seX & whY Episode 5 Part 1: Stress Response

Jeannette WolfePodcast Episodes

Show Notes for Podcast Five of Sex & Why

Host: Jeannette Wolfe

Topic: Stress Response

This Podcast focuses on the basics of the acute human stress response. Please see Dr Morgenstern’s excellent write up:

Performance Under Pressure Review:

Components of stress response

  • Trigger
  • Speed of activation
  • Magnitude of response
  • Time to return to baseline

Things that affect cortisol response

  • time of day
  • health
  • genetics
  • personality
  • early pre-natal/childhood stressors- epigenetics can change DNA expression
  • current stressors
  • smoking
  • if female- where you are in cycle or use of OCP
  • interaction with testosterone

Sensation of psychological stress is not always associated with physiological stress (i.e. cortisol stress response)

Conversely in psychological studies in which subjects get exogenous steroids (i.e take a hydrocortisone pill) although there are often associated behavioral changes from the steroids participants rarely feel anxious.

Somewhat ironic that women report more psychological stress but that men die on average 7 years earlier

Things that reliably trigger physiological stress:

Demands >>> Resources

  • Unpredictability
  • Uncontrollability
  • Novelty

Learning on stress is U shaped curve

  • A little stress helps things stick more
  • As stress increases harder to draw

Some suggested sex differences:

In general women have higher baseline HR than men (despite this, women are believed to have a higher parasympathetic baseline tone)


  • Men may be more vulnerable to stressors that trigger dominancy/hierarchy
  • Women may be more vulnerable to stressors that trigger social isolation

Free Cortisol is the active form and men appear to have higher free cortisol levels

Women may be more sensitive to acth- similar cortisol level with less trigger.

Men more likely to respond to threat of hierarchy, women social exclusion

Stress resiliency:

Time to respond, magnitude of response time until return to baseline

To what, how quickly, how much, how long.

Studies discussed in podcast

Alexander, G. M., Wilcox, T., & Woods, R. (2009). Sex differences in infants’ visual interest in toys. Archives of Sexual Behavior, 38(3), 427–33.

Ali, Amir; Subhi, Yousif; Ringsted, Charlotte; Konge, Lars. Gender differences in the acquisition of surgical skills : a systematic review. /I: Surgical endoscopy, Vol. 29, Nr. 11, 11.2015, s. 3065-3073.

Deane, R., Chummun, H., & Prashad, D. (2002). Differences in urinary stress hormones in male and female nurses at different ages. Journal of Advanced Nursing, 37 , 304–310.

Shane MD, Pettitt BJ, Morgenthal CB, Smith CD (2008) Should surgical novices trade their retractors for joysticks? Videogame experience decreases the time needed to acquire surgical skills.
Surg Endosc 22:1294–1297

Theorell Tores, On Basic Physiological Stress Mechanisms in Men and Women: Gender Observations on Catecholamines, Cortisol and Blood Pressure Monitored in Daily Life. Psychosocial Stress and Cardiovascular Disease in Women, DOI 10.1007/978-3-319-09241-6_7  Published 2015 pp 89-105

Turecki, G., & Meaney, M. J. (2016). Effects of the Social Environment and Stress on Glucocorticoid Receptor Gene Methylation: A Systematic Review. Biological Psychiatry, 79(2), 87–96.

Yael, Sofer, et al. “GENDER D. S. F. C. H. L. I. M. . E. P. (2016). (2015). Original Article GENDER DETERMINES SERUM FREE CORTISOL: HIGHER LEVELS IN MEN EP161370.OR. Endocrine Practice.

White MT, Welch K (2012) Does gender predict performance of novices undergoing fundamentals of laparoscopic surgery (FLS) training? Am J Surg 203:397–400

seX & whY Episode 3: Priming and Performance

Jeannette WolfePodcast Episodes

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.


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.


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)


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

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.

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.

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).

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)


seX & whY Episode 2: Code Leadership and Gender

Jeannette WolfePodcast Episodes

Show Notes for Podcast Two of seX & whY
Code Leadership and Gender
“Behavior” Pod
Hosts: Jeannette Wolfe and Simon Carley

Major Question: Are there potential unique gender challenges associated with stepping into traditional code leadership roles?

What we know- importantly there is no evidence that men and women differ in competence of running actual resuscitations (Wayne 2012). This discussion is based on whether unique gender associated variables should be considered when learning and then running resuscitations.

