Workplace Harassment, Cyber Incivility, and Climate in Academic Medicine

Reshma Jagsi; Kent Griffith; Chris Krenz; Rochelle D Jones; Christina Cutter; Eva L Feldman; Clare Jacobson; Eve Kerr; Kelly Paradis; Kanakadurga Singer; Nancy Spector; Abby Stewart; Dana Telem; Peter Ubel; Isis Settles

doi:10.1001/jama.2023.7232

. 2023 Jun 6;329(21):1848–1858. doi: 10.1001/jama.2023.7232

Workplace Harassment, Cyber Incivility, and Climate in Academic Medicine

Reshma Jagsi ^1,^2,^✉, Kent Griffith ¹, Chris Krenz ¹, Rochelle D Jones ¹, Christina Cutter ¹, Eva L Feldman ¹, Clare Jacobson ¹, Eve Kerr ¹, Kelly Paradis ¹, Kanakadurga Singer ¹, Nancy Spector ³, Abby Stewart ⁴, Dana Telem ¹, Peter Ubel ⁵, Isis Settles ⁴

¹Medical School, University of Michigan, Ann Arbor

²Emory University, Atlanta, Georgia

³College of Medicine, Drexel University, Philadelphia, Pennsylvania

⁴Department of Psychology, University of Michigan, Ann Arbor, Michigan

⁵School of Medicine, Duke University, Durham, North Carolina

Accepted for Publication: April 13, 2023.

^✉

Corresponding Author: Reshma Jagsi, MD, DPhil, Emory University, 1365 Clifton Rd NE, Atlanta, GA 30322 (rjagsi@emory.edu).

Author Contributions: Dr Jagsi and Mr Griffith had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Jagsi, Griffith, Cutter, Feldman, Jacobson, Kerr, Paradis, Singer, Spector, Stewart, Ubel, Settles.

Acquisition, analysis, or interpretation of data: Jagsi, Griffith, Krenz, Jones, Cutter, Feldman, Paradis, Singer, Telem, Settles.

Drafting of the manuscript: Jagsi, Griffith.

Critical revision of the manuscript for important intellectual content: Griffith, Krenz, Jones, Cutter, Feldman, Jacobson, Kerr, Paradis, Singer, Spector, Stewart, Telem, Ubel, Settles.

Statistical analysis: Griffith, Stewart.

Obtained funding: Jagsi, Singer, Settles.

Administrative, technical, or material support: Jagsi, Jones, Cutter, Telem, Settles.

Supervision: Jagsi, Singer, Spector.

Conflict of Interest Disclosures: Dr Jagsi reported receiving grants paid to her institution from the Susan G. Komen Foundation, the American Cancer Society, the Doris Duke Charitable Foundation, and Genentech; receiving personal fees from the Doris Duke Charitable Foundation, the Greenwall Foundation, and the law firm of Dressman Benziger Lavelle and Kleinbard LLC for serving as an expert witness; and having stock options in Equity Quotient (a company that evaluates culture in health care companies) for serving on the advisory board. Dr Cutter reported receiving grants from the Doris Duke Charitable Foundation and receiving personal fees from Wolters Kluwer, the RAND Corporation, and the Research Consortium for Health Care Value Assessment. Dr Feldman reported receiving grants from the Juvenile Diabetes Research Foundation. No other disclosures were reported.

Funding/Support: This work was supported by grant 5R01GM139842-03 from the National Institutes of Health.

Role of the Funder/Sponsor: The National Institutes of Health had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The views expressed in this article are those of the authors and do not necessarily reflect the official position of the National Institutes of Health.

Data Sharing Statement: See Supplement 2.

^✉

Corresponding author.

PMCID: PMC10245188 PMID: 37278814

Key Points

Question

Do experiences that reflect the culture of academic medicine (sexual harassment, cyber incivility, and positive or negative perceptions of climate) differ by gender, race and ethnicity, and lesbian, gay, bisexual, transgender, queer status, and are these factors associated with faculty mental health?

Findings

In this survey of clinician-researchers who received K08 or K23 career development grants from the National Institutes of Health, there were concerning rates of sexual harassment, cyber incivility, and negative perceptions of climate, which were experiences that were associated with poorer mental health.

Meaning

A cultural problem exists in academic medicine that disproportionately affects women and others from systematically marginalized populations, indicating an ongoing need for cultural transformation in the medical profession.

Abstract

Importance

The culture of academic medicine may foster mistreatment that disproportionately affects individuals who have been marginalized within a given society (minoritized groups) and compromises workforce vitality. Existing research has been limited by a lack of comprehensive, validated measures, low response rates, and narrow samples as well as comparisons limited to the binary gender categories of male or female assigned at birth (cisgender).

Objective

To evaluate academic medical culture, faculty mental health, and their relationship.

Design, Setting, and Participants

A total of 830 faculty members in the US received National Institutes of Health career development awards from 2006-2009, remained in academia, and responded to a 2021 survey that had a response rate of 64%. Experiences were compared by gender, race and ethnicity (using the categories of Asian, underrepresented in medicine [defined as race and ethnicity other than Asian or non-Hispanic White], and White), and lesbian, gay, bisexual, transgender, queer (LGBTQ+) status. Multivariable models were used to explore associations between experiences of culture (climate, sexual harassment, and cyber incivility) with mental health.

Exposures

Minoritized identity based on gender, race and ethnicity, and LGBTQ+ status.

Main Outcomes and Measures

Three aspects of culture were measured as the primary outcomes: organizational climate, sexual harassment, and cyber incivility using previously developed instruments. The 5-item Mental Health Inventory (scored from 0 to 100 points with higher values indicating better mental health) was used to evaluate the secondary outcome of mental health.

