Gender discrimination.

We assessed gender discrimination using a single item that assessed how often respondents have been treated unfairly based on their gender in the previous year, since January 2020. Response options ranged from never (score = 1) to almost all the time (score = 6). This item has been previously used to assess gender discrimination among women, men, and gender minorities [20]. Respondents who reported any frequency of gender discrimination (i.e., score>1) were presented with an additional open-ended question asking them to describe an event in which they dealt with gender discrimination.

Covariates.

We selected covariates based on previous studies that identified factors associated with gender discrimination among HCWs [21–24], as well as demographic characteristics (i.e., age, race, ethnicity, marital status, and occupation). For example, previous studies have found that gender discrimination is associated with childcare needs [23] and racial discrimination [21, 22]. We assessed childcare needs by asking respondents who had children if they needed a lot (score = 3), a little (score = 2), or no more (score = 1) childcare support. The childcare support variable was coded as two indicator variables, with no more additional childcare support used as the reference category. We used the General Ethnic Discrimination Scale to assess experienced racism in the past year [25]. This scale includes 18 items that assess various experiences of racial discrimination. We included an additional item asking about racial discrimination from patients. All items were scored on a 6-point Likert scale, from never to almost all the time, and were summed to create a continuous racial discrimination score (range: 19 to 114). This scale has been validated among Black, Latinx, Asian, and White respondents [25]. We also assessed social factors to understand how gender discrimination relates to perceived social support and team cohesion. Social support was measured using one item from the Social Support Questionnaire from the National Health and Nutrition Examination Survey to assess if the participant needs a lot (score = 4), some (score = 3), a little (score = 2), or no more social support (score = 1) [26]. The social support score was included as a continuous variable. Team cohesion was measured using previously validated questions from the Survey of Organizational Attributes for Primary Care to assess communication, decision making, and stress/chaos [27, 28]. This scale includes seven questions, each rated on a five-point Likert scale from strongly disagree to strongly agree. The scale score is computed by summing all items, and ranges from 7 to 35.

Quantitative analysis.

We first conducted a missing data analysis to compare participants included in the analytic sample with those who were dropped due to missing data using independent-samples t-tests and chi-square analyses [29]. We assessed correlations between all independent variables to assess for multi-collinearity and data suitability for analysis. After ensuring the multi-collinearity assumption was not violated, we ran unadjusted ordinal logistic regression models to test bivariate associations between gender discrimination and all factors [29]. Lastly, we ran an adjusted ordinal logistic regression model to predict gender discrimination, which included age, race, ethnicity, marital status, occupation, social support needs, team cohesion, childcare needs, and racial discrimination as covariates [29]. Analyses were conducted in SPSS 27.0 (IBM Corp., 2020). We considered p < .05 to be statistically significant.

Qualitative analysis.

We uploaded all responses to the open-ended question into Microsoft Excel. Our coding team included a woman doctoral student and a woman Master of Public Health student (RH and HG, respectively). We coded all data using inductive approaches based on grounded theory to develop codes and ultimately theory that describe how women experience gender discrimination in healthcare professions [30]. First, we read all responses to generate preliminary, inductive codes. We then met to develop the codebook by explicating definitions, inclusion criteria, and exclusion criteria for each code. Using this codebook, we independently coded the first 50 open-ended responses and met to discuss discrepancies and make necessary modifications to the codebook. Once the codebook was finalized, we independently coded the entire set of responses. We used Cohen’s Kappa to calculate intercoder reliability [31]. We defined sufficient intercoder reliability as Cohen’s Kappa>0.80. Then, we discussed any discrepancies in our coding to reach consensus and generate the final coded datafile. Finally, we met to discuss relationships between codes to conceptualize broad themes using thematic analysis [26]. We used reflexivity throughout the coding process by reflecting on how our own experiences and identities could influence our interpretations of the data [32].

Merging quantitative and qualitative findings.

To merge our quantitative and qualitative findings, we mapped themes that emerged from the qualitative analysis to significant factors identified in the adjusted ordinal logistic regression model (Fig 1). We then made interpretations by identifying how quantitative and qualitative findings converged, diverged, and/or complemented each other [19]. We used the Good Reporting of A Mixed Methods Study (GRAMMS) checklist to guide study reporting [33].

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Fig 1. Mixed methods design.

https://doi.org/10.1371/journal.pone.0281367.g001

Ethics.

The Yale Institutional Review Board approved our study and all participants provided written consent electronically before taking the survey. The first page of the online survey was a consent form, which the participant had to agree to before being directed to the main survey.

