During normal times, being disadvantaged has been associated with worse mental and physical health (Vanderbilt et al., 2013; Williams, 2018). However, during times of extreme societal stress, such as during 2020, the negative effects of being disadvantaged are often accentuated. For example, according to the Bureau of Labor Statistics, the number of unemployed people in the United States increased by 6.8 million between February 2020 and October 2020, with women, particularly those who identify as Black or Latina or disabled, affected disproportionately. In addition, as mentioned previously, COVID-19 infection and death rates are higher among those from socioeconomic or race/ethnic minority groups; this is also true for individuals with underlying health conditions, including mental illness (Boserup et al., 2020; Fond et al., 2020).
This chapter focuses on the mental health effects of the COVID-19 pandemic for women in science, technology, engineering, mathematics, and medicine (STEMM). The evidence presented here highlights ways mental health may affect women’s engagement in STEMM fields. In particular, this chapter provides evidence that psychosocial, professional, and biological factors contribute to greater risk for mental health concerns among academic women versus men in STEMM fields.
The evidence available at the end of 2020 from across the globe indicated that women in the general population, particularly those on the frontlines of
1 This chapter is primarily based on the commissioned paper “The Impact of COVID-19 on the Mental Health of Women in STEMM,” by C. Neill Epperson, Elizabeth Harry, Judith G. Regensteiner, and Angie Ribera.
health care, were at greatest risk of adverse mental health effects during the COVID-19 pandemic. There were, however, few studies focusing on the effects of stress on, or the mental health of, women in STEMM fields outside of medicine and nursing. Therefore, this chapter discusses key indicators and evidence-based assessments for burnout and mental illness, gender differences in stress exposures, the effects of epidemics and pandemics on the workforce in specific STEMM fields such as medicine and nursing, and the effects of social-distancing public health requirements on university students and faculty more generally, as well as interventions to promote well-being among academic women in STEMM fields. Where appropriate, data from studies focusing on the impact of previous epidemics and the COVID-19 pandemic on the mental health of women in health care and those in the general population were extrapolated to women in academic STEMM. Finally, the majority of the data reviewed assumes that women are those who were identified as women at birth (cisgender women). Where it is possible, this chapter describes how the intersectionality of gender minority status may be affected by the current crisis. Similarly, the chapter utilizes data from the general population to extrapolate to People of Color, with a few exceptions noted.
It is well documented in both preclinical and human studies that chronic and unpredictable stress, such as what occurred during the COVID-19 pandemic in 2020, is the most detrimental form of stress for health (Yaribeygi et al., 2017). Gender differences in stress exposures and in biological response to stress may interact to increase risk of mental health problems for women during the COVID-19 pandemic. Factors such as social isolation, caregiving, and job insecurity, all more common among women during previous pandemics, have been associated with greater mental health concerns (Connor et al., 2020).
Discrimination and marginalization have long been recognized as stressors and contributing factors to poor mental health (Schmitt et al., 2014; Sutter and Perrin, 2016). Women and other underrepresented groups studying and working in STEMM fields are disadvantaged to a greater degree than their male counterparts (Myers et al., 2020; Woitowich et al., 2020). Women in academic STEMM fields are more likely to be early in their career (NASEM, 2020), have a lower salary regardless of professional ranking in STEMM (Raj et al., 2019), be a single parent or a primary caregiver (Calisi et al., 2018; Jolly et al., 2014; Yavorsky et al., 2015), and report experiencing greater work-related stress (Ornek and Esin, 2020) and discrimination in the workplace or their community (Jagsi et al., 2016; Lu et al., 2020). Stressors such as these (discussed more fully in Chapters 2, 3, and 4) are compounded for women by the same social isolation, work disruption, financial worries, and health concerns experienced by others during the COVID-19 pandemic.
Social isolation can be an additional stressor specifically for women in STEMM. Social support—particularly that gained from in-person contact—is a protective factor against the adverse effects of stress on health (Connor et al., 2020), and during many recent societal stressors in the United States, such as natural disasters and terrorist attacks, individuals have been able to gather with family, friends, and colleagues to grieve and heal. Epidemics and pandemics are unique in their requirement for social distancing, which is in direct opposition to human nature under times of stress and increases risk for poor mental and physical health (Umberson and Montez, 2010).