Results

Of the 830 faculty members, there were 422 men, 385 women, 2 in nonbinary gender category, and 21 who did not identify gender; there were 169 Asian respondents, 66 respondents underrepresented in medicine, 572 White respondents, and 23 respondents who did not report their race and ethnicity; and there were 774 respondents who identified as cisgender and heterosexual, 31 as having LGBTQ+ status, and 25 who did not identify status. Women rated general climate (5-point scale) more negatively than men (mean, 3.68 [95% CI, 3.59-3.77] vs 3.96 [95% CI, 3.88-4.04], respectively, P < .001). Diversity climate ratings differed significantly by gender (mean, 3.72 [95% CI, 3.64-3.80] for women vs 4.16 [95% CI, 4.09-4.23] for men, P < .001) and by race and ethnicity (mean, 4.0 [95% CI, 3.88-4.12] for Asian respondents, 3.71 [95% CI, 3.50-3.92] for respondents underrepresented in medicine, and 3.96 [95% CI, 3.90-4.02] for White respondents, P = .04). Women were more likely than men to report experiencing gender harassment (sexist remarks and crude behaviors) (71.9% [95% CI, 67.1%-76.4%] vs 44.9% [95% CI, 40.1%-49.8%], respectively, P < .001). Respondents with LGBTQ+ status were more likely to report experiencing sexual harassment than cisgender and heterosexual respondents when using social media professionally (13.3% [95% CI, 1.7%-40.5%] vs 2.5% [95% CI, 1.2%-4.6%], respectively, P = .01). Each of the 3 aspects of culture and gender were significantly associated with the secondary outcome of mental health in the multivariable analysis.

Conclusions and Relevance

High rates of sexual harassment, cyber incivility, and negative organizational climate exist in academic medicine, disproportionately affecting minoritized groups and affecting mental health. Ongoing efforts to transform culture are necessary.

This study evaluates academic medical culture, faculty mental health, and their relationship among faculty members who received National Institutes of Health career development awards from 2006-2009.

Introduction

The culture of academic medicine may foster mistreatment that disproportionately affects individuals who, regardless of their number, have been marginalized within a given society (minoritized groups) with implications for workforce vitality, which is the ability of individuals to persist, grow, and develop in pursuit of the profession’s mission. Social scientific research suggests that mistreatment is rooted in power and maintaining the status quo.^1,2 Women physicians, individuals with race and ethnicity that is underrepresented in medicine (defined as race and ethnicity other than Asian or non-Hispanic White), and those with lesbian, gay, bisexual, transgender, queer (LGBTQ+) status have been historically excluded from the profession, and these minoritized groups would be expected to have more experiences with sexual harassment, incivility, and negative climate because they are disrupting the status quo and may consequently be targeted with hostile treatment. These stressors lead to a lack of psychological safety, communicate unbelonging, and can affect mental health, compromising the vitality of these critical contingents of the professional workforce.^3,4,5

A report from the National Academies of Sciences, Engineering, and Medicine (NASEM) highlighted the challenges of sexual harassment,⁶ with higher rates in medicine than in other fields that are driven by sexist remarks and crude behaviors, which constitute a phenomenon of gender harassment, rather than sexual coercion or unwanted advances that more commonly draw attention to the subject.^3,7,8 The NASEM report⁶ concluded that sexual harassment in medicine required more rigorous investigation, particularly among faculty whose experiences had only been evaluated by brief measures.^9,10 The NASEM report⁶ further emphasized how sexual harassment is part of a broader cultural problem, which includes other forms of incivility, and noted the need for more data on how such experiences relate to characteristics beyond the binary gender categories of male or female assigned at birth (cisgender).

Since publication of the NASEM report,⁶ several groups have investigated these issues further. Using a 5-item measure of sexual harassment in annual faculty surveys from 2019-2021, the Association of American Medical Colleges found that one-third of women respondents and one-eighth of men respondents indicated having experienced sexual harassment, with considerable variability across specialties.¹¹ A few single-institution,¹² single-state,¹³ and single-specialty¹⁴ reports characterized attending physicians’ experiences using the full Sexual Experiences Questionnaire,^15,16,17 which is a validated, behaviorally based instrument used for self-reporting sexual harassment that was recommended by the NASEM. These reported experiences suggest even higher rates of harassment with meaningful consequences; however, they were limited by low response rates, narrow samples, and typically continued to focus on binary gender comparisons. They also tended not to include other measures of incivility that may be important, particularly in an increasingly virtual environment.

Therefore, the first, to our knowledge, in-depth study was initiated of sexual harassment, cyber incivility, and organizational climate in a US multispecialty faculty cohort. This cohort has been surveyed longitudinally since participants first received prestigious K-series career development awards from the National Institutes of Health between 2006 and 2009. The primary goal was a nuanced descriptive understanding of faculty experiences with sexual harassment, cyber incivility, and perceived climate as these reflect culture.^18,19 The analyses focused on variations by identity characteristics, hypothesizing that minoritized groups would have worse experiences, given ongoing evidence that career paths of women and those with minoritized race or ethnicity lag behind those of White men.^20,21,22 Furthermore, data are extremely limited regarding the experiences of LGBTQ+ faculty. In addition to understanding how experiences with sexual harassment, cyber incivility, and climate varied, the current study sought to explore associations of these experiences with mental health.

Methods

Study Sample

The 2021 mailing addresses were identified for 1375 of 1719 clinician-researchers who were first-time recipients of National Institutes of Health K08 or K23 career development grants from 2006-2009. A cover letter was mailed to these individuals that included the elements necessary for informed consent (the University of Michigan institutional review board waived documentation of consent) along with the 12-page questionnaire and a cash incentive. An additional 55 clinician-researchers were emailed materials, for a total of 1430 individuals surveyed. Nonrespondents were sent reminders and given opportunities to respond online. Respondents still in academic positions constituted the analytic sample.

Outcome Measures

Three aspects of culture (climate, sexual harassment, and cyber incivility) were evaluated as the primary outcomes to describe experiences by gender, race and ethnicity, and LGBTQ+ status. These variables and several others described below served as independent variables in the models for the secondary outcome of mental health.