Belittlement by colleagues.

First, many respondents reported feeling belittled when their colleagues made gendered assumptions about their profession and used the incorrect professional title. For example, women physicians reported that they were often assumed to be nurses by their colleagues. Even when colleagues knew of their profession, many would not address women physicians as “doctor,” whereas men physicians were addressed by their proper title. A Black/African American physician-in-training explained:

“Nurses, technicians, residents, other attending physicians always assume I am a nurse, based primarily on gender, age, and race I would imagine- it happens countless times per day and if I had the time to reflect on it while it happened, I wouldn’t have time to do anything else as it happens so often.”

This respondent, in addition to others, suggested that being misidentified was due to a combination of their gender, race, and age, suggesting that discrimination experiences among HCWs are interpreted with respect to their intersecting identities.

Additionally, many women reported that their men colleagues used condescending language and had a dismissive tone during conversations about work issues. A Black/African American physician explained:

“As an attending hospitalist, I often have interactions with subspecialty attendings, particularly when challenging patient care issues arise. Frequently, those attendings are older white men. Many times, I’m spoken to in what I perceive as a condescending, belittling or dismissive manner during these conversations, particularly when I’m advocating a position with which that person disagrees. I’ve witnessed my male peers having similar conversations with those same individuals that are far more productive and collegial. These interactions make me feel unvalued and like a lesser member of the faculty than my equally-titled male peers.”

Despite her expertise, this physician described that when she advocates for her patients, her ideas are dismissed. However, when “male peers” have similar conversations, they are treated in a more collegial and professional way. This suggests that women HCWs are not given the same credibility as men, which leads to feelings of being undervalued.

Workload distribution.

Women reported that their workload distribution, both the content of their work tasks and hours, was gendered. Many respondents reported that they were often given additional roles or responsibilities that they interpreted as gendered, including organizing social events, secretarial work, and cleaning. For example, one physician wrote:

“I’ve been given more secretarial tasks rather than my male colleagues who were given leadership tasks. My work was not visible or celebrated.”

Although this HCW is a physician and is thus qualified to take on hospital leadership tasks, she is instead delegated secretarial tasks. This differential allocation of work tasks may impact the ability of women HCWs to gain leadership experiences, and ultimately to be promoted to leadership roles in their workplaces.

Women respondents also reported that they were asked to take on additional work compared with men, which was oftentimes unpaid and unacknowledged. A nurse explained:

“Our APP [Advanced Practice Providers] team was all women. We were expected to work OT [overtime] to continue to staff the COVID ICU [intensive care unit] even when much of the hospital had returned to normal operations. There was no acknowledgement of the work we had done throughout the pandemic despite other teams getting recognition. It felt very gendered that there was the expectation that we’d keep doing unrecognized labor and OT [overtime]”

This nurse described an implicit assumption that her majority-women team would work overtime throughout the pandemic. Due to this assumption, her team failed to be recognized for the sacrifices that they made throughout the pandemic. Thus, gender-based assumptions about willingness and ability to take on additional work is an important form of gender discrimination.

Unequal opportunities for professional advancement.

Women reported that they faced unequal opportunities for professional advancement such as salary, promotions, and job opportunities. Many reported being grossly underpaid compared with men, which made them feel undervalued. A Black/African American and American Indian/Alaska Native lab technician explained:

“I have been passed over for lead positions by those less qualified and with less seniority. I believe this occurred because the other person is a young white male and I am a Female POC [person of color]. I also make less money than my white male counterpart in the same lab whom also has less experience and seniority than myself.”

This respondent again exemplifies the importance of considering both gender and race when evaluating forms of discrimination in the workplace, as she perceives that unequitable opportunities for promotion and pay on her team are due to her intersecting identities as a woman and person of color.

Respondents also noted unfair hiring of new personnel based on gender. A health technician explained:

“Even when the female applicant had more experience and performed more work than the male applicant, the male applicant was selected for job promotion. It felt unfair.”

This woman, in addition to others, reported blatant favoritism to advance the careers of men, such as through hiring, promotions, and pay raises.

Expectations for communication.

Respondents reported conflicting, gendered expectations for how women should behave and speak at work. For example, some women were told to be less timid, while others were assumed to be aggressive:

“There seems to be a perception that women who speak normally are too timid—why is there a need to be extra loud/abrasive to be heard? Confidence and competence come in many forms.”

(physician-in-training)

“Called aggressive when expressed ideas that if one of my male colleagues would have expressed would have been considered assertive.”

