine this is critically important, as different identity groups often take potshots at each other which can ultimately lead (at least in medicine) to decreased collaboration and increased medical errors
    • it should not be “us versus them” rather “us with them to take care of patients”.
  • Increase diversity- having a single individual with a specific trait in a group is quite different than having several other group members also share that same trait. When there is just a single individual, other group members may unconsciously process that individual’s suggestions as being aligned with or opposed to associated stereotype versus seriously considering its stand-alone legitimacy.

_________________________

More Specific Gender Examples

Gender examples:

(Murphy 2007) women attending a major STEM conference in which gender imbalance was subtly primed felt isolated and disengaged at meeting

(Cheryan 2009) Stated interest in computer science decreased if women were exposed to a stereotypical male computer science environment (room with Star Trek poster and video games) than if exposed to more gender neutral space.

–   Distancing self from identification of attribute (women being unsupportive of other women)

Success story of positive priming

Harvey Mudd College’s computer science experience

Maria Klawe, president of Harvey Mudd University wanted to increase gender balance amongst computer science majors so she did three things

  • Affirmation
    • Personally contacted high potential female students women who were accepted into Harvey Mudd
  • Created enhanced opportunity in non-threatening environment
    • Required every freshman to take a computer science class but importantly divided students into two classes depending upon whether or not they had had previous experience (thus avoiding having novices feel out of their league if seated next to an expert)
  • Promoted exposure to role models
    • Invited women considering a computer science major to attend the national Grace Hopper conference so that they young women had first hand exposure to successful women programmers.
  • Results: Harvey Mudd increased percentage of female programmers from less than 15% to 40%

To test you own unconscious gender bias go to https://implicit.harvard.edu/implicit/user/agg/blindspot/indexgc.htm

Cheryan, S., Plaut, V. C., Davies, P. G., & Steele, C. M. (2009). Ambient belonging: how stereotypical cues impact gender participation in computer science. Journal of Personalityand Social Psychology, 97(6), 1045–60. http://doi.org/10.1037/a0016239

Hoyt C, Murphy S: Managing to clear the air: Stereotype threat, women, and leadership. The Leadership Quarterly Vol 27, Issue 3 June 2016 pp 387-399

Maass, A., & Ettole, C. D. (2008). Checkmate ? The role of gender stereotypes in the ultimate intellectual sport, 245(April 2007), 231–245. http://doi.org/10.1002/ejsp

Riskin, A., Erez, A., Foulk, T. A., Kugelman, A., Gover, A., & Shoris, I. (2015). The Impact of Rudeness on Medical Team Performance : A Randomized Trial, 136(3).

http://doi.org/10.1542/peds.2015-1385

Shih, Margaret, Pittinsky, Todd L and Ambady, N. (n.d.). Stereotype Susceptibility: Identity Salience and Shifts In Quantitative Performance. Psychological Science January 1999 vol. 10 no. 1 80-83

  • Wayne N, Vemillion M, Uijtdehaage S, Gender differences in leadership amongst first-year medical students in the small-group setting Academic Medicine, 85 (8) (2010), pp. 1276–1281

Harvey Mudd Experience (NY Times April 2, 2012) http://www.nytimes.com/2012/04/03/science/giving-women-the-access-code.html?_r=0

 

Leave a Reply

Your email address will not be published. Required fields are marked *