To evaluate perceptions of climate, we used validated measures developed by the University of Michigan ADVANCE program²³ and adapted from the Texas A&M University Climate Survey²⁴ that asked respondents to rate their current workplace on 5-point scales anchored at either end by opposite terms such as hostile to friendly. Of these items, the authors of the original measures^23,24 identified 7 items to constitute a positive climate or general climate scale (the term general climate is used in the current study) and 5 items to constitute a tolerant climate or climate for diversity scale (the term diversity climate is used in the current study). The confirmatory factor analysis²⁵ used in the current study sample is described in the eMethods in the Supplement 1. Four items derived from the Culture Conducive to Women’s Academic Success measure²⁶ also were included (additional details appear in the eMethods in Supplement 1).

To evaluate sexual harassment, the Sexual Experiences Questionnaire^16,17 was used and participants were asked whether they experienced any of 20 unwanted behaviors from colleagues, superiors, or others at work within the past 2 years. With a goal of describing incidence rather than frequency, the responses were grouped by those who indicated ever experiencing each behavior and categorized by the type of harassment (gender harassment, unwanted sexual attention, or sexual coercion).

Measures of cyber incivility also were included (adapted from Lim and Teo²⁷) by asking participants to indicate the frequency with which they had experienced 8 cyber incivility behaviors via email within the past year. Responses, which ranged from not at all (score of 0 points) to all the time (score of 4 points), were averaged to create an e-incivility scale with high reliability (Cronbach α = 0.87). Respondents also were asked 4 items about incivility when using social media professionally (social media incivility).²⁸ Responses were grouped as yes vs no (and the responses indicating not applicable were omitted).

Mental health was evaluated with the 5-item Mental Health Inventory (MHI-5),^29,30 which has 2 items focused on anxiety and 3 items focused on mood. Each item is assessed with a 5-point scale, which varies based on responses from never (0 points) to always (4 points). The final score was transformed to vary from 0 to 100 points, with higher values indicating better mental health.

The primary outcomes (independent variables) related to gender, race and ethnicity, and sexual orientation were measured with categories that are further detailed in section L in the eText in Supplement 1. Additional independent variables in the models for assessment of mental health included self-reported parental status, marital status, and academic rank. Respondents were grouped using data from the National Institutes of Health Research Portfolio Online Reporting Tools Expenditures and Results module by medical specialty and using the current addresses of the respondents to determine geographic region in the US. The survey items appear in the eText in Supplement 1.

Statistical Analysis

The responses regarding the 3 primary outcomes of culture (climate, sexual harassment, and cyber incivility) are described and compared (1) between men and women; (2) among those who identified as White only, those who identified as Asian or Asian and White (Asian category), and all other races and ethnicities (underrepresented in medicine category); and (3) among those who selected only man or woman and heterosexual or straight (cisgender and heterosexual category) and those who selected the nonbinary, transgender, or other category for gender or who selected any other descriptor of sexual orientation (LGBTQ+ category). The climate and e-incivility scale scores were summarized using means with 95% CIs and t tests for between-group comparisons.

For the items derived from the Culture Conducive to Women’s Academic Success measure,²⁶ full distributions were compared by gender and LGBTQ+ status using the Cochrane-Armitage trend test and by race and ethnicity using cumulative logit models for the ordinal outcome. The measures of sexual harassment and social media incivility were grouped as ever vs never experiencing each of those behaviors and χ² tests were used for between-group comparisons. A series of linear regression models was constructed in which the dependent variable was the continuous MHI-5 score to explore associations of gender, race and ethnicity, and LGBTQ+ status; experiences of culture (climate, sexual harassment, and cyber incivility); and other independent variables listed with mental health (additional details appear in the eText in Supplement 1).

Given the low amount of missing data and the challenges associated with imputing the measures that were the focus of the current study, missing data were omitted in the analyses using case-wise deletion. All statistical analyses were conducted using SAS version 9.4 (SAS Institute Inc). All tests and associated P values are 2-sided and P < .05 is considered statistically significant.

Results

Of 1430 individuals surveyed, 915 responded (64%), of whom 830 remained in academia (422 men, 385 women, 2 in nonbinary gender category, and 21 who did not identify gender). Of the 830 individuals, there were 169 Asian respondents, 66 respondents underrepresented in medicine, 572 White respondents, and 23 respondents who did not report race and ethnicity. There were 774 respondents who identified as cisgender and heterosexual, 31 had LGBTQ+ status, and 25 who did not identify status (Table 1). The comparison of respondents vs nonrespondents showed no significant difference by binary gender (women constituted 46.3% of respondents and 42.5% of nonrespondents [P = .16]; the binary category and data were determined using public data).

Table 1. Characteristics of Study Sample by Binary and Nonbinary Gender Categories.

Characteristic	Binary gender category (cisgender)		Nonbinary gender or did not indicate (n = 23)
Characteristic	Men (n = 422)	Women (n = 385)	Nonbinary gender or did not indicate (n = 23)
Gender, No. (%)^a
Men	422
Women		385
Nonbinary			2 (8.7)
Other (did not answer)			21 (91.3)
Race and ethnicity, No. (%)^a
Asian	87 (20.6)	81 (21.0)	1 (4.3)
Underrepresented in medicine^b	37 (8.8)	29 (7.5)	0
White	293 (69.4)	275 (71.4)	4 (17.4)
Other (not reported)	5 (1.2)	0	18 (78.3)
Identity, No. (%)^a
Cisgender and heterosexual	405 (96.0)	367 (95.3)	2 (8.7)
LGBTQ+ status	14 (3.3)	15 (3.9)	2 (8.7)
Other (not reported)	3 (0.7)	3 (0.8)	19 (82.6)
Academic rank, No. (%)
Professor	251 (59.5)	198 (51.4)	10 (43.5)
Associate professor	152 (36.0)	173 (44.9)	12 (52.2)
Assistant professor	19 (4.5)	12 (3.1)	1 (4.4)
Other^c	0	2 (0.5)	0
Clinical work, median (IQR), h	14.0 (7-24)	10.0 (3-18)	15.0 (7.8-32.3)
Specialty, No. (%)
Medical	182 (43.1)	135 (35.1)	9 (39.1)
Women/children/family^d	55 (13.0)	100 (26.0)	4 (17.4)
Basic sciences or non-MD	55 (13.0)	110 (28.6)	5 (21.7)
Hospital-based	59 (14.0)	34 (8.8)	5 (21.7)
Surgical	39 (9.2)	6 (1.6)
Region, No. (%)
Midwest	99 (23.5)	76 (19.7)	3 (13.0)
Northeast	123 (29.2)	125 (32.5)	7 (30.4)
South	97 (23.0)	82 (21.3)	4 (17.4)
West	100 (23.7)	100 (26.0)	9 (39.1)
International, No. (%)	3 (0.7)	2 (0.5)	0