Streiff Study

This study looked at a code simulation run by randomized groups of three Swiss fourth year medical students. Before participating in the simulation, students filled out basic demographic information and then took tests that evaluated for certain personality traits and for basic resuscitation knowledge and experience. The authors main objective was to see which variables were associated with code leadership by using “leadership statements” as a surrogate marker.  Leadership statements were statements made by participants that could be categorized into one of four areas: what should be done; how it should be done; who should do it; direction/command to another person that prompted action or change of action.

Results: 237 students

Variables that were associated with leadership statements were:

Male sex, extraversion and low scores on agreeableness personality trait.

Factors not associated with leadership statements were: height, experience or(most concerningly) fund of knowledge.

Study implications:

  • Individuals with the most knowledge might not actually be the ones taking charge/ speaking up in critical situations
  • Individuals who are less concerned with typical social conformity (tact, modesty) may be more comfortable stepping up to lead in short term emergencies
  • There are likely gender specific factors that need to be considered when teaching providers to become effective code leaders. (d = 0.38)

Kolehmainen’s study

  • Qualitative study on resuscitation perspectives
  • 25 residents from 9 internal medicine programs
  • Semi-structured telephone or in-person interviews

Men and women both shared that effective code leadership was extremely important for patient care and team cohesion and that the most effective code leaders ran codes in a classic “agentic” style (i.e. loud, direct and authoritarian).

Women found it much more stressful to step into this style of leadership and were concerned about potential backlash from team members who assumed they were acting “witchy with a b”.

The authors contend this is a legitimate concern because when women step into code leadership they are bucking implicit bias around cultural stereotypes that expect men to be more aligned with agentic roles and women to be more aligned with communal ones (i.e. cooperative and soft spoken)

Leadership and gender: All participants thought that men and women were equally effective leaders, and both described the same ideal leadership behaviors and their struggles to achieve them. However, the larger majority of female participants expressed their discomfort and stress in acting more assertively during codes. One female participant observed that “tall men with a deep voice may naturally appear more authoritative.” A male participant confirmed this advantage, saying “Anyone who tells you that being a white male with a deep voice who’s a little bit taller is not an advantage … would be lying.” Another female participant said, “I act differently during a code … you’re trying to assume this persona of being in charge and I think that’s probably a little more stressful (for women).” Almost half of the female participants described their apprehension in appearing “bossy” when leading codes, whereas no male participants expressed this concern.”

Kolehmainen’s tips to help women cognitively prepare for running a resuscitation.

  • Establish “Identity safety”
    • Remind them there are no gender differences in code competencies

Validate potential awkwardness

  • Acknowledge that transitioning from one’s typical communication style can be difficult but it is also necessary for running effective resuscitations
  • Practice “Enclothed cognition”
    • Use pager and white coat as external symbols that validate leadership role
    • Consciously transition by tying hair back
  • Adopt “Embodied Cognition”
    • Take advantage of body positioning
      • Stand elevated at head of bed
      • Use power stance
      • Deepen voice
    • Debrief (and possibly acknowledge awkwardness of leadership role) afterwards

Other tips from podcasters:

Reframe resuscitation scenario- advocate for patient, optimize their outcome

Liberal use of time outs- this allows summary, direction and formally solicits input

  • Consciously creating a space that empowers others in the room to have the opportunity to speak up is paramount to patient safety

Bottom line of these two studies:  it is important to consider the potential of gender specific issues and possibly gender specific consequences associated with traditional code leadership.

Kolehmainen c, Brennan M, Filut A, Issac C, Carnes M” Afrain of being “witchy” with a “b”: a qualitative study of how gender influences residents’ experiences leading cardiopulmonary resuscitations. Academic Medicine: 2014 89 (9) 1276-81.

Wayne DB, Cohen ER, McGaghie WC. Leadership in medical emergencies is not gender-specific. Simul Healthc 2012;7:134.

Streiff S, Tschan F, Hunziker S, et al. Leadership in medical emergencies depends on gender and personality. Simul Healthc 2011;6:78Y83.

Tool to understand Cohen’s d effect graph: Magnussen, K:

In gender associated research the following d effect size  is commonly used (d 0.10) or small (0.11 d 0.35) range, a few are in the moderate range (0.36 d 0.65), and very few are large (d 0.66–1.00) or very large (d 1.00).