Particularly in fields such as engineering, physics, computer science, and certain subspecialties of medicine, women are likely to be in the minority and have fewer women role models at the rank of professor or in other leadership positions (NASEM, 2020). Because women are more likely than men to use social relationships to cope with stress or threat (Smith, 2014; Taylor et al., 2000), social distancing during the COVID-19 pandemic could exacerbate the relative lack of social support from women colleagues, mentors, and role models, as discussed in Chapter 5. For example, women university students who use a coping style characterized by greater social supports showed a reduction in physiologic response to stress, both across the day and during a laboratory stressor (Sladek et al., 2017). Taken together with exposure to fewer women in the workplace and the importance of social support to stress regulation among women, it may be beneficial for leaders in academic institutions to consider the social distancing required during the COVID-19 pandemic as they create programs to maintain engagement of academic women in STEMM fields (see Chapter 6 for more on leadership).
Finally, during pre-COVID-19 pandemic times, women across the globe were more likely to have depression, anxiety, posttraumatic stress, and insomnia (Bracke et al., 2020). The main mental health conditions most exacerbated by recent societal stressors—such as terrorist attacks, natural disasters, and infectious disease outbreaks—are insomnia, depression, anxiety, posttraumatic stress, and alcohol and drug use (Cabarkapa et al., 2020; Esterwood and Saeed, 2020). Each of these, with the exception of alcohol and drug abuse, are disorders that occur more frequently among women (Bracke et al., 2020).
Several organizations, including the Centers for Disease Control and Prevention, Veterans Health Administration, state governments, and public health agencies, have developed web pages listing a wide range of COVID-19–associated sources of stress, such as personal, family, and community health related to the risk of infection; financial related to loss of job or wages; childcare resulting from school and/or daycare closures; social isolation; and the uncertain future
trajectory of the COVID-19 pandemic and its consequences (Park et al., 2020; UN, 2020). These kinds of stressors may affect women and men differently. As discussed in Chapter 4, women tend to be the major caregivers within an extended family, and, as a result, they are more likely to experience increased stress associated with caring for themselves, loved ones, or friends who contract disease. Along with social isolation and sheltering, there has been an increase in domestic violence during the COVID-19 pandemic, adding yet another stressor predominantly for women (Boserup et al., 2020).
Women are at greater risk of medical issues such as endocrine, immune, rheumatologic, and neurologic conditions that are frequently comorbid with depression and anxiety (Desai and Brinton, 2019; Golden and Voskuhl, 2017; van der Woude and van der Helm-van Mil, 2018). Many of these conditions are stress sensitive, increasing the risk of an exacerbation during the COVID-19 pandemic (Gazerani and Cairns, 2020). In addition, women are more likely to be diagnosed with autoimmune diseases that put them into an at-risk category that could affect their ability to work in any STEMM field that requires some level of social or in-person contact during the COVID-19 pandemic.
There are special concerns related to women health-care workers. As with any pandemic, frontline health-care workers are most at risk for exposure and contracting SARS-CoV-2.2 However, approximately 77 percent of the health-care frontline workforce is made up of women, creating a greater overall infection risk for women in this STEMM field (Robertson and Gebeloff, 2020). In addition to caring for their own families (see Chapters 2 and 4 for more information), women health-care workers are more likely than men health-care workers to be at the bedside taking care of patients with COVID-19 and managing the distress of family members and of the sick and dying (Lai et al., 2020). Women health-care workers are also more likely than men health-care workers to work shift-based schedules that can be unpredictable and can negatively affect circadian rhythms and sleep (Lai et al., 2020).