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Abbreviation: LGBTQ+, lesbian, gay, bisexual, transgender, queer.

^{^a}

Obtained via self-report using measures that provided closed-ended and write-in options. Additional details appear in the eMethods in Supplement 1.

^{^b}

Defined as race and ethnicity other than Asian or non-Hispanic White. Additional details appear in the eMethods in Supplement 1.

^{^c}

Department chair and senior scientist. Obtained via self-report using a measure that provided a write-in option.

^{^d}

Clinical specialties treating women, children, and families.

The Figure shows perceptions of climate by gender, race and ethnicity, and LGBTQ+ status. When converted to numerical scales in which lower numbers signify more negative ratings, women rated general climate more negatively than men (mean, 3.68 [95% CI, 3.59-3.77] vs 3.96 [95% CI, 3.88-4.04], respectively, P < .001). Women and men also differed significantly in the ratings for diversity climate (mean, 3.72 [95% CI, 3.64-3.80] vs 4.16 [95% CI, 4.09-4.23], respectively, P < .001). Women’s ratings of every subitem were significantly lower than men’s ratings (P < .05).

Respondents did not differ in the ratings for general climate by race and ethnicity (mean, 3.78 [95% CI, 3.64-3.92 among Asian respondents, 3.73 [95% CI, 3.49-3.97] among respondents underrepresented in medicine, and 3.84 [95% CI, 3.77-3.91] among White respondents, P = .54). The ratings for diversity climate were significantly different by race and ethnicity (mean, 4.0 [95% CI, 3.88-4.12] among Asian respondents, 3.71 [95% CI, 3.50-3.92] among respondents underrepresented in medicine, and 3.96 [95% CI, 3.90-4.02] among White respondents, P = .04). Specifically, ratings of racism were lower (indicating a perception of the climate as more racist) for respondents underrepresented in medicine than White respondents (mean, 3.63 [95% CI, 3.33-3.93] vs 4.14 [95% CI, 4.06-4.22], respectively, P = .02).

Ratings of general climate did not differ by LGBTQ+ status (mean, 3.83 [95% CI, 3.77-3.89] among cisgender and heterosexual respondents vs 3.71 [95% CI, 3.39-4.02] among LGBTQ+ respondents, P = .46). The ratings for diversity climate were not significantly different between cisgender and heterosexual respondents vs LGBTQ+ respondents (mean, 3.96 [95% CI, 3.91-4.01] vs 3.68 [95% CI, 3.37-3.99], respectively, P = .09). However, LGBTQ+ respondents rated the climate as more homophobic (lower score) than cisgender and heterosexual respondents (mean, 3.87 [95% CI, 3.49-4.25] vs 4.43 [95% CI, 4.37-4.49], respectively, P = .009).

Fewer women than men agreed that their salary was equitable (46.3% [95% CI, 41.2%-51.5%] vs 61.8% [95% CI, 56.9%-66.4%], respectively), that their comments in meetings are given appropriate credit and attention (72.0% [95% CI, 67.2%-76.4%] vs 84.1% [95% CI, 80.2%-87.4%]), and that they play an important role in decisions in the workplace (66.0% [95% CI, 61.0%-70.7%] vs 75.3% [95% CI, 70.9%-79.3%]; Table 2). Fewer respondents underrepresented in medicine than White respondents agreed that their comments in meetings are given appropriate credit and attention (67.2% [95% CI, 54.3%-78.4%] vs 79.8% [95% CI, 76.3%-83.0%], respectively) and that they were included in informal social gatherings with colleagues (46.9% [95% CI, 34.3%-59.8%] vs 74.4% [95% CI, 70.6%-77.9%], P < .001). Full distributions and comparisons by gender, race and ethnicity, and LGBTQ+ status appear in eTables 1-3 in Supplement 1.

Table 2. Perceptions of General Climate and Cyber Incivility.