(physician)

The Asian physician-in-training was described as too timid, while the Black/African American physician was called aggressive. In this way, beliefs about how women HCWs should communicate are not only conflicting, but also function to prevent women from communicating in their own style.

Many respondents also reported that they were critiqued for being too “emotional.” A physician shared:

“I was told that female faculty members of my division were ’emotional’ in their asks for additional staffing support during administrative meetings. This made me feel angry that all voices were not being heard.”

This HCW described that being labeled as “emotional” functioned to silence women HCWs from voicing their opinions on important staffing decisions.

Objectification.

Women reported experiences of objectification in the workplace. For example, they reported that colleagues made comments that communicate a fixation with their appearance, rather than their performance. A physician shared:

“People are very fixated on my weight in a way that I think would not happen if I were a man. I have lost weight but have a healthy BMI [body mass index] and everyone keeps bringing it up with me. It makes me feel that my appearance counts more than my performance.”

This physician described that frequent comments fixating on her weight signal to her that her appearance is more important than her performance in the hospital.

Many respondents also reported being explicitly sexually harassed in the workplace and not receiving adequate support following these experiences. A lab technician explained:

“I was sexually harassed by a coworker who made frequent explicit sexual commentary along with demeaning commentary about women (saying he hated women, using gendered slurs, complaining about female doctors). When I reported this to my boss, I was placed alone with the offending party on a COVID adjusted night shift schedule.”

This lab technician’s account of her experience and supervisor’s response underscores the minimization of reports of sexual harassment in the workplace.

Expectations of motherhood.

Respondents reported experiencing certain motherhood expectations that colleagues who are men did not face. For example, respondents reported that their colleagues assumed that their work would be negatively impacted by their role as a mother. A psychologist explained:

“Some senior colleagues questioned whether I would return to work from a planned maternity leave based on the suggestion that women often don’t. I felt underappreciated and patronized.”

Questioning women HCWs’ decisions to come back to work after maternity leave inappropriately asserts gender-based expectations for childrearing. For this respondent, these comments made her feel not only patronized, but also underappreciated.

Many respondents also noted how addressing childcare shortages they faced due to the pandemic and simultaneous added workload in the hospital, which disproportionately impacted women, was not prioritized by hospital administration. A physician explained:

“Leadership did not understand the dire childcare situation. The COVID-19 pandemic will set back accomplishments of women in the workplace for decades to come.”

Notably, respondents who were not presently mothers also reported certain expectations related to their childbearing. A physician-in-training shared:

“It was assumed that I wanted to pursue anesthesiology because it ‘allows for more flexibility to raise children.’ I currently have no desire to have children… though this could be considered an innocent assumption, it just happens to be a constant stigma women in medicine must battle against and are hyper aware of.”

This account shows that HCWs’ experience in the gender discrimination related to motherhood could contribute to distress, including hypervigilance.

Mistreatment by patients.

Lastly, respondents expressed that they faced mistreatment by patients based on their gender. For example, they reported that their patients often assumed they were a different profession based on their gender; namely, women physicians were assumed to be nurses. A physician described:

“Often assumed to be a nurse, or not the doctor. Two times when patient assumed male med [medical] student was the doctor and asked if he ‘approved’ of my recommendations. Both situations made me feel frustrated and disappointed.”

This physician’s recollection demonstrates how gender discrimination from patients can influence women HCWs’ emotional wellbeing, perhaps undermining job satisfaction.

Women noted that even after they told patients that they were the physician, many would still not address them as a doctor, and some would even refuse to be seen by a woman physician. A physician-in-training recalled:

“I had an instance where a patient requested their ‘real doctor’. They were not satisfied until a male colleague intervened. As a woman in medicine this is not an unfamiliar encounter. It is disheartening but even more so in this pandemic where I am working harder than ever for my patients.”

This account demonstrates that gender discrimination, although present prior to the pandemic, was particularly hurtful given the profound sacrifices women HCWs were making for their patients.

Notably, many women suggested that they were treated unfairly by patients based on a combination of their gender and ethnicity. A Latina physician-in-training explained:

“Taking care of a patient at the VA [Veterans Affairs Hospital], he said that women should not be doctors, and called me a foreigner. He then walked out of the room and refused being seen by me. Like that, many other similar experiences.”

This HCW described how patients frequently refuse to be seen by her due to a combination of her gender and ethnicity, underscoring the importance of considering intersecting identities to interpret discrimination experiences. These common occurrences suggest that there is a lack of mechanisms for reporting instances of patient-perpetuated discrimination.