Mothers-to-be in STEMM, meanwhile, face additional COVID-19 pandemic stressors and consequences (Staniscuaski et al., 2020). Prenatal care, delivery, and infant needs present financial challenges and stress (Ahlers-Schmidt et al., 2020), and concerns about infection during pregnancy not only create stress but lead to avoidance of medical services and worries about how delivery will occur (Berthelot et al., 2020; Preis et al., 2020a, 2020b). Given that increased maternal stress will negatively affect the progression of pregnancy, it is imperative for all mothers to receive care that minimizes disease exposure and delivery complications. Similar to women in STEMM with underlying medical conditions, pregnant women in STEMM have to consider the location of their work and whether colleagues and labmates are careful about their own exposures to the
2 The virus that causes COVID-19.
novel coronavirus. Institutional procedures to ensure safety in the workplace by ensuring access to testing, screening those who come to campus, and rapidly responding to contain outbreaks are essential for these women to be able to use laboratory facilities.
For women in academic STEMM in general, the COVID-19 pandemic has exacerbated many stresses women in academia face under usual conditions, as discussed in Chapters 3, 4, and 5 (Howe-Walsh and Turnbull, 2016). For example, the mantra “publish or perish” emphasizes survival, let alone success, in academia and requires one to continually publish papers and obtain funding. As described more fully in Chapter 3, the effects of the COVID-19 pandemic on women in academic STEMM fields has already been observed as a decrease in productivity. With variation by discipline, women published fewer papers and received fewer citations of their work between March 2020 and December 2020 (Amano-Patino et al., 2020; Andersen et al., 2020; Gabster et al., 2020).
During 2020, the COVID-19 pandemic accentuated gender differences in mental health concerns such as depression, anxiety, posttraumatic stress, and insomnia (Carmassi et al., 2020; Guadagni et al., 2020; Pappa et al., 2020). Delays in clearance for conducting research during 2020, a result of the COVID-19 pandemic, led researchers to experience increased burnout, sleep disturbance, poor appetite, increased interpersonal problems, and decreased motivation (Sharma et al., 2020). The confluence of major events, including the COVID-19 pandemic, racial injustices, and geopolitical unrest, affected academic faculty in multiple domains professionally and personally (Gruber et al., 2020). Each of these outcomes serves as a surrogate measure of well-being and risk for mental health problems during and after the COVID-19 pandemic.
There is a reciprocal relationship between employee well-being and institutional success (Attridge, 2007, 2009).3 Employee well-being affects institutional metrics and culture, while institutional culture, policies, and procedures affect individual employee well-being. This section discusses key indicators that leaders can use to identify risk of declining employee well-being, including mental illness, burnout, and sleep disturbance.
3Employee well-being is defined “as an integrative concept that characterizes quality of life with respect to an individual’s health and work-related environmental, organizational, and psychosocial factors. Well-being is the experience of positive perceptions and the presence of constructive conditions at work and beyond that enables workers to thrive and achieve their full potential” (Chari et al., 2018, p. 590).
Burnout as a Key Indicator of Overall Mental Well-being and Job Satisfaction
Burnout can be measured and has documented negative effects on individuals in the workforce, with considerable attention paid to individuals in health-care professions (NASEM, 2019b).4 Academic medical centers pay particular attention to the prevalence and prevention of burnout among health-care workers, including the effects of burnout on patient safety, quality of care, and professionalism (Panagioti et al., 2018). Across the workforce more generally, high levels of burnout (variably defined) have been associated with a number of somatic conditions, including high blood pressure, coronary artery disease, and diabetes (Guan et al., 2017; von Känel et al., 2020). Women in medicine, nursing, and basic science research report higher levels of personal and work-related burnout than men in similar roles (Gold et al., 2016; Linzer et al., 2000; Messias et al., 2019; Rabatin et al., 2016). These gender differences in the individuals’ relationship to work starts early in academic training. A recent 3-year longitudinal study from Germany comparing freshmen medical students with STEM students indicated that STEM students started and continued to demonstrate greater burnout-related risk patterns compared with medical students. Women students showed a more unfavorable pattern regardless of group (Voltmer et al., 2019).
Institutional leaders have several validated tools to measure burnout available to them, including the Maslach Burnout Inventory–Human Services Survey for Medical Personnel and the Copenhagen Burnout Inventory (designed to be used for any occupation; see Table 7-1; NAM, n.d.). Similarly, there are several validated tools to measure composite well-being, including the Stanford Professional Fulfillment Index. These tools can be used to monitor burnout and well-being among those in the STEMM environments, with particular attention to vulnerable populations such as women, trainees, and people with identities historically marginalized or excluded in STEMM.