	Agree with statement or had experience, No. (%) [95% CI]
	Gender		Race and ethnicity			LGBTQ+ status
	Men	Women	Asian	Underrepresented in medicine^a	White	Cisgender and heterosexual^b	LGBTQ+
Statements
My salary is equitable vs my peers	260 (61.8) [56.9-66.4]	177 (46.3) [41.2-51.5]	87 (51.8) [44.0-59.9]	29 (45.3) [32.8-58.3]	319 (56.0) [51.8-60.1]	416 (54.2) [50.6-57.7]	17 (54.8) [36.0-72.7]
The comments I make in meetings are given appropriate credit and attention	354 (84.1) [80.2-87.4]	275 (72.0) [67.2-76.4]	128 (76.2) [69.0-82.4]	43 (67.2) [54.3-78.4]	455 (79.8) [76.3-83.0]	601 (78.3) [75.2-81.1]	25 (80.6) [62.5-92.5]
I play an important role in decisions in my workplace	317 (75.3) [70.9-79.3]	252 (66.0) [61.0-70.7]	121 (72.0) [64.6-78.7]	40 (62.5) [49.5-74.3]	406 (71.2) [67.3-74.9]	540 (70.3) [66.9-73.5]	24 (77.4) [58.9-90.4]
I am included in informal social gatherings with my colleagues	297 (71.1) [66.4-75.4]	262 (68.6) [63.7-73.2]	111 (66.5) [58.8-73.6]	30 (46.9) [34.3-59.8]	418 (74.4) [70.6-77.9]	531 (70.0) [66.6-73.2]	25 (80.6) [62.5-92.5]
While using social media professionally, have you ever been…
Subjected to sexist comments?	19 (8.5) [5.2-12.9]	41 (21.8) [16.1-28.4]	15 (15.2) [8.7-23.8]	2 (6.9) [0.8-22.8]	45 (15.9) [11.8-20.6]	58 (14.7) [11.3-18.5]	4 (26.7) [7.8-55.1]
Subjected to racist comments?	27 (12.1) [8.1-17.1]	19 (10.3) [6.0-15.7]	21 (21.2) [13.6-30.6]	7 (25.0) [10.7-44.9]	18 (6.4) [3.9-10.0]	43 (11.0) [8.1-14.5]	3 (20.0) [4.3-48.1]
Personally targeted or attacked on social media?	51 (22.6) [17.3-28.6]	37 (19.6) [14.2-26.0]	20 (20.2) [12.8-29.5]	6 (20.0) [7.7-38.6]	63 (22.0) [17.2-27.0]	83 (20.8) [16.9-25.1]	6 (40.0) [16.3-67.7]
Sexually harassed on social media?	0 [0-1.3]	12 (6.4) [3.3-10.8]	2 (2.0) [0.2-7.1]	1 (3.5) [0.08-17.8]	9 (3.1) [1.4-5.9]	10 (2.5) [1.2-4.6]	2 (13.3) [1.7-40.5]

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Abbreviation: LGBTQ+, lesbian, gay, bisexual, transgender, queer.

^{^a}

Defined as race and ethnicity other than Asian or non-Hispanic White. Additional details appear in the eMethods in Supplement 1.

^{^b}

Defined based on survey self-response (additional details appear in the eMethods in Supplement 1).

Overall, 45.4% (95% CI, 40.5%-50.3%) of men and 72.7% (95% CI, 67.9%-77.1%) of women (P < .001) reported experiencing at least 1 form of workplace sexual harassment within the past 2 years. This did not vary significantly by race and ethnicity or LGBTQ+ status. At least 1 form of workplace sexual harassment within the past 2 years was reported by 57.7% (95% CI, 49.9%-65.3%) of Asian respondents, 59.4% (95% CI, 46.4%-71.5%) of respondents underrepresented in medicine, and 58.3% (95% CI, 54.1%-62.3%) of White respondents (P = .98) and by 58.5% (95% CI, 55.0%-62.1%) of cisgender and heterosexual respondents vs 61.3% (95% CI, 42.2%-78.2%) of LGBTQ+ respondents (P = .76). Details on the sexual harassment subtypes indicated by men vs women appear in the eFigure in Supplement 1. Women were significantly more likely than men to report experiencing gender harassment (71.9% [95% CI, 67.1%-76.4%] vs 44.9% [95% CI, 40.1%-49.8%], respectively, P < .001) and unwanted sexual attention (16.0% [95% CI, 12.5%-20.1%] vs 5.7% [95% CI, 3.7%-8.4%], P < .001). Sexual coercion was rare for both women and men (0.52% [95% CI, 0.06%-1.8%] vs 0.24% [95% CI, 0.01%-1.3%], respectively, P = .51).

The overall e-incivility score did not differ significantly between men and women (2.05 [95% CI, 1.98-2.12] vs 2.14 [95% CI, 2.06-2.22], respectively, P = .11). However, the e-incivility score differed by gender for 2 of the 8 subcomponents of the score: someone wrote something hurtful to you in an email (mean, 1.65 [95% CI, 1.56-1.74] for men vs 1.84 [95% CI, 1.73-1.94] for women, P = .005) and someone put you down or was condescending to you in an email (mean, 1.57 [95% CI, 1.48-1.65] for men vs 1.82 [95% CI, 1.72-1.92] for women, P < .001).

The overall e-incivility score was not significantly different by race and ethnicity (mean, 2.06 [95% CI, 1.95-2.17] among Asian respondents, 2.22 [95% CI, 1.79-2.21] among respondents underrepresented in medicine, and 2.09 [95% CI, 2.03-2.15] among White respondents, P = .33). However, the e-incivility score differed for 2 of 8 subcomponents of the score: someone wrote something hurtful to you in an email (mean, 2.0 [95% CI, 1.73-2.27] for respondents underrepresented in medicine vs 1.73 [95% CI, 1.65-1.81] for White respondents, P = .03) and someone made demeaning or derogatory remarks about you in an email (mean, 1.58 [95% CI, 1.33-1.83] for respondents underrepresented in medicine vs 1.37 [95% CI, 1.31-1.43] for White respondents, P = .03).

Women were more likely than men to report being subjected to sexist comments (21.8% [95% CI, 16.1%-28.4%] vs 8.5% [95% CI, 5.2%-12.9%], respectively, P < .001) and experiencing sexual harassment (6.4% [95% CI, 3.3%-10.8%] vs 0% [95% CI, 0%-1.3%], P < .001) when using social media professionally (Table 2). Asian respondents and those underrepresented in medicine were more likely to report being subjected to racist comments than White respondents when using social media professionally (21.2% [95% CI, 13.6%-30.6%] for Asian respondents, 25.0% [95% CI, 10.7%-44.9%] for respondents underrepresented in medicine, and 6.4% [95% CI, 3.9%-10.0%] for White respondents, P < .001). Respondents with LGBTQ+ status were more likely to report experiencing sexual harassment than cisgender and heterosexual respondents when using social media professionally (13.3% [95% CI, 1.7%-40.5%] vs 2.5% [95% CI, 1.2%-4.6%], respectively, P = .01).

In the evaluation of mental health, the mean score for the MHI-5 was 69.9 (SD, 16.1) and the median was 75 (IQR, 60-82.5). In the bivariable analysis, the MHI-5 scores were significantly different for women (mean, 66.9 [95% CI, 65.3-68.6] vs 72.83 [95% CI, 71.4-74.2] for men, P < .001), but not by race and ethnicity (P = .79) or by LGBTQ+ status (P = .39). Gender was significantly associated with MHI-5 score after adjusting for other demographic factors (5.7 points lower, indicating worse mental health) and was the only demographic covariate that was significantly associated with MHI-5 score (Table 3). When experiences with harassment, e-incivility, and climate were added in separate models, each was also significantly associated with MHI-5 score. No significant interactions between gender and cultural experience variables were identified and therefore not included.

Table 3. Multivariable Linear Regression Models to Explain Mental Health by Demographic and Experience Factors.

	Multivariable linear regression model, estimate (95% CI)^a
	0^b	1^c	2^d	3^e	4^e
Demographic factors
Intercept	73.19 (70.09 to 76.28)	75.67 (72.47 to 78.86)	73.80 (70.81 to 76.79)	72.84 (69.91 to 75.78)	72.15 (69.10 to 75.20)
Gender
Men	Reference	Reference	Reference	Reference	Reference
Women	−5.72 (−8.03 to −3.41)	−4.06 (−6.43 to −1.68)	−4.94 (−7.19 to −2.70)	−4.05 (−6.28 to −1.82)	−3.75 (−6.13 to −1.38)
Parental status
A parent	Reference	Reference	Reference	Reference	Reference
Not a parent	0.60 (−3.43 to 4.63)	0.28 (−3.72 to 4.27)	0.67 (−3.23 to 4.57)	0.25 (−3.64 to 4.14)	−0.40 (−4.44 to 3.63)
Marital status
Married or have domestic partner	Reference	Reference	Reference	Reference	Reference
Single, divorced, or widowed	−2.45 (−6.59 to 1.68)	−1.64 (−5.73 to 2.44)	−2.68 (−6.66 to 1.29)	−1.48 (−5.50 to 2.53)	−2.20 (−6.35 to 1.95)
LGBTQ+ status
Cisgender and heterosexual	Reference	Reference	Reference	Reference	Reference
LGBTQ+	−0.90 (−6.95 to 5.15)	−0.70 (−6.66 to 5.26)	−0.60 (−6.47 to 5.28)	−0.41 (−6.13 to 5.32)	0.61 (−5.32 to 6.54)
Race and ethnicity
White	Reference	Reference	Reference	Reference	Reference
Asian	−0.17 (−2.98 to 2.64)	−0.19 (−2.96 to 2.58)	−0.47 (−3.18 to 2.23)	0.23 (−2.45 to 2.90)	−0.40 (−3.17 to 2.37)
Underrepresented in medicine^f	0.85 ( −3.34 to 5.04)	0.84 (−3.29 to 4.97)	0.77 (−3.28 to 4.82)	2.24 (−1.81 to 6.28)	2.52 (−1.67 to 6.72)
Region
Northeast	Reference	Reference	Reference	Reference	Reference
Midwest	−0.55 (−3.73 to 2.63)	0.11 (−3.03 to 3.25)	−0.39 (−3.45 to 2.67)	−0.65 (−3.68 to 2.38)	0.24 (−2.91 to 3.39)
South	0.33 (−2.78 to 3.43)	0.12 (−2.94 to 3.18)	0.37 (−2.62 to 3.37)	−0.49 (−3.44 to 2.47)	−0.01 (−3.07 to 3.05)
West	1.05 (−2.01 to 4.10)	0.95 (−2.06 to 3.95)	1.27 (−1.68 to 4.22)	0.56 (−2.35 to 3.47)	0.82 (−2.19 to 3.83)
Academic rank
Professor	Reference	Reference	Reference	Reference	Reference
Associate professor	−1.41 (−3.79 to 0.96)	−1.29 (−3.63 to 1.05)	−2.90 (−5.22 to −0.58)	−0.89 (−3.15 to 1.37)	−1.17 (−3.51 to 1.18)
Assistant professor or other	1.57 (−4.08 to 7.21)	0.46 (−5.12 to 6.03)	−0.61 (−6.05 to 4.83)	3.11 (−2.30 to 8.52)	1.91 (−3.69 to 7.50)
Specialty
Medical	Reference	Reference	Reference	Reference	Reference
Basic sciences or non-MD	−1.06 (−4.12 to 2.00)	−1.29 (−4.31 to 1.74)	−1.08 (−4.03 to 1.86)	−0.65 (−3.57 to 2.26)	−0.91 (−3.93 to 2.11)
Women/children/family^g	1.41 (−1.51 to 4.33)	1.61 (−1.27 to 4.48)	1.76 (−1.06 to 4.59)	1.16 (−1.62 to 3.94)	1.15 (−1.72 to 4.03)
Hospital-based	−0.22 (−3.94 to 3.50)	−0.22 (−3.88 to 3.44)	0.42 (−3.16 to 4.01)	0.33 (−3.18 to 3.84)	−0.04 (−3.69 to 3.62)
Surgical	−3.14 (−8.34 to 2.07)	−2.38 (−7.51 to 2.74)	−1.53 (−6.60 to 3.55)	−0.35 (−5.36 to 4.65)	−2.49 (−7.64 to 2.65)
Experience factors
Sexual harassment
Did not experience sexual harassment		Reference
Experienced sexual harassment		−5.93 (−8.26 to −3.60)
e-Incivility score^h			−6.23 (−7.71 to −4.76)
Climateⁱ
General				5.95 (4.75 to 7.15)
Diversity					4.59 (3.12 to 6.05)

Open in a new tab

Abbreviation: LGBTQ+, lesbian, gay, bisexual, transgender, queer.