Factors Contributing to Burnout
During 2020, the COVID-19 pandemic exacerbated many of the long-standing factors that contribute to greater burnout among women, compared with men, in the STEMM professions. Prior to the COVID-19 pandemic, women in STEMM reported greater emotional exhaustion, a domain of burnout; greater cynicism; and lower academic efficiency in environments described as “chilly” and unwelcoming to women (Jensen and Deemer, 2019). A comprehensive review
4 The World Health Organization defines burnout as “a syndrome conceptualized as resulting from chronic workplace stress that has not been successfully managed. It is characterized by three dimensions: (1) feelings of energy depletion or exhaustion; (2) increased mental distance from one’s job, or feelings of negativism or cynicism related to one’s job; and (3) reduced professional efficacy. Burn-out refers specifically to phenomena in the occupational context and should not be applied to describe experiences in other areas of life” (WHO, 2019).
of burnout among university teachers working in multiple countries indicated that men are more likely to report cynical and negative approaches to others (depersonalization), while women were more likely to report greater emotional exhaustion (Purvanova and Muros, 2010; Wyatt and Robertson, 2011), both symptoms of burnout (Maslach and Jackson, 1993). Moreover, there is some research indicating that women were more likely to score higher than men on all dimensions of burnout (Wyatt and Robertson, 2011). Being younger, having a larger student load, and growing tuition costs among students were also associated with greater symptoms of burnout.
When juggling more domestic responsibilities, as discussed in Chapters 2 and 4, women experience a higher overall cognitive load, putting them at higher risk of burnout. For example, when women physicians are performing more of the domestic responsibilities, they are more likely to wish for a career change, particularly when in a procedural field (Lyu et al., 2019). In addition, high task loads of workplace environments may also contribute to enhanced burnout (Harry et al., 2019). Women are also more likely to take time at home or reduce hours to accommodate the COVID-19 pandemic, as noted in Chapters 3 and 4, which may propagate gender inequities and gaps in compensation (Brubaker, 2020). Leaders in STEMM environments can take steps to measure the climate for women in their institution, have a process to monitor if more women than men are decreasing hours or full-time equivalents, and evaluate the task load placed on employees using a validated tool such as the National Aeronautics and Space Administration (NASA) Task Load Index (NASA, n.d.).
Insomnia is both a symptom and a predictor of onset or exacerbation of a number of mental health disorders, including depression, bipolar disorder, posttraumatic stress disorder (PTSD), and substance abuse. Sleep disturbance is also associated with greater risk for suicide among those with mental illness (R.T. Liu et al., 2020; Weber et al., 2020). Prior to the COVID-19 pandemic, studies examining sleep have focused on the workforce in general or specific patient or demographic populations, with health-care workers, particularly nurses, reporting worse sleep quality than the general population (Khatony et al., 2020; Zeng et al., 2019).
Psychological stress is a primary contributor to reductions in sleep quality (Kim and Dimsdale, 2007), and many of the COVID-19 pandemic-related stressors create risk for the onset and worsening of insomnia and health burdens related to poor sleep quality among frontline health-care providers (Kobayashi and Mellman, 2012). Since the COVID-19 pandemic and its associated public health measure were implemented across nations, a focus has been on health-care workers and students. Similar to reports with previous coronavirus epidemics, such as severe acute respiratory syndrome, or SARS, and Middle East respiratory syndrome, or MERS, insomnia is one of the most common and consistently
Data from multiple nations indicate an increase in poor sleep quality and complaints of insomnia in the general population during the COVID-19 pandemic, but to a significantly greater degree among health-care workers (Cabarkapa et al., 2020; Li et al., 2016; Marelli et al., 2020; Romero-Blanco et al., 2020; Sheraton et al., 2020). For example, between March 1 and April 30, 2020, health-care workers in Spain reported a higher prevalence of new onset or worsening of insomnia compared with non-health-care workers (Herrero San Martin et al., 2020). Given many of the stressors experienced by women health-care workers are also experienced by women in academic STEMM fields, much of these data can potentially be generalized.
Sleep quality among university students may also be unduly affected by the shutdown. A recent longitudinal (pre- and post-lockdown) study of 207 nursing students in Spain revealed that being a woman, being a first- or second-year student, living with one’s family, and use of alcohol were associated with significantly worse sleep quality (Romero-Blanco et al., 2020). Similarly, a longitudinal study including Italian university students indicated a worsening in sleep parameters, particularly among women students, during the lockdown from March 10, 2020, to a partial lifting on May 3, 2020 (Marelli et al., 2020). While more than half of the students reported clinically meaningful sleep problems before the COVID-19 pandemic shutdown, almost three-quarters fell into this range after the shutdown was partially lifted.
Women who have caregiving responsibilities also report changes to sleep quality during the COVID-19 pandemic. A recent study (Zreik et al., 2020) in Israel found an increase of self-reported insomnia in mothers with at least one child between the ages of 6 and 72 months during home confinement related to the COVID-19 pandemic from 11 percent (retrospective report) to 23 percent. Women who are balancing work-related expectations with “sandwiched care” responsibilities (such as caring for both emerging adult children and elderly parents; see Chapter 4) can greatly impact sleep quality and may lead to women leaving academic STEMM (Mavriplis et al., 2010). Importantly, insomnia was found to be a predictor of employed workers ages 50–70 leaving the workforce because of poor health (Dong et al., 2017). Hence, institutions cannot afford to ignore insomnia as a potential contributing factor to women leaving academic STEMM during and after the COVID-19 pandemic.
Relevant sleep quality for People of Color, everyday discrimination, and the perceived stress of racism are associated with worse self-reported sleep quality (Grandner et al., 2012; Vaghela and Sutin, 2016). As racism and other forms of discrimination in the workplace remain common (Fekedulegn et al., 2019), particularly for Women of Color, it would be expected that Black women in STEMM carry the additional burden of perceived stress of racism on sleep quality during COVID-19. Moreover, it is well documented that the physical and mental
health of People of Color and their access to medical interventions, particularly for mental illness, were lacking even prior to the COVID-19 pandemic (Breslau et al., 2017; IOM, 2011; Mangrio and Sjögren Forss, 2017). Given that mental health conditions are also associated with a decreased utilization of primary care services (DeCoux, 2005), the intersection of COVID-19 pandemic-related stress, reductions in access to medical care, fear of infection, and other barriers may have a greater impact on women and People of Color in the months and years to come. However, the relationship between the effects of mental health and chronic health conditions for women compared with men in the setting of the COVID-19 pandemic was not understood at the end of 2020.
Assessing Mental Health in the STEMM Workforce
Validated tools such as the 2-item and 9-item Patient Health Questionnaires, or PHQ-2 and PHQ-9 (Kroenke et al., 2001, 2003), the Generalized Anxiety Disorder 7-Item (GAD-7; Spitzer et al., 2006) questionnaire, the Posttraumatic Stress Disorder Checklist (PCL; Bovin et al., 2016), and sleep-related impairment measures, such as the Insomnia Severity Index or the Pittsburgh Sleep Quality Index (Buysse et al., 1989), are validated measures to assess the likelihood of developing a serious mental condition (Morin et al., 2011; NAM, n.d.; Spitzer et al., 2006; Yu et al., 2011). A description of these instruments and symptom severity range is included in Table 7-1. Given continued concerns among the academic and medical workforce that seeking mental health care will adversely affect their professional standing among their peers and threaten their career opportunities (Feist et al., 2020), institutions may experience resistance to widespread assessment for mental health conditions. Utilizing burnout scales or assessments for sleep disturbances may be a less stigmatizing method to obtain a proxy for faculty mental health during and after the pandemic.