^{^a}

The 5 models were developed to evaluate whether baseline differences in mental health existed between demographic subgroups. The estimates are β coefficients from the regression models. All experience measures were not introduced simultaneously because of concerns about collinearity. In each of the models including experience factors (models 1-4), only 1 experience measure was introduced at a time to avoid multicollinearity.

^{^b}

This model began with a theoretically preselected set of demographic factors seeking to quantify any associations between minoritized group status and mental health. There were tests for interactions between any minoritized group status variables that were significant in model 0 (first model) and the experience variables introduced in models 1-4.

^{^c}

Model 1 included a binary indicator variable for having experienced sexual harassment as independent variables.

^{^d}

Model 2 was constructed to assess the e-incivility scale score.

^{^e}

Models 3 and 4 assess associations between climate scale scores and mental health.

^{^f}

Defined as race and ethnicity other than Asian or non-Hispanic White. Additional details appear in the eMethods in Supplement 1.

^{^g}

Clinical specialties treating women, children, and families.

^{^h}

Experienced any of the 8 uncivil behaviors via email (adapted from Lim and Teo²⁷).

^ⁱ

Evaluated using measures developed by the University of Michigan ADVANCE program²³ and adapted from the Texas A&M University Climate survey²⁴ to develop separate scales for general climate and diversity climate.

Discussion

Substantial differences in the experiences of certain medical faculty with sexual harassment, cyber incivility, and work climate persist. Key findings of the current study include observations that women were more likely than men to indicate experiencing gender harassment and unwanted sexual attention, rate both general and diversity climate as worse than men, and report certain forms of e-incivility and sexist comments and harassment when using social media professionally, suggesting that although women’s representation in medicine has improved, their experiences still reflect marginalization that requires attention.

Moreover, mental health was lower for women, and this difference appeared partly explained by differences in the measured cultural experiences. Men also frequently reported unwanted experiences. The lack of interactions between measures of cultural experiences and gender in the models for mental health suggests that these experiences also have consequences for men.

Respondents underrepresented in medicine also reported certain forms of e-incivility and racist comments when using social media professionally, along with lower diversity climate ratings within their organizations. Together, these results strongly suggest an ongoing need for specific interventions to transform culture in academic medicine.

Prior studies^{6,9,10,12,14,31} have suggested that medicine must cultivate civility, but these have been criticized for low response rates, narrow focus, dated samples, and lack of sufficiently detailed and validated outcome measures. The current study provides detailed, recent data that reveal the magnitude of the cultural problem that exists in academic medicine—and how that problem disproportionately affects women and other minoritized groups. Addressing bias and harassment in academic medicine is both a matter of professional ethics³² and problem affecting the vitality of the professional workforce necessary to deliver on its critical mission. This study was conducted during the COVID-19 pandemic, and it highlights the need for ongoing attention to equity, diversity, and inclusion.^33,34,35,36 These findings should motivate urgent, evidence-based interventions that are modeled upon promising practices that have already been identified.^37,38,39

The highest rates of sexual harassment occur in organizations that are perceived to tolerate such behavior.^4,40 Organizations that proactively develop, disseminate, and enforce sexual harassment policies are least likely to harbor such behaviors.⁴¹ These efforts must go beyond formalistic and symbolic legal compliance to engage workers from the ground up and leaders from the top down to ensure meaningful cultural change. Opportunities to share organizational wins and best practices abound, including the NASEM’s own Action Collaborative, the Association of American Medical Colleges’ Group on Women in Medicine and Sciences, and myriad others in professional specialty societies. The findings from the current study should motivate increased attention and resources toward these efforts.

The current study sought to compare the experiences of men and women and to explore experiences across the spectrum of gender identity and sexual orientation. Given the dearth of information about the experiences of gender-minoritized groups, we believe the descriptions provided in the current study fill a void. In the Association of American Medical Colleges surveys,¹¹ race and ethnicity and sexual orientation appeared to be predictive of sexual harassment. Future studies are necessary to build on this work and better understand in detail the experiences of LGBTQ+ individuals and those underrepresented in academic medical faculty, as well as to look at intersections of marginalized identities as a priority, including women from racial and ethnic groups underrepresented in medicine and Asian women.

Limitations

There are limitations to this study. First, there is a possibility of selection bias, which is mitigated somewhat by the survey response rate. Nevertheless, the sample of clinician-researchers who received K08 or K23 career development grants from the National Institutes of Health and who have remained in academic positions and responded to the survey may not reflect the entire underlying population of grant recipients, especially if those who left academic medicine experienced more extreme forms of negative culture or were more vulnerable to the negative effects.

Second, this study focused on recent rather than career-long experiences to minimize recall bias and was not designed to compare experiences of those who remained in academia vs those who departed academia before the survey. Future research should specifically collect data from individuals leaving academic positions about their experiences with the culture of academic medicine.

Third, this study includes a US multispecialty sample, but focuses on only 1 segment of the profession. Future research must consider samples from populations beyond the select group of mid-career academic faculty studied, especially because negative experiences with the culture of academic medicine early in one’s career may preclude attaining a career development grant in the first place, let alone persistence into mid-career.

Fourth, no survey study can completely avoid concerns about measurement bias, although the use of validated measures strengthens the reliability of the current study. Fifth, when interpreting findings, it is important to reflect not only on statistical significance but also on effect sizes and whether they are meaningful.

Sixth, due to the small numbers of respondents in specific subgroups of the LGBTQ+ community, we were limited by having to group diverse individuals together but still lacked statistical power to detect anything other than very large differences between their experiences and those of cisgender and heterosexual individuals who constituted the vast majority of respondents. Seventh, this is also true of the need to combine all respondents underrepresented in medicine into 1 category. Thus, any lack of difference by LGBTQ+ status or underrepresented in medicine status should not be interpreted as evidence that no differences exist.

Conclusions

The current study revealed concerning rates of sexual harassment, cyber incivility, and negative climate in academic medicine, with associations between these experiences and mental health. These reported experiences warrant ongoing efforts to transform the culture of the medical profession through action-oriented interventions.