COVID-19–Specific Stress Measures
Essential workers in STEMM fields, such as medicine and nursing, work at the epicenter of the COVID-19 pandemic and, as a result, face increased risk for infection and overall higher rates of stress. The recently developed COVID Stress Scales (CSS; Taylor et al., 2020) categorize stressors from the COVID-19 pandemic into five categories: danger and contamination fear, social and economic stress, traumatic stress symptoms, checking and reassurance-seeking behavior, and xenophobia. Recent findings suggest that the five factors of the CSS form a COVID-19 pandemic stress syndrome. In the general population, each of these factors can contribute to increased substance use and abuse risk. These factors can be compounded in essential workers, placing this group at particularly high risk for substance use and abuse (McKay and Asmundson, 2020). While there were no data available at the end of 2020 specifically for women and People of Color
|Patient Health Questionnaire – 2-Item (PHQ-2; Kroenke et al., 2003)||Assesses depressed mood and decreased interest/pleasure. Responses ranging from 0 = not at all to 3 = nearly every day. Total scores of 3 are considered indicative of major depression. Reference period = past week.|
|Patient Health Questionnaire – 9-Item (PHQ-9; Kroenke et al., 2001)||Frequency of depression symptoms are measured using a scale ranging from 0 = not at all to 3 = nearly every day. Scores range from 0 to 27 with mild (5–9), moderate (10–14), moderately severe (15–19), and severe (20–27) depression. Reference period = past week.|
|Generalized Anxiety Disorder – 7-Item (GAD-7; Spitzer et al., 2006)||Measure of generalized anxiety disorder. Frequency of anxiety symptoms are rated as 0 = not at all to 3 = nearly every day. Total score range = 0 to 21, with mild (5–9), moderate (10–14), and severe (15–21) anxiety. Reference period = past 2 weeks.|
|Insomnia Severity Index (ISI; Morin et al., 2011) (7 items)||Items 1–3 assessed the nature of insomnia with questions related to problems falling asleep, staying asleep, and early awakening (0 = no problem to 4 = very severe). Item 4 assessed dissatisfaction with sleep (0 = very satisfied to 4 = very dissatisfied). Items 5–7 assessed the impact of insomnia by asking about sleep difficulties interfering with daytime functioning, etc. (0 = not at all to 4 = very much). Scores range from 0 to 28 with >10 considered indicative of insomnia.|
|Pittsburgh Sleep Quality Index (PSQI; Buysse et al., 1989) (19 items)||Individuals report on seven components of sleep: sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. Scores on the seven components (weighted equally on a 0–3 scale) are added for a total score of 0–21. A score of >5 is considered indicative of poor sleep quality. Reference period = past month.|
|PTSD Checklist for DSM-5 (PCL-5; Blevins et al., 2015) (20 items)||Respondents report on how much they have been bothered by each PTSD symptom using a scale ranging from 0 = not at all to 4 = extremely. The items tap into four subscales: re-experiencing, avoidance, hyperarousal, and negative alterations in cognition and mood. Total score ranges from 0 to 80. Reference period = past month.|
|Maslach Burnout Inventory – Human Services Survey for Medical Personnel (MBI-HSS MP; Maslach and Jackson, 1993) (22 items)||Measures three aspects of burnout: emotional exhaustion (EE; 9 items), depersonalization (DP; 5 items), and low sense of personal accomplishment (PA; 8 items). Frequency of experiences ranges from 0 = never to 6 = every day. Items are added for a total score ranging from 0 to 54 for EE, 0 to 30 for DP, and 0 to 48 for PA. A score of 27 on the EE subscale and a score of either 10 on the DP subscale or 33 on the PA subscale are considered indicative of burnout.|
|Stanford Professional Fulfillment Index (PFI; Trockel et al., 2018) (16 items)||Measures burnout and personal fulfillment in physicians. Four items assess work exhaustion (e.g., EE at work) and 6 items assess interpersonal disengagement using a scale ranging from 0 = not at all to 4 = extremely. The 6 items related to professional fulfillment (e.g., my work is meaningful to me) use a scale ranging from 0 = not at all true to 4 = completely true. The items are added for a total score of 0 to 64. Reference period = past 2 weeks.|
|Copenhagen Burnout Inventory (CBI; Kristensen et al., 2005) (19 items)||Measure of burnout in any occupational group. Three aspects of burnout are assessed: Prolonged physical or psychological exhaustion perceived to be related to personal (6 items) or work life (7 items) and 6 items related to working with clients. Items are rated on frequency where 0 = never or almost never, 25 = seldom, 50 = sometimes, 75 = often, 100 = always or 0 = to a very low degree; or bother, where 25 = to a low degree, 50 = somewhat, 75 = to a high degree, and 100 = to a very high degree. Subscale range is 0–100.|
|NASA Task Load Index (NASA-TLX; Hart and Staveland, 1988) (6 items)||Assesses subjective experience of workload. Individuals report on six dimensions: mental demand, physical demand, temporal demand (i.e., time pressure to complete tasks), performance, effort, and frustration level. Each dimension is rated on a 0 to 100 scale in 5-point increments. The dimensions can be weighted by using 15 pair-wise comparisons of the dimensions (e.g., comparing whether mental demand versus physical demand contributed more to workload). Each dimension can be chosen from 0 (not relevant) to 5 (more important than any other dimension) times. Ratings of dimensions deemed to be most important in creating the workload of a task are given more weight in computing an overall workload score.|
regarding scores on the CSS, one can extrapolate that any group that came into the COVID-19 pandemic facing health disparities or lower professional standing (e.g., lack of seniority and lower salary) could experience the COVID-19 pandemic as a greater threat to their health and financial stability.
Depression and Anxiety
Depression and anxiety are frequently comorbid conditions, and most studies of mental well-being during the COVID-19 pandemic have measured both, often using standardized ratings such as the PHQ2/PHQ9 and the GAD-7 (see Table 7-1). As measured in 2020, the prevalence of depression symptoms, including those in the moderate to severe range, in the general U.S. population was 3-fold higher during the COVID-19 pandemic than before (Ettman et al., 2020). The risk factors included lower economic resources and greater exposures to stressors.5 Literature that focuses on mental health among health-care workers also consistently reports being a woman as a risk factor for adverse mental health consequences of the COVID-19 pandemic.
The earliest results came from China, where SARS-CoV-2 first spread to humans. A cross-sectional, web-based study conducted in February 2020 showed
5 Findings were not reported by sex or gender nor type of employment, making it difficult to examine these data in relationship to the goal of understanding the effects of the COVID-19 pandemic on women in STEMM.
that overall psychological problems, including depression, anxiety, and insomnia, were reported by a majority of physicians, medical residents, nurses, technicians, and public health professionals. Being a frontline woman health-care worker was associated with greatest risk for both anxiety and depression (Que et al., 2020). These data have been borne out in a meta-analyses and scoping reviews of studies focusing on mental health during the COVID-19 pandemic (Krishnamoorthy et al., 2020; Shaukat et al., 2020). One group (Linos et al., 2020) studied anxiety among U.S. physician mothers using the GAD-7 survey and found that 41 percent of 1,809 participants scored as having moderate or severe anxiety. Being a shift worker, being a nurse, caring for infected patients, and being a woman are each most consistently reported as risk factors for depression and anxiety. The finding of vulnerability to depression and anxiety among women during the COVID-19 pandemic is similar to that reported for previous viral epidemics, including MERS, Ebola, and SARS (Cabarkapa et al., 2020).
These findings in health-care workers extend to trainees. Trainees in health care who are exposed to patients with COVID-19 report significantly higher stress than trainees not caring for these patients (Kannampallil et al., 2020). This study also found that women trainees were more likely to be stressed regardless of patient exposure status, while unmarried trainees were significantly more likely to be depressed and marginally more likely to have anxiety.
Prior to the pandemic, more than one-third of graduate students reported seeking mental health care resulting from the stress of their studies and uncertainty about their career (Woolston, 2019). A survey of graduate students during the COVID-19 pandemic indicates that depression is equally high for women and men, but women are more likely to report symptoms of anxiety than are men. Symptoms of psychological distress were even higher among Latinx students and students who identify as lesbian, gay, or bisexual. Depression was most common among students in the physical sciences, and anxiety was more common among those in biomedical research. Of the 5 percent of students who reported not adapting well to online learning, almost two-thirds reported high anxiety levels (Woolston, 2020d). With the added stress of having to study virtually in many cases, having reduced laboratory access, and growing concerns about federal grant funding, particularly for topics that are not related to the COVID-19 pandemic, it follows that graduate students will likely require more mental health care as a result of the COVID-19 pandemic (Woolston, 2020e).
Trauma Exposures and Posttraumatic Stress Symptoms
Within 1 month of the COVID-19 epidemic emerging in Wuhan province, investigators in China examined posttraumatic stress syndrome (PTSS) symptoms using the PTSD Checklist, specifically the PCL-5 (Bovin et al., 2016), and sleep quality using the Pittsburgh Sleep Quality Index among current or recent residents of Wuhan. Women reported more PTSS symptoms than did men. Women also
experienced higher degrees of reexperiencing symptoms, negative alterations in cognition or mood, and hyperarousal compared with men (N. Liu et al., 2020). Better subjective sleep scores were associated with lower PCL-5 scores. Treating both the PTSS symptoms as well as the sleep disturbance is critical to recovery, as poor sleep quality has been linked to the onset and maintenance of PTSD (Richards et al., 2013, 2020).
While evidence indicates that women in STEMM on the frontline of the COVID-19 pandemic are at greater risk or poor mental health, a review of data from previous pandemics and early studies of health-care workers from the COVID-19 pandemic provides a glimpse into risk and resilience factors for PTSD and PTSS (Carmassi et al., 2020) (see Table 7-2). One can also extrapolate from these data in health-care workers to consider women in other academic STEMM fields. For example, unpredictability at work and having to learn new strategies to accomplish one’s work are risk factors for PTSS in the context of a pandemic. Cognitive overload is also a risk factor, particularly in the face of stress and trauma. Providing clarity regarding safety measures and making sure that individuals feel adequately trained to meet the needs of their job during the pandemic are critical for mental health. Social supports and personal traits such as
|Health-Care Worker||Women in STEMM Fields|
|Unpredictability at work
Families and patients
Increase in critically ill
Increased executive load
More deaths per day
New treatments to learn
|Access to laboratory and equipment
Mentors, program officers
Increased executive load
Threat of infection, loss of job “COVID-izing” research
|Supportive family and friends
Support at work
Feeling adequately trained
Structure in the workplace
Safety in the workplace
|Supportive family and friends
Trainings and supervision
Clear safety instructions
Humor and planning
Open dialog about stress
Altruism and spirituality
|Supportive family and friends
Mentor, collaborators, labmates
Support to “COVID-ized” work
Structured office and home time
Clear safety instructions
Humor and planning
Open dialog about stress
Altruism and spirituality
NOTE: While the majority of research focusing on risk and resilience factors for posttraumatic stress and other mental health concerns has focused on health-care workers, many of the principals can be extrapolated to academic women in other STEMM fields.
SOURCE: Adapted from presentation by N. Epperson. The Impact of COVID-19 on Mental Health and Wellbeing of Women in STEMM. November 6, 2020.
altruism, ability to use humor, making plans, and being able to make meaning of the current situation are protective factors in the face of tremendous work-related stress (Carmassi et al., 2020).
The stress associated with the COVID-19 pandemic in 2020 accentuated the gender gap in STEMM. Unlike community-based stressors that have occurred in the United States since the last global pandemic in the early 20th century, the nature of the stressors related to the COVID-19 pandemic affected all nations, continued for months, and required social distancing to reduce viral spread. This type of chronic and unpredictable stress, along with social isolation, is particularly aversive for women in STEMM, worsening mental health concerns during the COVID-19 pandemic. Indeed, when it comes to women in health-care professions, particularly those providing care to SARS-CoV-2–infected patients, the risk for increased depression, anxiety, and sleep disturbance was even greater in 2020 than that for men in health care as well as the general population, which can likely be expanded to reflect conditions among women in academic STEMM.
The mental health disorders that arise de novo or are worsened during a widespread crisis such as the COVID-19 pandemic are more common among women and People of Color. COVID-19 pandemic-related factors conspire to increase these problems for women in academic STEMM. Social isolation, lack of or disconnection from women role models, previous and ongoing exposures to discrimination and related stress, biological and hormonal factors, and economic and family concerns are just a few of the larger social determinants of mental health among women in STEMM. Individual risk factors in risk for burnout, mental health concerns, and loss to the workforce are important to understand and consider.