Supplement 1.

eMethods

eText. Survey Items on Incivility, Harassment, Climate, Well-Being, and Demographics

eTable 1. Perception of Climate by Gender

eTable 2. Perception of Climate by LGBTQ+ Status

eTable 3. Perception of Climate by Race/Ethnicity

eFigure. Types of Sexual Harassment Experienced by Men and Women

Click here for additional data file.^{(323.4KB, pdf)}

Supplement 2.

Data sharing statement

Click here for additional data file.^{(13.3KB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

eMethods

eText. Survey Items on Incivility, Harassment, Climate, Well-Being, and Demographics

eTable 1. Perception of Climate by Gender

eTable 2. Perception of Climate by LGBTQ+ Status

eTable 3. Perception of Climate by Race/Ethnicity

eFigure. Types of Sexual Harassment Experienced by Men and Women

Click here for additional data file.^{(323.4KB, pdf)}

Supplement 2.

Data sharing statement

Click here for additional data file.^{(13.3KB, pdf)}

[joi230050r1] 1.Konik J, Cortina LM. Policing gender at work. Soc Justice Res. 2008;21(3):313-337. doi: 10.1007/s11211-008-0074-z [DOI] [Google Scholar]

[joi230050r2] 2.Berdahl JL. Harassment based on sex. Acad Manage Rev. 2007;32(2):641-658. doi: 10.5465/amr.2007.24351879 [DOI] [Google Scholar]

[joi230050r3] 3.Cortina LM, Jagsi R. What can medicine learn from social science studies of sexual harassment? Ann Intern Med. 2018;169(10):716-717. [DOI] [PubMed] [Google Scholar]

[joi230050r4] 4.Sojo VE, Wood RE, Genat AE. Harmful workplace experiences and women’s occupational well-being: a meta-analysis. Psychol Women Q. 2016;40(1):10-40. doi: 10.1177/0361684315599346 [DOI] [Google Scholar]

[joi230050r5] 5.Siad FM, Rabi DM. Harassment in the field of medicine: cultural barriers to psychological safety. CJC Open. 2021;3(12)(suppl):S174-S179. [DOI] [PMC free article] [PubMed] [Google Scholar]

[joi230050r6] 6.National Academies of Sciences, Engineering, and Medicine . Sexual harassment of women: climate, culture, and consequences in academic sciences, engineering, and medicine. Published 2018. Accessed January 10, 2023. https://nap.nationalacademies.org/catalog/24994/sexual-harassment-of-women-climate-culture-and-consequences-in-academic [PubMed]

[joi230050r7] 7.Cortina LM, Berdahl JL. Sexual harassment in organizations: a decade of research in review. Published 2008. Accessed January 10, 2023. https://sk.sagepub.com/reference/hdbk_orgbehavior1/n26.xml

[joi230050r8] 8.Beeler WH, Cortina LM, Jagsi R. Diving beneath the surface. J Clin Invest. 2019;129(9):3468-3471. [DOI] [PMC free article] [PubMed] [Google Scholar]

[joi230050r9] 9.Carr PL, Ash AS, Friedman RH, et al. Faculty perceptions of gender discrimination and sexual harassment in academic medicine. Ann Intern Med. 2000;132(11):889-896. [DOI] [PubMed] [Google Scholar]

[joi230050r10] 10.Jagsi R, Griffith KA, Jones R, et al. Sexual harassment and discrimination experiences of academic medical faculty. JAMA. 2016;315(19):2120-2121. [DOI] [PMC free article] [PubMed] [Google Scholar]

[joi230050r11] 11.Lautenberger D, Dandar V, Zhou Y; American Association of Medical Colleges . Understanding and addressing sexual harassment in academic medicine. Accessed January 10, 2023. https://www.aamc.org/data-reports/faculty-institutions/report/understanding-and-addressing-sexual-harassment-academic-medicine

[joi230050r12] 12.Vargas EA, Brassel ST, Cortina LM, et al. #MedToo: a large-scale examination of the incidence and impact of sexual harassment of physicians and other faculty at an academic medical center. J Womens Health (Larchmt). 2020;29(1):13-20. [DOI] [PubMed] [Google Scholar]

[joi230050r13] 13.Mathews E, Hammarlund R, Kullar R, et al. Sexual harassment in the house of medicine and correlations to burnout. Ochsner J. 2019;19(4):329-339. [DOI] [PMC free article] [PubMed] [Google Scholar]

[joi230050r14] 14.Subbiah IM, Markham MJ, Graff SL, et al. Incidence, nature, and consequences of oncologists’ experiences with sexual harassment. J Clin Oncol. 2022;40(11):1186-1195. [DOI] [PMC free article] [PubMed] [Google Scholar]

[joi230050r15] 15.McClain T, Kammer-Kerwick M, Wood L, et al. Sexual harassment among medical students. Workplace Health Saf. 2021;69(6):257-267. [DOI] [PubMed] [Google Scholar]

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PERMALINK

Workplace Harassment, Cyber Incivility, and Climate in Academic Medicine

Reshma Jagsi, MD, DPhil

Kent Griffith, MS, MPH

Chris Krenz, BA

Rochelle D Jones, MS

Christina Cutter, MD, MSc, MS

Eva L Feldman, MD, PhD

Clare Jacobson, MD

Eve Kerr, MD, MPH

Kelly Paradis, PhD

Kanakadurga Singer, MD, MA

Nancy Spector, MD

Abby Stewart, PhD

Dana Telem, MD

Peter Ubel, MD, PhD

Isis Settles, PhD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposures

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Study Sample

Outcome Measures

Statistical Analysis

Results

Table 1. Characteristics of Study Sample by Binary and Nonbinary Gender Categories.

Figure. Self-reported Perceptions of Climate by Gender, Race and Ethnicity, and LGBTQ+ Status.

Table 2. Perceptions of General Climate and Cyber Incivility.

Table 3. Multivariable Linear Regression Models to Explain Mental Health by Demographic and Experience Factors.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases