research paper on disability discrimination

• Research article
• Open access
• Published: 15 March 2018

A national survey on violence and discrimination among people with disabilities

• Jesper Dammeyer 1 &
• Madeleine Chapman 2  

BMC Public Health volume  18 , Article number:  355 ( 2018 ) Cite this article

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The aim of the study was to quantify levels of violence and discrimination among people with disabilities and analyze the effects of gender and the type and degree of disability.

The study analyzed data on self-reported violence and discrimination from a Danish national survey of 18,019 citizens, of whom 4519 reported a physical disability and 1398 reported a mental disability.

Individuals with disabilities reported significantly higher levels of violence than those without. Specifically, individuals reporting a mental disability reported higher levels of violence and discrimination. Significant gender differences were found with regard to type of violence: while men with disabilities were more likely to report physical violence, women with disabilities were more likely to report major sexual violence, humiliation and discrimination. Neither severity nor visibility of disability was found to be a significant factor for risk of violence.

Conclusions

This large-scale study lends support to existing research showing that people with disabilities are at greater risk of violence than people without disabilities. Further, the study found that people with mental disabilities were significantly more likely to report all types of violence and discrimination than those with physical disabilities. The findings also show that gender is significant in explaining the type of violence experienced and the experience of discrimination.

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Understanding disability

The World Health Organization (WHO) uses the term disability to refer to the physical or mental impairment of everyday functionality due to congenital conditions, injury or disease [ 1 ]. While this study follows the WHO conceptualization of disability as comprising impairment of everyday functionality, it is grounded in the understanding that people are disabled by the intersecting effects of impairment and social attitudes and barriers [ 2 ]. Further, the study is guided by the understanding that many mental health issues such as depression and anxiety may be caused by a combination of factors, including environmental and experiential factors. In this study, the term disability encompasses these understandings and is used to refer to a range of mental as well as physical health issues, including developmental disorders such as autism spectrum disorder and mood disorders such as depression. The key objective of this study is to explore the relationship between different types of disability and the experience of violence and discrimination.

Violence and discrimination among people with disabilities

Interpersonal physical and sexual violence contribute significantly to the global burden of physical and mental health problems, substance abuse, and early mortality [ 3 ]. As the World Report on Disability [ 4 ] highlights, people with disabilities are at greater risk of violence than those without disabilities. Due to ageing populations and the increasing global burden of disease and injury, the prevalence of disability worldwide – now estimated at 15% of adults – is predicted to rise [ 4 ], further underlining the importance of more research on the experience of violence among people with disabilities.

There are few studies that compare risks of violence among different disability groups within a large sample and none that compare risks of discrimination.

One large-scale study that highlights disability as a risk factor for violence is Khalifeh et al. [ 5 ] which analyzed data gathered from 44,398 adults through the British Crime Survey and estimated the risks of experiencing past-year violence. After adjusting for socio-demographic and other confounders, the study found that people with disabilities were at increased risk of experiencing violence compared to people without disability, with the risk greatest for those with mental disabilities (with relative odds ratio of 3.0). In their systematic review and meta-analysis of research on violence and disability, Hughes et al. [ 6 ] reported similarly that adults with disabilities were at a significantly higher risk of violence compared with non-disabled adults. They also found that the experience of past-year violence was highest (at 24%) among individuals with mental disabilities.

Even though a higher prevalence of violence among those with mental disabilities has been reported, there are no clear findings on the type of violence experienced nor the effects of other factors such as the specific type and severity of disability. However, gender has been reported to be an important factor. For example, Khalifeh et al. [ 7 ] found that women with chronic mental illness reported higher levels of intimate partner violence than men with chronic mental illness (the figures for reported past-year violence were 21% for women and 10% for men).

Disability-related discrimination is an issue of interest in legal and social science literature on disability [ 8 ]. There are some studies that draw attention to the implications of discrimination for well-being, for example highlighting links between underemployment, perceived discrimination, and negative well-being [ 9 ]. However, there are no large-scale studies on disability-related discrimination nor studies that address different forms of discrimination and examine the effects of various factors such as type, severity and visibility of disability. Some disabilities are clearly visible to others, thereby exposing individuals more to the risk of disability-related discrimination, but others may not be readily apparent. Such factors need to be addressed in research to better understand the operation of discrimination as distinct from violence.

Existing studies give a picture of the greater risks of violence faced by people with disabilities. However, there is an identified need [ 6 ] for more large-scale studies and, specifically, studies examining interactions between different forms of violence and possible risk factors. Khalifeh et al. [ 5 ] urge in particular further research on which subgroups of people with mental disabilities are at greatest risk of violence. Further, there is a need for large-scale research using detailed measures on disability-related discrimination. Thus, the objectives of this study are to provide an overview of violence and discrimination among people with disabilities through analysis of data from a national survey; and to compare the prevalence of different forms of violence and discrimination with respect to gender and the type, severity, and visibility of disability.

Sampling and participants

Data for this study were drawn from the Survey of Health, Impairment, and Living Conditions in Denmark, collected by The Danish National Centre for Social Research in 2012/2013 [ 10 ]. Using personal identification numbers, Statistics Denmark generated a random selection of 32,810 citizens aged from 16 to 65 years old. Selectees were sent an invitation with instructions about how to complete the questionnaire online. If they did not respond, they were offered a phone interview. Of the selectees, 18,957 (57.8%) responded, with 15,292 (81%) completing the questionnaire online and 3665 (19%) participating in a phone interview. Consent to participate was obtained for the Survey of Health, Impairment, and Living Conditions in Denmark.

The mean age of the participants was 43.3 ( SD  = 14.13). Of the total number of participants, 46.8% were men. Regarding education, 13% had completed five years or more of tertiary education, 38% had completed some years (less than five) of tertiary education, 29% had completed secondary education, and 20% had completed primary education.

Questionnaire and measurements

Physical and mental disabilities.

The main exposures were physical disability and mental disability. In the questionnaire, participants were asked if they had “a long-term physical health problem or disability” and/or “one or more mental disorders”. They were then asked to categorize their most serious physical and/or mental disability. The study grouped the response categories for physical disabilities as follows: (1) Motor and movement disorders; (2) Blindness and vision loss, despite use of glasses or contact lenses; (3) Deafness and impaired hearing, despite use of hearing aids or cochlear implants; speech and language difficulties; dyslexia; (4) Skin diseases; (5) Allergies and breathing difficulties; (6) Chronic conditions and progressive diseases; (7) Other health problem or disability. The questionnaire provided examples for the categories, such as cerebral palsy for motor and movement disorders. The study grouped the response categories for mental disabilities as follows: (1) Mental disorder caused by alcohol or substance use; (2) Schizophrenia and psychosis; (3) Mood disorders including depression and bipolar disorder; (4) Stress, phobias, anxiety, obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD); (5) Personality disorders, (6) Autism spectrum disorders; (7) Attention deficit hyperactive disorder (ADHD) or similar disorder; (8) Eating disorders; (9) Other mental disorders.

Severity and visibility of disability

The study also used measures of the severity and visibility of disability. In the questionnaire, participants were asked if their main physical and/or mental disability was “minor or major”. They were also asked: “Would a stranger recognize within five minutes that you have a disability/health problem/mental disorder?” The response categories for the latter were coded by this study as “always” and “sometimes/never”.

The outcomes were forms of violence and discrimination. For violence, the outcomes were separate forms of violence in the past 12 months, including physical violence, sexual violence, and non-physical violence. For non-physical violence, the question was: “In the past year, has someone: (1) Threatened you with violence (2) Humiliated, degraded or ridiculed you, or constantly criticized you; (3) Prevented you from accessing your money or bank account, blocked your bank card, or forced you to pay a sum of money or act as guarantor?” For physical violence, the question was: “In the past year, has someone: (1) Shaken you, pushed you or pulled your hair; (2) Hit or kicked you?” The study refers to (1) and (2) as “minor” and “major” physical violence respectively. A question on violence done to others was also included in this study, as follows: “Have you shaken, pushed, hit or kicked another person within the last year?” For sexual violence, the question was: “In the past year, has someone forced you to: (1) Kiss or hug; (2) Have sexual intercourse or engage in other sexual acts?” The study refers to (1) as “minor sexual violence” and (2) as “major sexual violence”.

• Discrimination

In the survey, the following definition of discrimination was provided: “Discrimination occurs when people are unfairly treated because they are perceived as different from others.” In the questionnaire, participants were asked: “Do you feel that you are discriminated against because of your disability?” Participants were then asked who discriminates against them (naming only the most important). Response categories were grouped into two for this study, as follows: (1) Employment and education (e.g. work managers, personnel at college/university, colleagues); (2) Services (e.g. staff in public administration, health-care professionals, home carers, and support staff, staff in shops, cinemas, buses, trains etc.).

Data analysis

Descriptive analysis of the frequency of violence and discrimination was carried out with respect to gender, type of disability, and severity and visibility of disability. Chi-square tests were completed to compare differences for outcomes on the basis of mental and physical disability, specific types of mental and physical disability, severity and visibility of disability, and gender. Further, logistic regressions models were built, with types of violence and discrimination as dependent variables, and gender, age, level of educational achievement, physical disability and mental disability as independent variables.

As reported in Table  1 , individuals with disabilities were significantly more likely to report all types of violence committed against them than those without disabilities. For example, whereas 3.2% ( n  = 403) of those without disabilities reported major physical violence in the last year, the figures were 3.8% ( n  = 173) for those with physical disabilities and 6.7% ( n  = 93) for those with mental disabilities. The regression models (see Table  6 ) showed that having a physical and mental disability was significant for all types of violence.. For example, the odds ratio for reporting major sexual violence was 4.30 for participants with a mental disability compared to participants without a mental disability.

People with mental disabilities were significantly more likely to report all types of violence than those with physical disabilities. This included violence done to others: 6.2% ( n  = 86) of those with mental disabilities reported this, compared to 2.9% ( n  = 131) of those with physical disabilities.

No significant differences were found for violence with respect to severity of disability and visibility of disability (see Table  2 ).

Gender and violence

Differences were significant for all categories of violence for men and women with mental disability as compared, respectively, with men and women without disability (Table  3 ). There were no significant differences in reporting of physical and sexual violence between men with physical disabilities and men without. For women with either physical or mental disabilities, reporting of all categories of violence was significantly higher than for women without disabilities, except for major physical violence for women with physical disability. For example, 0.8% ( n  = 55) of women without disabilities reported major sexual violence compared with 1.7% ( n  = 42) of women with physical disabilities and 5.0% ( n  = 45) of women with mental disabilities.

Comparing men and women with mental and physical disabilities, respectively, women were significantly more likely to report major sexual violence than men. Men with physical disabilities were significantly more likely than women with physical disabilities to report physical violence, the threat of violence, and violence against others. Comparing women and men with mental disabilities, there were no significant differences in reports of physical violence, the threat of violence, and violence against others. These findings were reflected in the regression models (see Table 6 ) which showed that gender was significant for all kinds of violence except for financial violence and minor sexual violence. The odds for men were higher than for women for physical violence, being threatened and violence against others. The odds for women were higher for major sexual violence and being humiliated compared to men.

Disability type and violence

With regard to type of physical disability, those with a motor disability reported higher levels of being threatened and lower levels of being humiliated than people with all other kinds of physical disability. Compared to people with all other kinds of physical disability, people with visual impairment reported higher levels of being humiliated, financial violence, major physical violence, and both minor and major sexual violence. Finally, those with allergies reported higher levels of being threatened, being humiliated, and minor and major physical violence than people with all other kinds of physical disability (see Table  4 ).

With regard to mental disability, the overall finding was that people with personality disorders, ADHD, autism spectrum disorder, and schizophrenia/psychosis reported significantly higher levels of violence than people with other kinds of mental disability (Table  5 ). People with stress and mood disorders reported significantly lower levels of violence than people with other kinds of mental disability.

People with mental disabilities were significantly more likely to report discrimination of both categories than those with physical disabilities (Table 1 ). Severity of physical disability was significant with respect to discrimination: those with major physical disabilities reported higher levels of discrimination in both categories than those with minor physical disabilities (Table 2 ). Those with major mental disabilities reported significantly higher levels of discrimination in services than those with minor mental disabilities. Finally, those with visible disabilities reported significantly higher levels of discrimination in services than those without.

With regard to gender, women with physical disabilities were significantly more likely than men with physical disabilities to report discrimination of both categories (Table 3 ). Women with mental disabilities were significantly more likely than men with mental disabilities to report discrimination in employment and education. In line with this, the regressions models showed that gender was significant for both types of discrimination (see Table 6 ).

Regarding type of disability, those with a motor disability, autism spectrum disorder, or schizophrenia/psychosis were significantly more likely than those with other types of physical or mental disabilities, respectively, to report discrimination of both categories (Tables  4 and 5 ). Those with a personality disorder were significantly more likely to report discrimination in services and those with ADHD were significantly more likely to report discrimination in employment and education. By contrast, those with a stress or mood disorder were significantly less likely to report discrimination of both categories.

The findings here lend support to existing research showing that individuals with disabilities are at increased risk of violence [ 5 , 6 ]. By analyzing data on various kinds of violence, the study indicates that the increased risk is associated with all the forms of violence measured: physical, sexual, and non-physical. The finding that participants with mental disability reported significantly higher levels of all categories of violence and discrimination than those with physical disability are in line with other studies showing the particular vulnerabilities of people with mental disabilities [ 5 , 6 ]. However, more focused studies are required to explore more precisely the nature of the relationship between mental disability and violence and discrimination (see Limitations).

The study’s findings in relation to gender both build upon and nuance previous research on disability and violence [ 7 ] and highlight the need for an intersectional approach to disability studies. Whereas men with disability reported more physical violence, women with disability reported more humiliation, discrimination and major sexual violence. For example, 5% ( n  = 45) of women with mental disabilities in this study reported past-year major sexual violence. This compares to the estimated EU-wide figure of 5% of women who have been raped since the age of 15 [ 11 ]. The finding of this study underlines an urgent need for more research to address the nature of the relationship between mental disabilities among women and the experience of sexual violence.

Neither the severity nor visibility of disability were significant in explaining the risk of violence. While perhaps surprising, this is in line with previous studies which have found that the degree of physical impairment does not always predict life outcomes [ 12 ]. However, this study found that degree of physical disability was significant for both categories of discrimination. Further research with respect to who commits violence and discrimination could shed light on risk factors, both within and outside the home.

The findings from this study suggest that women with disabilities are at increased risk of discrimination than men with disabilities. and further that those with mental disabilities are at greater risk of discrimination than those with physical disabilities. This study’s findings from a large-scale survey provide an overview of risk that can connect piecemeal studies on discrimination and disability, such as studies highlighting cases of workplace discrimination among those with mental health problems [ 13 ], and further underline the need for an intersectional understanding of risk.

Regarding findings with respect to disability type, attention is directed to the high levels of violence and discrimination reported by those with personality disorders, schizophrenia/psychosis, ADHD, and autism spectrum disorder. On discrimination specifically, the findings direct attention to motor disorders in addition to the above. However, these findings are offered with caution because of small group numbers.

Limitations

The first main limitation of this study might be a participation bias. The survey was designed for the general population and may have excluded those with severe cognitive impairment or communication difficulties. Further, this study did not include people above 65 years of age, thereby excluding a group of people among whom the prevalence of physical disabilities is high [ 14 ]. However, this had an advantage, which was the default exclusion of much age-related discrimination and violence.

The second main limitation of this study was that the data on disabilities were based on self-report rather than validated diagnoses of disability. This might have led to either under- or over-reporting of disability. However, the survey’s detailed level of questioning about type of disorder and its use of diagnostic terms were designed to promote specificity and reliability of reporting.

There may also be a self-report bias with respect to violence and discrimination. This is likely to be in the direction of under-reporting. First, as Hughes et al. [ 6 ] observe, the past-year criterion for violence likely results in conservative estimates as “many more will have suffered violence more than 12 months previously” (p.1627). Second, there may have been a disclosure bias with respect to domestic violence. As Khalifeh et al. [ 5 ] observe, it may be particularly difficult for people with disabilities to report domestic violence because of dependency on perpetrators and fear of institutionalization. It should also be noted here that there is some controversy about the ability of those with serious mental disorders to report traumatic events. However, research suggests the reliability of self-report among this group. For example, Goodman et al. [ 15 ] concluded from their research that the occurrence and severity of violence are reliably reported by people with serious mental health illness.

Another limitation of this study was that the cross-sectional design did not enable clear identification of whether disability or violence occurred first. However, this issue is largely mitigated by the past-year criterion for occurrence of violence, a study condition that Hughes et al. [ 6 ] applied for inclusion in their systematic review, and by the survey’s qualification of physical disabilities as “long-term”. As the survey did not provide this qualification for mental disabilities, the implications of findings with respect to mental disabilities are discussed in the study with more caution. For some kind of disabilities, bi-directional and compounding effects of violence and disability might exist [ 16 , 17 ]. For example, Khalifeh et al. [ 5 ] found that people with disabilities were at greater risk of psychological health problems following violence than non-disabled people. This study included participants’ reports on doing violence to others and found that significantly higher levels were reported by participants with personality disorder and ADHD. The experience of multiple victimization and the compounding effects of negative experience are topics that need further attention.

One further limitation concerns the inclusion of data relating to those with both physical and mental disabilities ( n  = 635) in the data for physical and mental disability groups respectively. While this potentially resulted in the over- or under-statement of rates of violence and discrimination, the decision was made to be inclusive of all those reporting physical and mental disabilities by not stripping out co-morbidity.

Finally, the number of cases within some of the disability groups was low and therefore any conclusions for these groups should be taken with caution.

Strengths of study

The strengths of this study were the large national sample and detailed survey data about the type and severity of disability and different forms of violence and discrimination. This enabled robust comparative analysis of the prevalence and risk of violence and discrimination.

Understanding the extent of violence against vulnerable groups is the first step in starting to combat it [ 6 ]. While this study’s design constrains conclusions, the findings here call attention to the significantly higher levels of violence reported by people with disabilities and particularly those with mental disabilities. Clinicians and other health professionals as well as service providers and employers should be cognizant of these patterns of vulnerability and the intersections with gender and other risk factors.

Further to increased awareness and screening, this study highlights the need for coordinated assessment of causes of violence and policies on prevention as well as treatment and support. Specifically, the high level of sexual violence among women reporting mental disabilities demands further inquiry and action. Further to this, the consistently high levels of reported threats of violence, humiliation, and financial abuse suggest the need for agencies to identify and tackle non-physical and domestic violence. This requires attunement to the factors contributing to the vulnerabilities of people with disabilities, including dependency on personal care, social isolation, and communication difficulties [ 6 , 18 ]. Specialist services to support people with disabilities facing domestic violence are required but seldom in place [ 5 ].

Finally, the findings on disability-related discrimination call for greater awareness of this issue and its social costs in terms of employment, education, and service provision. Discrimination should be approached with an understanding of its “institutionalized” nature which, to paraphrase the U.K. Macpherson Report on racism [ 19 ], can be “seen or detected in processes, attitudes, and behaviour which amount to discrimination through unwitting prejudice, ignorance, thoughtlessness, and stereotyping which disadvantage people with disabilities.” The findings here hopefully provide some grounding for future research and action on discrimination that addresses multiple factors and the apparently increased risk for those with mental disabilities and women with disabilities.

Abbreviations

Attention deficit hyperactive disorder

Obsessive-compulsive disorder

Post-traumatic stress disorder

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Acknowledgements

We would like to thank the Danish National Centre for Social Research (SFI), Steen Bengtsson and colleagues for access to data.

No funding to be reported for this study.

Availability of data and materials

The datasets analysed during the current study are available in the CSSR database, http://cssr.surveybank.aau.dk/webview/ .

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Department of Psychology, University of Copenhagen, Øster Farimagsgade 2a, 1353, Copenhagen K, Denmark

Jesper Dammeyer

Department of Psychology, University of Westminster, London, England

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JD analyzed the data and wrote the first draft of the manuscript. MC assisted in analyzing the data, wrote the first draft of the manuscript and edited the manuscript. Both authors have read and approved the manuscript.

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Correspondence to Jesper Dammeyer .

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Dammeyer, J., Chapman, M. A national survey on violence and discrimination among people with disabilities. BMC Public Health 18 , 355 (2018). https://doi.org/10.1186/s12889-018-5277-0

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Research brief: experience of discrimination and the ada.

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Experience of Discrimination and the ADA

An ada knowledge translation center research brief, sarah parker harris.

Courtney Mullin

Department of Disability and Human Development

University of Illinois at Chicago

The Americans with Disabilities Act (ADA) is a civil rights law that creates a legal framework for people with disabilities to address discrimination. Passed in 1990, the ADA represents bipartisan support for disability inclusion in all aspects of public life. Through the ADA, disability is a recognized source of discrimination, similar to “race, color, religion, sex, or national origin” within the Civil Rights Act of 1964. The ADA allows individuals with disabilities to challenge discrimination in the realms of employment, public services, and places of public use. The overarching goal of the ADA is to promote equal opportunity, full participation, independent living, and economic self-sufficiency for all people with disabilities.

ADA and Experiences of Discrimination

Developing a law that prohibits discrimination and creates regulations around access was, and continues to be, an important step in addressing barriers to inclusion. Disability-based discrimination is often related to both prejudices as well as broader social barriers that deny people with disabilities equal opportunities. Some researchers describe the goal of the ADA “…to integrate persons with disabilities into the social mainstream,” (p. 13). 1  The ADA has regulations to address structural barriers (i.e. physical and programmatic issues) and discriminatory practices, in order to impact attitudes towards disability.

Much of the research on discrimination is about causes and frequency of negative attitudes held by people without disabilities. This research brief looks at the experiences of discrimination from the perspective of people with disabilities as a way to better understand the influence of the ADA.

What the Research Says

Discrimination comes in many different forms. Research throughout the last three decades highlights how people with disabilities experience discrimination and negative attitudes. This research brief organizes these ideas as well as how people with disabilities respond to discriminatory experiences. The following section is divided into three areas where there is information from people with disabilities reporting and describing their experiences with discrimination. While people with disabilities experience discrimination in various domains of their public and private lives, these are some topics for which researchers have begun to document the perceptions and experiences of people with disabilities.

Differences in Experiences

The experiences of discrimination amongst people with different disabilities are diverse. Demographic factors have been shown to affect both prevalence and type of discrimination. For example, people whose need for accommodations change at different times, such as people with mental health conditions, are more likely to report workplace discrimination than people with other types of impairments. 2  Another study found that people with physical disabilities experience different attitudes and misperceptions in the workplace when compared to other groups, such as people with learning disabilities. 1  Furthermore, race, gender, and socioeconomic class have also been shown to impact and compound experiences of disability-based discrimination. 3  African Americans, women, and people with low incomes are all more likely to report disability-based discrimination in health care. 3

Social factors such as family, social class, race, and religion also influence how people understand their rights and types of resources available to address inequalities . 1  Timing of a disability onset or diagnosis is also a critical factor, as people have varying kinds of resources at different times in their lives. One study furthers this idea by exploring the relationship between age and disability discrimination through data from the Equal Employment Opportunity Commission (EEOC), the agency in charge of enforcing the ADA in employment. 4  There is evidence that older workers are more likely to perceive and file complaints regarding employment discrimination. These variances highlight the diversity within the disability community and how people with disabilities experience discrimination in different ways. Recognizing differences in experience is noteworthy as is acknowledging the widespread prevalence of disability-based discrimination.

Employment is one of the most documented and researched areas regarding the ADA and disability-based discrimination. Though prohibited in the ADA, discrimination in the workplace has been a longstanding issue for people with disabilities. Nearly one in ten working adults with disabilities reported experiencing some kind of workplace discrimination within the five years after the passage of the ADA, and almost a third of these respondents permanently exited the workforce. 5

Workplace discrimination is often subtle, however people with disabilities have expressed that negative attitudes towards disability influence their success in employment. 6  One study, which involved sending mock job applications, found that those who disclosed disability (either spinal cord injury or Autism) received 26% fewer expressions of employer interest than applicants that did not include a disability disclosure. 7  Stigmatizing attitudes have been perceived by people with disabilities to negatively impact progress in their careers through not getting hired, being denied promotions, having extended probationary periods, or being treated differently than coworkers without disabilities. 6,7,8,9,10  In a study conducted by the Center for Talent Innovation as described in an article published by the  Harvard Business Review , a third of survey respondents with disabilities indicate that they had experienced negative bias in the workplace such as feeling underestimated, insulted, excluded, or had coworkers appear uncomfortable because of their disability. 9  Almost half of these respondents (47%) also report that they would never achieve a leadership role in their company, regardless of their performance or qualifications. 9

Disclosing a disability, or sharing a disability status, is clearly influenced by experiences of discrimination. In one study, less than half of respondents with disabilities (39%) report that they had disclosed to a manager and even fewer had told other colleagues (24%); only 4% of respondents told clients about their disabilities. 11  Reasons for employees with disabilities to hide their disability status include fear of teasing, harassment, potential changes in coworker relationships, being perceived as less capable, and reduced progress in their careers. Not disclosing a disability status has been described as “allowing people with disabilities to be employed ‘without fear of prejudice or discrimination’” (p. 487). 12

Another study found that people with disabilities who do not disclose on a job application, but later disclose their disability status at work, are also met with discriminatory behaviors such as coworker unease, inappropriate questions, and assumptions about their capability. 8  Choosing to disclose a disability status is a delicate situation due to the prevalence of disability discrimination, however there are noted benefits of disclosure for some. For example, one study estimates that employees with disabilities who disclose are more content (65% versus 27%) and less isolated (8% versus 37%) at work than employees who do not disclose. 11

Experiences of employment discrimination are not limited to attitudes, as people with disabilities may face other types of structural barriers. Examples include lack of physical accessibility in the workplace, such as absence of accessible restrooms, inaccessible equipment to perform job tasks, and lack of access to reasonable accommodations. 1  This physical inaccessibility can also impact feelings of isolation. Another study identifies barriers to inclusion in the workplace by interviewing employees with disabilities in large, public-sector organizations. 13  The study reveals that people with disabilities experience both physical and social segregation at work. One of the participants of this study describe how their office places employees with disabilities in “a little corner spot where nobody can see them” (p. 145). 13  The segregated desk location not only physically isolates the participant but also prevents social interactions with colleagues. Access discrimination such as this translates into business concerns as feelings of disability-based discrimination have been shown to significantly reduce job satisfaction. 14

Home and the Community

In addition to work, people with disabilities also experience discrimination in access to housing and the community. Institutionalization is a longstanding issue in the disability community, and often refers to the physical segregation of people with disabilities living and/or spending time in areas that are designated solely for people with disabilities. In a landmark decision as part of Olmstead vs L.C., the U.S. Supreme Court ruled that unjustified segregation violates the ADA. However, there are still many people with disabilities who live and spend time in institutional settings. Researchers explored this topic and found that people with intellectual disabilities who live in institutions report experiences of exclusion and discrimination. 15  These reports include notes of overly restrictive environments, lack of privacy, and difficulty getting involved in the community because of the physical and social segregation as a result living in an institutional setting.

Institutionalization is not the only issue related to community living and experiences of discrimination for people with disabilities. Though not regulated by the ADA, housing is a major issue and source of discrimination for people with disabilities. A study sponsored by the U.S. Department of Housing and Urban Development found that people who are deaf or hard of hearing face significant barriers during the home seeking process, including communicating with housing providers and learning about available units. 16  Additionally, people who use wheelchairs face barriers at several points in the home finding process, including locating accessible units, setting up appointments with providers to be shown units, and getting responses to reasonable modification requests. 16  These issues are made worse by the fact that 14-29% of federally funded housing facilities are estimated to violate federal regulations regarding access. 17

Social and Public Spaces

People with disabilities may experience discrimination when trying to access public spaces. For example, social stigma is another issue faced by people with disabilities. Researchers describe disability stigma, or negative attitudes or misconceptions towards disability, as a relationship between knowledge (ignorance), attitudes (prejudice), and behavior (discrimination). 18  These aspects are well documented in disability-based discrimination. In fact, people with mental health conditions report concerns about being viewed unfavorably based on their disability status, and over half of the respondents said that they have heard offensive statements about mental illness. 19  These factors shape public awareness about the capability of people with disabilities. 20  Many of the mentioned access barriers are rooted in negative attitudes that surround disability.

Another noteworthy example of disability discrimination is access to voting. A research team reviewed information from the U.S. 2012 elections and found that almost a third (30.1%) of voters with disabilities experienced some kind of difficulty in the voting process, which differs greatly from those without disabilities (8.4%). 21  The most common barrier was being able to see the ballot and understanding how to use the voting machines. Voting is a foundational right, and access barriers prohibit the participation of people with disabilities. This exemplifies a sentiment in other literature, that feelings of discrimination faced by people with disabilities can influence identifying as a citizen. 22

Responding to Discrimination

People with disabilities deal with discrimination and stigma in a variety of ways. Some people with disabilities choose to ignore negative attitudes, in order to not perpetually feel upset or the need to consistently react to negative interactions. 1  People with disabilities may not identify negative interactions as discriminatory if they do not have language or words to describe their experiences. 1  In fact, people with disabilities are hesitant to use the ADA or seek litigation due to social factors and describe a “threshold,” or feelings of a “minimum” level, of discrimination that must be reached prior to taking action through the ADA.

While choosing to take legal action is a complex decision, it is a powerful way for people with disabilities to respond to discrimination. Trends in legal filings change over time and are influenced by contextual factors. A review of EEOC case data shows a decrease in allegations from 2001- 2008, prior to the passage of the ADA Amendments Act (ADAAA), which greatly broadened the definition of disability and redefined the intent of the ADA. 23  Since the ADAAA was enacted, there has been a steady increase in allegations regarding disability discrimination. However, many cases are not closed in favor of claimants (i.e. people with disabilities). In fact, a review of EEOC claims from 1992-2011 found only 23.4% of cases are closed with merit, meaning that they affirmed disability discrimination, while 76.6% of cases are closed without merit, meaning in favor of the employer. 23  Additionally, claimants who are perceived as disabled rather than claimants with documented disabilities, are more likely to file charges related to disability discrimination and have cases ruled in their favor. 24  Most discrimination cases are related to job retention or quality of work; the most common allegations of workplace discrimination are discharge and failure to receive reasonable accommodations. 23  Though discrimination in hiring is less common, it is also notable as legal cases regarding hiring are closed in favor of people with disabilities at higher rates than other allegations. 25

The goal of this brief is to present a 'state of the state' of how people with disabilities perceive discrimination in relation to the ADA, the types of issues experienced, and outcomes of these events. People with disabilities face significant discrimination in many areas, including employment and in public and private aspects of life- some of which are covered in this research brief. To date, the majority of research is related to employment and there is limited information related to other areas of private and public life. While disability-based discrimination is a major facet of life for people with disabilities, these experiences are not universal and are influenced by many factors. Responding to discrimination also varies, and people with disabilities must make complex decisions when choosing to invoke legal action such as through the ADA. There is growing public interest in experiences of disability discrimination, and there is a need for more research on experiences of discrimination particularly from the perspective of people with disabilities.

Examples from the ADA National Network

Below are a few examples of how the ADA national network are addressing the issues raised in this brief. For further information on how the ADA Centers can help with issues related to the ADA, please contact the  ADA National Network here .

• Giving advocacy tools:  A person with vision and hearing disabilities contacted ADA center staff regarding his rights to travel by taxi or public transportation with his service dog. He was very pleased with the explanation he received. After some discussion, the staff person provided the caller with a laminated copy of the explanation, so he could show it to cab drivers where he lives. Having information on hand is helpful to share when traveling with his service dog and helping to advocate for his rights.
• Ensuring parking access:  A person reached out to the ADA center to ask a question about accessible street parking regulations, as two spots were added outside of her office that she did not think looked accessible. The technical assistant shared the guidance regarding street accessible parking design and the caller forwarded the information to the city administration. Within 24 hours, the city began to properly mark the spots and the owner of the building moved a bench to align with accessible parking regulations.
• Newsworthy information:  Another ADA Center was contacted by a local news station after a wheelchair user reached out to discuss blocking the access aisles in accessible parking spaces. Technical assistants provided information to the news reporter about the purpose of access aisles. A few days later, the reporter followed up with the ADA Center and shared they had received positive comments about the story and how it changed peoples’ attitudes and future actions to help keep access aisles unblocked.
• Engel, D. M., & Munger, F. W. (2003). Rights of inclusion: Law and identity in the life stories of Americans with disabilities. University of Chicago Press.
• Chan, F., McMahon, B. T., Cheing, G., Rosenthal, D. A., & Bezyak, J. (2005). Drivers of workplace discrimination against people with disabilities: The utility of attribution theory. Work, 25(1), 77-88.
• LaVeist, T. A., Rolley, N. C., & Diala, C. (2003). Prevalence and patterns of discrimination among US health care consumers. International Journal of Health Services, 33(2), 331-344.
• Bjelland, M. J., Bruyere, S. M., Von Schrader, S., Houtenville, A. J., Ruiz-Quintanilla, A., & Webber, D. A. (2010). Age and disability employment discrimination: Occupational rehabilitation implications. Journal of occupational rehabilitation, 20(4), 456-471.
• Kennedy, J., & Olney, M. (2001). Job discrimination in the post-ADA era: Estimates from the 1994 and 1995 National Health Interview Surveys. Rehabilitation Counseling Bulletin, 45(1), 24-30.
• Beatty, J. E. (2012). Career barriers experienced by people with chronic illness: A US study. Employee Responsibilities and Rights Journal, 24(2), 91-110.
• Ameri, M., Schur, L., Adya, M., Bentley, F. S., McKay, P., & Kruse, D. (2018). The disability employment puzzle: A field experiment on employer hiring behavior. ILR Review, 71(2), 329-364.
• McKinney, E. L., & Swartz, L. (2019). Employment integration barriers: experiences of people with disabilities. The International Journal of Human Resource Management, 1-23.
• Sherbin, L. & Taylor Kennedy, J. (2017, December) The Case for Improving Work for People with Disabilities Goes Way Beyond Compliance. Harvard Business Review. Retrieved from  https://hbr.org/2017/12/the-case-for-improving-work-for-people-with-disabilities-goes-way-beyond-compliance .
• Vickers, M. H. (2009). Bullying, disability and work: A case study of workplace bullying. Qualitative Research in Organizations and Management: An International Journal, 4(3), 255-272.
• Jain-Link, P. & Taylor Kennedy, J. (2019, June). Why people hide their disabilities at work. Harvard Business Review. Retrieved from https://hbr.org/2019/06/why-people-hide-their-disabilities-at-work .
• Goldberg, S. G., Killeen, M. B., & O'Day, B. (2005). The disclosure conundrum: How people with psychiatric disabilities navigate employment. Psychology, Public Policy, and Law, 11(3), 463.
• Robert, P. (2003). Disability oppression in the contemporary U.S. capitalist workplace. Science & Society, 67(2), 136-159.
• Perry, E. L., Hendricks, W., & Broadbent, E. (2000). An exploration of access and treatment discrimination and job satisfaction among college graduates with and without physical disabilities. Human Relations, 53(7), 923-955.
• Jahoda, A., & Markova, I. (2004). Coping with social stigma: People with intellectual disabilities moving from institutions and family home. Journal of intellectual disability research, 48(8), 719-729
• Aranda, C. L. (2015). Targeting Disability Discrimination: Findings and reflections from the national study on housing discrimination against people who are deaf and people who use wheelchairs. Cityscape, 17(3), 103-122.
• Froehlich-Grobe, K., Regan, G., Reese-Smith, J. Y., Heinrich, K. M., & Lee, R. E. (2008). Physical access in urban public housing facilities. Disability and Health Journal, 1(1), 25-29.
• Thornicroft, G., Brohan, E., Kassam, A., & Lewis-Holmes, E. (2008). Reducing stigma and discrimination: Candidate interventions. International journal of mental health systems, 2(1), 3.
• Dickerson, F. B., Sommerville, J., Origoni, A. E., Ringel, N. B., & Parente, F. (2002). Experiences of stigma among outpatients with schizophrenia. Schizophrenia bulletin, 28(1), 143-155.
• Hampson, M., Hicks, R., & Watt, B. (2016). Understanding the employment barriers and support needs of people living with psychosis. The Qualitative Report, 21(5), 870-886.
• Schur, L., Adya, M., & Kruse, D. (2013). Disability, voter turnout, and voting difficulties in the 2012 elections. Report to US EAC and RAAV.
• Barton, L. (1993). The struggle for citizenship: the case of disabled people. Disability, Handicap & Society, 8(3), 235-248.
• McMahon, M. C., & McMahon, B. T. (2016). The National EEOC ADA research project: History, available data, and basic findings. Journal of Vocational Rehabilitation, 44(3), 333-342
• Draper, W. R., Reid, C. A., & McMahon, B. T. (2011). Workplace discrimination and the perception of disability. Rehabilitation Counseling Bulletin, 55(1), 29-37.
• McMahon, B. T., Hurley, J. E., West, S. L., Chan, F., Roessler, R., & Rumrill, P. D. (2008). A comparison of EEOC closures involving hiring versus other prevalent discrimination issues under the Americans with Disabilities Act. Journal of Occupational Rehabilitation, 18(2), 106-111.

For More Information, Please Contact:

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SUGGESTED CITATION:  Parker Harris, S., Gould, R., and Mullin, C. (2019).  ADA research brief: Experiences of discrimination and the ADA  (pp. 1-6). Chicago, IL: ADA National Network Knowledge Translation Center.

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• Published: 15 September 2022

How we can make academia more disability inclusive

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Nature Human Behaviour volume  6 ,  pages 1324–1326 ( 2022 ) Cite this article

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The low representation of academics with disabilities is a longstanding problem on which progress has been slow. Drawing on my research on disability-related barriers and my experiences of disability, I make six practical suggestions for how academic staff and people with disabilities can help make academia more disability inclusive.

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I thank M. Levitt, C. Oppenheim and M. Thelwall for their helpful feedback, and F. Moreira for his helpful research support with the visually intensive parts of this paper.

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Data analysis, participants, drivers of perceived disability-based discrimination, manifestations of perceived disability-based discrimination, conclusions, perceived disability-based discrimination in health care for children with medical complexity.

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Stefanie G. Ames , Rebecca K. Delaney , Amy J. Houtrow , Claudia Delgado-Corcoran , Justin Alvey , Melissa H. Watt , Nancy Murphy; Perceived Disability-Based Discrimination in Health Care for Children With Medical Complexity. Pediatrics July 2023; 152 (1): e2022060975. 10.1542/peds.2022-060975

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Disability-based discrimination in health care can lead to low quality of care, limited access to care, and negative health consequences. Yet, little is known regarding the experiences of disability-based discrimination in health care for children with medical complexity and disability. An understanding of disability-based discrimination in pediatrics is needed to drive change and improve care.

We conducted in-depth, semistructured interviews with caregivers of children with medical complexity and disability. Participants were purposefully recruited through national advocacy and research networks. Interviews were conducted via video conferencing, recorded, and transcribed. Data collection and analysis occurred iteratively. An inductive thematic analysis approach with constant comparison methods was used to identify themes that form a conceptual framework of disability-based discrimination in health care.

Thirty participants from diverse backgrounds were interviewed. Six themes emerged, forming a conceptual framework of disability-based discrimination in health care. Three themes described drivers of discrimination: lack of clinician knowledge, clinician apathy, and clinician assumptions. Three themes described manifestations of discrimination: limited accessibility to care, substandard care, and dehumanization.

Children with medical complexity may face disability-based discrimination in health care. Themes describing the drivers and manifestations of discrimination offer a conceptual framework of disability-based discrimination. Understanding the drivers and acknowledging perceived manifestations can provide insight into improving patient care for children with disabilities.

Disability-based discrimination in health care can lead to gaps in care and poor health outcomes for patients with disabilities. Evaluation of physicians has demonstrated a lack of confidence and skill in caring for patients with disabilities which may perpetuate disparities.

Caregivers of children with medical complexity report experiences of disability-based discrimination in the healthcare of their child. These experiences are driven by clinician knowledge, apathy, and assumptions, and manifest as lack of access to care, substandard care, and dehumanization.

Discrimination in health care occurs in 1 out of every 5 patients. 1   Although racial and gender discrimination in health care are important topics of active research, disability-based discrimination in health care is largely overlooked, particularly in children with disability. 2   Disability-based discrimination in health care is complex and may reflect physician lack of confidence and skill in caring for patients with disabilities, lack of available time or resources for complex care, or explicit and implicit biases including inferences regarding quality of life and worthiness. 3 – 5   Regardless of root causes, disability-based discrimination in health care can impact patient health and well-being, leading to poor outcomes with severe consequences. 6   Adults who have experienced disability discrimination report significantly higher rates of depression, poor mental functioning, and overall worse health and quality of life than those who have not. 7 , 8   Disability discrimination can also harm patient clinical outcomes by potentiating gaps in health care access and avoidance of necessary care for vulnerable patients, further exacerbating inequities. 9 – 12  

Children with medical complexity represent a subset of children with disability who have substantial health needs and disability leading to frequent interactions with the health care system. 13   The experiences of these children in the health care systems are unique, and their perspectives of disability-based discrimination in health care are poorly understood. A deeper understanding of perceived experiences of discrimination through caregiver perspectives is needed to inform education and interventions to improve care for children with medical complexity. Therefore, the primary objective of this study was to qualitatively describe the perspectives and experiences of family caregivers of children with medical complexity regarding disability-based discrimination in health care.

This is a qualitative study using semistructured individual interviews and a thematic analysis approach to inductively identify themes related to disability-based discrimination from the perspective of caregivers of children with medical complexity. 14   The research team for this study consisted of a pediatric critical care physician, a general pediatrician, 2 physical medicine and rehabilitation and disability physicians, a pediatric palliative care physician, and 2 qualitative research experts. The consolidated criteria for reporting qualitative research checklist was used during study design, analysis, and reporting. 15  

Eligible participants were parents/caregivers of a child with medical complexities who were aged ≥1 year and reported a disability related to physical, cognitive, communication, and/or social functioning. Medical complexities were defined as having ≥2 organ systems affected and either technology dependencies, functional impairments, or high health care resource utilization. In addition, the caregiver must have perceived that their child experienced discrimination in a health care setting because of disability, which was assessed during a screening questionnaire before enrollment ( Supplemental Information ).

Parents/caregivers of children with medical complexity were recruited and selected by purposive sample techniques to participate in an interview to explore experiences of discrimination in health care. Participants were recruited through a variety of methods to ensure a diverse and geographically broad sample with experiences in different health care settings in the United States. First, participants were recruited through flyer advertisements distributed by Family Voices, Inc, a national family advocacy group working to support families of children with special health care needs. Additional participants were directly recruited through medical clinics focused on care of children with medical complexity through the Children and Youth with Special Healthcare Needs National Research Network, a research network of major pediatric hospitals in the United States. Sampling was continued until thematic saturation occurred.

Participants received a gift card after their participation to compensate for their time and expertise. This study was approved by the institutional review board, and informed consent was reviewed before participation in the study.

Individual in-depth interviews of 30 participants were conducted between November 2021 and August 2022. An interview guide was developed in conjunction with parent partners recruited through a local parent advisory council. The guide was organized around a stigma framework and included open-ended questions and probes related to experiences of discrimination, impacts on the child, and impacts on caregivers ( Supplemental Information ). 16   Interview questions were piloted with a parent of a child with disability and refined for phrasing and content on the basis of feedback.

Interviews were conducted in English (by S.G.A.) or Spanish (by C.D.) on the basis of participant preference. All interviews were conducted via video conferencing because of geographic distribution of participants, with only the participant and the interviewer present. Interviews lasted between 30 and 90 minutes, and were audio-recorded and transcribed verbatim by a third-party transcription service.

Participants completed a demographic survey for the purpose of describing the sample and ensuring recruitment of a racially, socioeconomically, and geographically diverse population. The survey included questions related to age, sex, race and socioeconomic status, and information regarding their child including age and number of health care visits annually.

Data analysis and data collection occurred iteratively, to revise the interview guide and develop a more nuanced understanding of disability-based discrimination in health care. We applied grounded theory principles to build our conceptual model on the basis of the experiences of participants. Grounded theory is defined by systematic collection and concurrent analysis of qualitative data to allow themes and theories to emerge from the data themselves rather than building from a priori hypotheses. 14  

Data management and analysis were conducted using Dedoose software (Version 9.0.54, Los Angeles, CA: SocioCultural Research Consultants, LLC). Coding began with a line-by-line evaluation of the first 5 transcripts by 2 analysts (S.G.A. and R.K.D.). The analysts met to review codes and reach consensus on an initial codebook that captured emerging themes related to disability-based discrimination in health care. The codebook was refined as researchers revised and expanded codes with subsequent analysis. All transcripts were dually coded (S.G.A. and R.K.D.) to ensure trustworthiness. Any coding discrepancies were discussed and resolved through consensus.

After coding, the analysts ran code reports and wrote analytic memos in which codes and text were evaluated for concepts and categories of data and comparison among participants. The research team discussed codes and memos to group concepts and evaluate for emergent themes using axial coding. Data collection and analysis were complete when thematic saturation had occurred, which was determined when no new themes or information emerged and themes were felt to adequately determine a conceptual framework. 17  

Overall, 30 participants were recruited from 15 states ( Fig 1 ). The majority of caregiver participants were female (25 of 30), ranging from ages 26 to 55 years old, and married (20 of 30). Their children with medical complexity ranged from age 18 months to 18 years. Most caregivers reported that their children had >20 health care encounters annually and were insured through Medicaid. Child and participant characteristics are shown in Table 1 .

Geographic representation of participant location by state.

Child and Caregiver Participant Demographic Information

Estimated annual average number of health care encounters, including emergency department, urgent care, inpatient, outpatient, and subspeciality care.

IQR, interquartile range.

Six themes emerged surrounding perceived disability-based discrimination in a health care setting. Three themes were categorized as perceived drivers of discrimination (clinician lack of knowledge, clinician apathy, and clinician assumptions) and 3 themes were categorized as manifestations of discrimination (limited accessibility to care, substandard patient care, and dehumanization). These themes generate a framework of experiences of interpersonal discrimination in a health care setting for children with medical complexities and their families ( Fig 2 ).

Conceptual framework of interpersonal disability-based discrimination in health care.

“ What I’ve often found is, we got a lot of blanket statements about the nonviability of this diagnosis or just … what am I trying to say? Just the hopelessness around the diagnosis. But not many providers actually knowing what to do to treat, right?”

Illustrative Quotes for Themes Describing Drivers of Perceived Disability-Based Discrimination in Health Care for Children With Disability

“ My perception is that [clinicians] wanted to take care of the patient that didn’t have a severe, special need. I don’t know. They just didn’t seem like they cared to even treat [my daughter].”

“ They are acting as you’re a waste of resources or you are not worth whatever, and they’re gate keeping … They’re being influenced by their perception of disability or kids with this diagnosis or whatever it is. They act as gatekeeper and you are trying to do everything you can to knock that gate down .”

“ A lot of times, these [clinicians] that are counseling you on these (medical) decisions, they see such a small piece of that person’s life. They either only see them when they’re in the hospital and they’re at their sickest, or they only see them when they come in for an appointment, so they see them for 30 minutes every 3 or 6 months or something like that. So, I don’t think it’s not necessarily with bad intent, but they don’t have a positive impression of disabilities or medical needs and things like that.”

“[My child] has specialists. I need [the pediatrician] for the simple, basic pediatric stuff. Like write the referrals, take her weight, do her annual checkup. [The pediatrician] said ‘I really don’t think that I can serve you.’ And I say, ‘Can you just be honest with me? What is it?’ She goes, ‘I’m just not comfortable. I’m not comfortable caring for your daughter.’”

Themes, Subthemes and Exemplar Quote for Manifestations of Perceived Interpersonal Disability-Based Discrimination in Health Care for Children With Disability

OT, occupational therapy.

Additionally, lack of appropriate accommodations inhibited care for some families. Examples of missing appropriate accommodations included lack of wheelchair scales, accessible doors, wheelchair ramps, and parking for larger vehicles. The experiences of feeling unwelcome at a medical practice and being provided reasonable accommodations were further challenged by cultural, racial, and language barriers that were perceived to further decrease willingness to care for a child with disability. For example, participants from minoritized groups described interactions in the health care system where treatment of pain was inappropriate because of assumptions of race, language services were not offered so care was not adequate, and interactions with clinicians were strained because of racial and ethnic differences.

“ [Doctors told me], ‘She’s been through so much. And do you really want to put her through more?’ All these things and I’m thinking, if this were a typical child, would you be telling this parent, ‘Don’t treat this cancer?’ Or would you be saying, ‘Here’s the number to St. Jude’s?’”

“I think the assumption is pain looks like they’ll pull away, pain looks like they’ll cry, pain looks like that. She doesn’t respond to pain that way, but it is still painful to her. It’s still aversive.”

“They mistreated her, and treated her like a robot. Every single time a nurse walked in the room, they treated her like she was not even there.”

“[The doctor said], ‘Well, you can [read] if it makes you feel better, but she’s not really learning, and she’s not really responding like other kids. She responds like a dog.’ That’s literally what he said. Those were his words, and you think this is the clinic for people with special health care needs.”

In this study, caregivers of children with medical complexity describe discrimination against their children in the health care setting. This data informed a conceptual framework of interpersonal disability-based discrimination in pediatric health care ( Fig 2 ), which includes drivers and manifestations. This framework validates caregiver experiences and can help clinicians to recognize and address microaggressions and explicit discrimination in health care encounters, and also identifies specific targets for better preparing the health care workforce to render quality care to pediatric patients with disability.

Clinicians’ lack of knowledge regarding disability was perceived to be a key driver of discrimination. Although this driver emerged from caregiver perceptions in our study, previous research aligns with this assessment, because clinicians commonly report significant gaps in knowledge and skills, as well as a general lack of comfort in caring for patients with disability. 18   Unfortunately, lack of knowledge likely contributes to attenuated and substandard care for children with disability. In a survey, physicians reported a lack confidence in providing quality of care for adult patients with disability, with only 56% strongly agreeing that they welcomed patients with a disability into their practice. 5   Accessibility to quality care for patients with disability is further inhibited by lack of appropriate accommodation, as was found in our study. Previous research has noted that physicians lack knowledge about reasonable accommodations for disabilities, and do not feel obligations to provide accommodations. 18 , 19   Although not yet studied well in pediatric health care, clinicians’ limited self-efficacy in caring for patients with disability may perpetuate disparities in health care accessibility and contribute to poor health outcomes. 20 – 22  

Across the interviews, clinicians’ implicit bias toward individuals with disabilities emerged as a key driver of discrimination. Caregivers shared examples of clinicians assuming children with disabilities have a negative quality of life or are less worthy of care, leading to biased medical decision-making, dehumanizing encounters, and substandard care with suboptimal outcomes. When quality of life assumptions are conflated with futility, resource rationing and fatal medical decisions can result. 6 , 23 , 24   Importantly, previous research has shown clinician assumptions of quality of life in both adults and children with disability are often grossly incorrect. 5 , 25   Clinicians often predict quality of life to be poor for patients with disability as compared with patient- or parent-reported quality of life, which is often reported to be good to excellent. 25   This concept is known as the disability paradox and represents a significant implicit bias against disability because of mispredictions of quality of life by health care professionals. 26  

Finally, clinician apathy emerged as a driver of disability-based discrimination in health care. For many caregivers, this driver often led to encounters in which clinicians were perceived to dehumanize children with medical complexity or have a negative attitude regarding disability. This lack of interest may stem from clinician inexperience, feelings of burden because of structural barriers, or implicit bias. 18   Caregivers reported strategies to mitigate dehumanization of their child, including sharing stories of their child and posting pictures in their hospital room to demonstrate their life outside of the hospital.

The emergence of lack of knowledge, bias, and apathy as key drivers of disability-based discrimination in health care identifies an urgent need for further education and disability training in clinicians. As the number of children with medical complexity increases, it is imperative that postgraduate medical education curricula address these knowledge gaps. Unfortunately, current training in disability is felt to be inadequate in medical and nursing education, leading to gaps in knowledge and negative attitudes of health professionals toward persons with disability. 27 – 31   Pediatric clinicians would benefit from increased education with curriculum focused on patients with medical complexity and disability. 32   One potential intervention is the incorporation of established core competencies for health care professionals into accreditation and licensure standards. 33   Other potential education-focused interventions for improving knowledge and regarding disability and medical complexity and reducing bias in pediatric trainees may include contact-based approaches or immersive curriculum. 34 – 37  

There were limitations to this study. First, because participants were recruited from clinics or advocacy organizations that serve families with children with complex medical needs, the sample may be biased to exclude patients who do not have access to comprehensive care or are not part of a disability-focused community. The recruitment of these samples was purposeful for qualitative research, but may not reflect the experience of other caregivers of children with disability. In addition, the experience of interpersonal discrimination represents an interaction between at least 2 people. In this study, only caregivers of children with disability were participants and therefore this conceptual model lacks the perceptions of clinicians in caring for children with disability. Given the focus of perceptions of discrimination, the caregiver experience develops an important model, and future work should focus on improved understanding of clinician perceptions and experiences in pediatric health care.

Children with medical complexity are dependent on the health care system to meet their health needs. Unfortunately, their experiences in health care are threatened by discrimination because of their disability. The results of our qualitative study provide a conceptual framework of disability-based discrimination in health care for children with themes emerging encompassing both the drivers and manifestations of discrimination between clinicians and their pediatric patients. Addressing the drivers and acknowledging perceived manifestations can provide insight into improving patient care for children with medical complexity and all children with disability.

Dr Ames conceptualized and designed the study, designed the data collection instruments, collected data, conducted the initial analyses, drafted the initial manuscript, and critically reviewed and revised the manuscript; Drs Murphy, Houtrow, and Alvey conceptualized and designed the study, contributed to data analysis, and critically reviewed and revised the manuscript; Dr Delaney designed the data collection instruments, collected data, conducted the initial analyses, and critically reviewed and revised the manuscript; Dr Delgado collected data, and critically reviewed and revised the manuscript; Dr Watt supervised data collection and analysis, and critically reviewed and revised the manuscript for important intellectual content; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2023-061604 .

This program is supported by the Health Resources and Services Administration of the US Department of Health and Human Services, under UA6MC31101 Children and Youth with Special Health Care Needs Research Network. This information or content and conclusions are those of the authors and should not be construed as the official position or policy of, nor should any endorsements be inferred by, the Health Resources and Services Administration, Health and Human Services, and the US government.

FUNDING: Supported by a pilot grant from the University of Utah Health Equity Research Core in the Woman and Child Institute.

CONFLICT OF INTEREST DISCLOSURES: The authors have indicated they have no conflicts of interest relevant to this article to disclose.

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Diversity and Discrimination in Research Organizations: Theoretical Starting Points

Diversity and Discrimination in Research Organizations

ISBN : 978-1-80117-959-1 , eISBN : 978-1-80117-956-0

Publication date: 1 December 2022

This article outlines the theoretical foundations of the research contributions of this edited collection about “Diversity and Discrimination in Research Organizations.” First, the sociological understanding of the basic concepts of diversity and discrimination is described and the current state of research is introduced. Second, national and organizational contextual conditions and risk factors that shape discrimination experiences and the management of diversity in research teams and organizations are presented. Third, the questions and research approaches of the individual contributions to this edited collection are presented.

• Comparative research
• Implicit bias

Müller, J. , Striebing, C. and Schraudner, M. (2022), "Diversity and Discrimination in Research Organizations: Theoretical Starting Points", Striebing, C. , Müller, J. and Schraudner, M. (Ed.) Diversity and Discrimination in Research Organizations , Emerald Publishing Limited, Leeds, pp. 3-30. https://doi.org/10.1108/978-1-80117-956-020221001

Emerald Publishing Limited

Copyright © 2023 Jörg Müller, Clemens Striebing, and Martina Schraudner

Published by Emerald Publishing Limited. This work is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this work (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Purpose of this Edited Collection

The era of team science has long since dawned ( Wang and Barabási, 2021 ; Pavlidis et al., 2014 ). Diverse teams are considered to have the potential to work particularly efficiently. Creative thinking, diversity of perspectives and the ability to solve complex problems might be pronounced in diverse teams, which has not only been shown for multidisciplinary but also gender-diverse teams (Abdalla et al., 1999; Bear and Woolley, 2011 ; Østergaard et al., 2011 ). Such skills are key competencies for research organizations that want to be influential and internationally-recognized sites for cutting-edge research.

However, in order for the individual members of a team to work well, research organizations need to provide a productive and naturally non-discriminatory working environment. The fact that bringing together and integrating researchers and their diverse backgrounds in effective teams is precarious due to the structural conditions of the research system – that is, it does not happen on its own – will be further discussed here. To harness the positive effects of diversity, it must be managed proactively ( Nielsen et al., 2018 ). In this context, the edited collection has the following purposes:

to contribute rare quantitative analyses of the extent of discrimination according to diverse socio-demographic characteristics of individuals in research-performing organizations;

to contribute analyses of the contextual organizational factors that affect the perception of discrimination within research-performing organizations, and

to seek the connection to practice by highlighting options for action.

The publication explores discrimination in research organizations, by which we mean all forms of organizations whose main purpose is to conduct research. The focus is on public research organizations such as universities or non-university research institutions (represented in the edited collection primarily by the German Max Planck Society). Research departments of companies – which in our view operate more according to the rules of the private sector than academia – are not included.

In principle, discrimination can be discussed for all areas of society and is regularly relevant simply due to its strong significance for the working climate and the well-being of individuals and teams. The relevance of research-performing organizations as a research topic seems to be additionally given by the political efforts of advanced (trans-)national innovation systems to combat systemic discrimination and the major role that effective diversity management plays for successful cooperative creative processes. At a political level, as editors and researchers active in national and international projects we experience the European Commission as a particularly proactive actor. With its “Horizon Europe” funding programme for research and innovation, the EC also promotes research projects and practical measures to reduce discrimination and create an inclusive research culture in the research systems of its member states. In doing so, it strives to strengthen international mobility and the competitiveness of a common European research area as part of its mandate laid down in Article 179 of the EU Treaty. 1

Diversity and Discrimination: A Sociological Definition

Conceptual understanding of discrimination.

Research on discrimination in the labor market and work organizations has lost none of its relevance. This continued interest by researchers and practitioners is partly due to the fact that discrimination has become more subtle while still producing adverse effects for disadvantaged social groups. Over the decades, theory as well as empirical research has moved away from understanding discrimination as deliberate and intentional acts of exclusion perpetuated by individuals toward more complex and elusive mechanisms including cognitive “implicit bias” ( Quillian, 2006 ), “microaggressions” ( Sue, 2010 ), unfair and biased organizational processes ( Nelson et al., 2008 ), or the systemic nature of what Barbara Reskin (2012) has called “ über discrimination.”

Nonetheless, while discriminatory practices have become less overt ( Sturm, 2001 ), their effects continue to be felt in a very direct and real way by individuals as well as organizations. Findings presented by Jones et al. (2016) in their meta-analysis show that subtle forms of discrimination are “at least as substantial, if not more substantial” (italics original) than overt forms regarding diminishing the physical and mental health of individuals, job satisfaction, or organizational commitment, to name just three of its effects. The resulting reduced well-being and self-esteem of staff has organizational-level consequences as employees’ work attitudes decline, turnover intentions increase or job performance dwindles, affecting the overall effectiveness of firms (for a review, see Colella et al., 2012 ). Thus, while it has become more difficult to detect discrimination, its negative consequences are as direct and powerful as ever, calling for equally strategic and systemic counter-measures.

Discrimination has a long and substantive research pedigree in the social and behavioral sciences, with contributions spanning several disciplines including economics, sociology, psychology, management and law. Although the explanatory models for discrimination differ across these fields of knowledge, there is a certain agreement on its basic definition: discrimination involves the differential treatment of individuals based on functionally irrelevant status cues such as race or gender ( Merton, 1972 ; Altonji and Blank, 1999 ).

Unpacking this definition first implies recognizing that discrimination is based on group membership and as such it never targets a person due to individual reasons. Discrimination happens because individuals are perceived as belonging to a social group delineated by gender, race or national origin, age, health conditions or disability, religion, and/or sexual orientation ( Colella et al., 2012 ; Baumann et al., 2018 ). These categories often do not function as unified, mutually-exclusive entities, but rather they “intersect” and can thereby aggravate experiences of oppression and power ( Collins, 2015 ).

Second, discrimination implies an “unjustified” differential treatment that occurs due to social group membership rather than actual differences in terms of task-relevant qualifications, contributions, or performance. Thus, job opportunities, promotions or rewards (e.g., wages) differ between women and men, even when comparing equally qualified and experienced persons. Consequently, discrimination is considered not only unfair but also illegal in many contexts.

Third, discrimination refers to behavior rather than solely beliefs and attitudes. Although the psychological literature predominately explains discrimination with references to prejudice and stereotypes, this is insufficient to constitute an act of discrimination ( Fiske et al., 2009 ). For discrimination to occur, actions need to be carried out that exclude, disadvantage, harm, harass or deprive the members of a less favored group compared to the members of a more favor group. Although most research conceives discrimination as negative behavior against disadvantaged groups, it can also involve positive behavior, that is, giving advantages to already-privileged groups. In fact, as Nancy DiTomaso (2020, 2013) argues, for the perpetuation of social inequality, the

positive actions taken on behalf of those who are already advantaged may be as consequential or more so than the negative actions that deny opportunity to those who are disadvantaged.

Conceptual Understanding of Diversity

Similar to research on discrimination, research on workplace diversity continues to be a burgeoning academic field. As Faria (2015) suggests, diversity research came into being in the US during the 1980s as a specific reaction against the previous social justice-based Equal Employment Opportunity (EEO) and Affirmative Action (AA) policies dealing with discrimination. Driven by an increasingly heterogeneous workforce and economic globalization, these justice-based policies were considered to be inefficient and costly, and replaced in favor of an emerging business case for diversity. Whereas discrimination involves a moral component in terms of the “unjustified” differential treatment ( Altman, 2011 ), diversity relinquishes these moral and legal burdens, concentrating instead on a pragmatic strategy to increase the corporate bottom line ( Litvin, 2006 ). Diversity research therefore attenuates regulatory approaches for ameliorating the negative effects of discrimination and instead emphasizes proactive measures to capitalize on heterogeneous resources available in different work settings. For diversity research, the focus on measurable profits implied the establishment of a matrix of quantification where certain clear-cut, easily observable demographic differences could be set in relation to equally quantifiable, dependent outcomes. Backed up by the predominant positivist research tradition in the US, demographic differences according to gender, age, race as well as functional differences such as educational background were thus operationalized and enshrined as measurable, stable markers of identity to be harnessed by Human Resource Departments and Management for improved profitability.

As a result, a major difference between discrimination and diversity approaches in workplace settings concerns the role reserved for markers of social identity such as age, gender, or race. While diversity scholars conceived these differences in terms of a-historical, personal attributes, discrimination scholars are mostly attentive to the ways in which these individual attributes delineate group-based membership, which in turn is tied to historically-grown positions of privilege and power ( Prasad, Pringle, and Konrad, 2006 ).

Today, diversity research has increasingly overcome its initial and overly simplistic conceptions of fixed identity attributes, partly driven by the largely inconsistent findings of its initial research program, which failed to establish any clear-cut linear relationship between diversity attributes and economic benefits ( Haas, 2010 ). While subsequent work has become more aware of the contextual nuances that moderate and mediate the effects of diversity ( van Knippenberg and Schippers, 2007 ; Joshi and Roh, 2007 , 2009 ), other approaches appear to have come full circle in terms of recognizing the importance of power and status processes for working groups ( van Dijk and Van Engen 2013 ; Ravlin and Thomas 2005 ; DiTomaso et al., 2007 ). As van Dijk et al. (2017) rightly emphasize, diversity research needs to take into account that

members of different social groups are likely to be perceived and approached differently because of their membership in a given social category […] and, in part as a consequence, may behave differently (p. 518).

Diversity and Discrimination — Common Ground

Thus, as these recent developments suggest, discrimination and diversity research are becoming more closely aligned. This is especially apparent from the combination of the underlying psychological models in work groups and their organizational context factors. As we argue, social categorization models need to be combined with status-/power-based approaches (e.g., AA and equal opportunities) to work group diversity, prevent discriminating behaviors and enable organizations to take full advantage of their diverse human resources. Studies of discrimination and diversity appear in this sense as two sides of the same coin, suggesting that measures leading to a reduction of discrimination not only reduce adverse effects at the individual level but also hold the potential to create more productive and effective work environments.

Approaches to Studying Discrimination and Diversity

Levels of analysis.

While research on diversity primarily operates at the level of teams and small- to medium-sized work groups ( Roberson, 2019 ; van Knippenberg and Schippers, 2007 ), research on discrimination can target the micro-, meso- and macro-level of society or a combination of these levels of analysis. At the macro-level, the magnitude and persistence of discrimination has been well documented in relation to race and gender in employment, housing, credit markets, schooling and consumer markets ( Pager and Shepherd, 2008 ). For example, concerning housing and credit markets, Pager and Shepherd (2008) summarize that “blacks and Hispanics face higher rejection rates and less favorable terms in securing mortgages than do whites” (p. 189). Although differential treatment varies across countries and even cities, discrimination remains pervasive and an important barrier to residential opportunities. Gender-based discrimination in the labor market – to use a second macro-level example – is just as widespread and structural as race-based inequalities. The wage gap between women and men remains at an estimated 16 percent globally ( International Labour Office, 2018 ). In the EU-28, women in Research & Development earn on average 17 percent less than their male colleagues (European Commission, 2019). Together with the horizontal segregation of women and men in certain labor market segments and vertical segregation restricting women from access to decision-making positions, these macro-level forms of discrimination constitute defining structural fault lines of contemporary labor markets.

While macro-level accounts usually produce evidence regarding the extent of structural disadvantages between social groups, meso- and micro-level accounts have advanced explanatory models of why discrimination occurs at all. The crucial influence of the organizational climate on discrimination constitutes a well-known example at the meso level. Thus, it has been shown that the organizational climate is the single-most important driving factor for sexual harassment to occur (National Academies of Sciences, Engineering, and Medicine, 2018; Willness, Steel, and Lee, 2007 ). On the other hand, micro-level accounts build upon psychology and social psychology to expose the individual-level dimensions of discrimination. Different psychological models exist concerning how prejudice and stereotypes are linked to discriminating actions, such as when implicit attitudes shape the behavior toward others defined by their social group identity ( Greenwald and Krieger, 2006 ). The contributions of this edited collection in their entirety cover the macro-, meso- and micro-level.

Discrimination and Diversity through a National and Organizational Lens

While considerable advances have been achieved to untangle the hidden dynamics of discrimination in organizations, the collection of research articles presented here makes two specific contributions to the existing literature. First, they contribute research on aggregated and individual identity-related experiences of workplace misconduct at the research workplace. The contributions focus on different socio-demographic groups of people and consider research organizations that operate in different national contexts. The contributions reflect the influence of the systemic framework of academia.

Second, the relationship between diversity and discrimination in the context of the academic workplace is especially interesting in relation to one of the most decisive transformations of the academic environment over recent decades, namely the simultaneous intensification of work and diminishing resources/funding. The introduction of a new managerialism and regimes of accountability has obliged academics to do more with fewer resources and less time. As incipient research shows, the effects in terms of discrimination are particularly felt by minorities and those collectives that are already in more precarious and disadvantaged situations. Although research on the “neoliberal university” is abundant, there is a clear lack of more focused approaches to understand its implications for discrimination as well as diversity in work teams.

The contributions gathered in this edited collection are all situated in different national and organizational contexts, from the USA, France, Germany and Nigeria to Vietnam, and the conditions of academic workplaces in non-university and university contexts as well as public or private research organizations at different hierarchical levels and in different disciplines are examined. These national and organizational contextual conditions must be taken into account when considering the transferability of the results to other contexts, as explained below.

The Relevance of National Context

Discrimination is a persistent phenomenon throughout time, but levels of discrimination considerably differ across countries. As Quillian et al. (2019) show in their meta-analysis of job application field experiments, the strength of racial discrimination can considerably vary across the nine countries included in their study. White job applicants receive up to 65–100 percent more callbacks in France and Sweden than non-white minorities. Discrimination of job applications is weaker in Germany, the United States and Norway, where they receive on average 20–40 percent fewer callbacks. Similar findings are available from the large GEMM study carried out in several EU countries, particularly focusing on hiring discrimination based on ethnic background. Discrimination ratios were the highest in Britain – where ethnic minorities need to send out 54 percent more applications to achieve the same callback rate as the majority group – and the lowest in Germany, where minority applicants need to send out 15 percent more applications ( Lancee, 2021 ; Di Stasio and Lancee, 2020 ). Examining religion, the study also finds that in the Netherlands, Norway and the UK, Muslims are “more than 10 percentage points less likely than majority members to receive a callback” ( Di Stasio et al., 2021 , p. 1316).

Comparative studies examining the effects of perceived discrimination equally attest to country-level differences concerning both gender and race. As Triana et al. (2019) show, differences in outcomes in terms of the psychological and physical health of gender discrimination at work can be linked back to differences in national labor policies and gender-egalitarian cultural practices between countries. To the degree that institutional frameworks such as labor market policies, legal regulations or cultural norms differ between countries, levels of discrimination will vary accordingly. Along the same lines, Quillian et al. (2019) see the comparatively high levels of hiring discrimination in France and Sweden as resulting from unconstrained employers’ discretion that is neither monitored nor held in check by discrimination lawsuits such as in the US.

The role of national context factors for diversity are equally not fully understood. Although Joshi and Roh (2007) highlight national culture as one “distal omnibus” element affecting diversity outcomes, results are not particularly abundant. Early insights suggest that important dimensions of teamwork such as hierarchical versus more horizontal peer-based control structures vary across cultures and can invert the outcomes of diversity. Thus, van der Vegt, Van de Vliert, and Huang (2005) show that in cultures where power is more centralized, tenure and functional diversity are negatively associated with innovative climates, whereas in low power distance cultures diversity is positively associated with innovative climates.

As the GLOBE study across 62 societies has amply documented, cultural differences not only exist in terms of “power distance” but also regarding other important features affecting diversity climate in work groups such as risk avoidance, performance orientation, gender egalitarianism, or levels of collectivist versus more individualized values ( House et al., 2004 ). For certain areas of diversity research such as the under-representation of women on corporate boards, cultural differences in terms of gender egalitarianism and/or traditional gender roles have been shown to play a decisive role ( Lewellyn and Muller-Kahle, 2020 ). However, since the primary interest of diversity research lies at the work group level, explorations of macro-scale patterns that are so common for discrimination research are rare. Instead, national differences are frequently operationalized in terms of the diversity of cultural values that individual team members bring to the work group ( Bodla et al., 2018 ).

An important additional perspective for understanding the national context of discrimination concerns a situational perspective. Apart from institutional differences in terms of labor market legislation between countries, discrimination has also been linked to historical legacies of oppression such as slavery. Apart from historical legacies, situational accounts frequently also explain discrimination with reference to current economic and demographic conditions or political events ( Quillian and Midtbøen, 2021 ). Right-wing politics stigmatizing certain ethnic or religious groups – for example in relation to terrorist attacks – can fuel discrimination. In situations of crisis such as the recent Covid-19 outbreak, discrimination can be aggravated. As reported by Pew Research Center (2020) , 40 percent of black and Asian Americans indicate an increase in discriminating behavior toward them by others since the start of the pandemic. The Covid-19 pandemic has also clearly shown that under conditions of stress or crisis, minorities and marginalized groups will be even further disadvantaged compared to majority social groups ( Kantamneni, 2020 ). However, while the effects of a public health crisis on discrimination have been extensively explored, this is not necessarily true for the effects of economic crises or recessions. Among the few studies directly examining the link between worsening economic conditions and discrimination, Kingston, McGinnity, and O’Connell (2015) show that non-Irish nationals experienced higher rates of work-based discrimination during the recession in 2010 compared to time of economic growth in 2004. Implicitly, there seems to be an understanding that “under conditions of threat (e.g., recessions, downsizing)” or insecurity, organizations and individuals fall back into “a limited set of well-learned and habituated behavioral scripts” ( Gelfand et al., 2005 , p. 93) to the disadvantage of already-marginalized and excluded social groups.

Overall, it remains unclear how these wider economic situational factors play out in terms of discrimination experiences and possibilities of fostering diverse teams. This holds especially in relation to the transformation of academic life in general. Driven by wider transformations and restructuring of the post-war European welfare states, academic work has experienced dramatic shifts over recent decades. Scientific autonomy has increasingly been replaced with an orientation toward performance measures, a focus on excellence and competition, entrepreneurship, or the emphasis on cost efficiency ( Herschberg and Benschop, 2019 ). How these recent developments play out in terms of discrimination experiences within academic organizations remains to be more fully understood. The work conducted here at the meso and micro level provides promising avenues for discrimination research. As we will argue in the next section, organizational culture and climate are not only influenced by wider national settings but they also modulate and refract some of these broader national trends with important implications for reducing discrimination and fostering team effectiveness. As the organizational level is the primary work environment in which people interact, it is one of the most important arenas to control and diminish discrimination.

The Relevance of the Organization

Organizational factors play an important role for discrimination rates and experiences in work settings. Organizational policies have also been identified as a crucial element for taking advantage of diversity. Formal and informal structures, organizational culture and climate, leadership or human resources, or workplace composition may all contribute to or attenuate discrimination ( Gelfand et al., 2005 ). For example, transparent and formal evaluation criteria at the organizational level – for promotion or recruitment – can reduce discrimination as decision-making is accountable to objective criteria. Similar, holding managers socially accountable for performance ratings is one of three promising and effective strategies in terms of increasing workforce diversity and diminishing discrimination in companies ( Dobbin and Kalev, 2016 ). In addition to encouraging social accountability, two further factors mentioned by Dobbin and Kalev (2016) to reduce discrimination effectively concern the engagement of managers in solving problems and the increase of contact among people from different groups. Both factors can be decisively steered through organizational policies.

Organizational climate – to mention another important organization-level factor – is a key driver of harassment ( Pryor, Giedd, and Williams, 1995 ). Incidents of sexual and other harassment are more likely to occur in working environments where harassment is “tolerated” by a leadership that fails to act on complaints, does not sanction perpetrators or protect complainants from retaliation (National Academies of Sciences, Engineering, and Medicine 2018). This is especially true in settings where men are overrepresented among staff and at the leadership level. For example, a recent study on sexual harassment of undergraduate female physicists in the US – with women being under-represented in physics – revealed that three-quarters of respondents had experienced at least one type of sexual harassment ( Aycock et al., 2019 ). Organizational-level factors such as the overall gender ratios or the wider work climate are therefore considered key elements that can inhibit or encourage discrimination.

Examining organizational context factors of discrimination more broadly, most evidence from the US is largely based upon plaintiff accounts of discrimination lawsuits. Thus, Hirsh and colleagues ( Hirsh, 2014 ; Hirsh and Kornrich, 2008 ) show – for example – how several factors such as the previous vulnerable economic or social status, the workplace culture and the workplace composition affect the perception of discrimination by employees. Similar, Bobbitt-Zeher (2011) exposes how organizational practices and policies combine with workplace composition and gender stereotyping to produce workplace gender discrimination in quite predictable ways. As mentioned, gendered norms of behavior, dress code, or sexualized talk in often male-dominated management and leadership positions create an organizational culture in which discrimination can flourish.

Among the few studies to explore the organizational context via an extensive survey is Stainback, Ratliff, and Roscigno (2011) whose study is based upon a sample of 2,555 respondents to the US National Study of the Changing Workforce in 2002. Corroborating the insights of Hirsh (2014) , and Bobbitt-Zeher (2011) , the results show that the experience of discrimination is reduced for both genders when they are part of the numerical majority in their organization and where a supportive workplace culture is in place. In their survey among 176 employees in the United States, Kartolo and Kwantes (2019) show that behavioral norms related to organizational culture modulates perceived discrimination.

While the majority of research on discrimination operates with a concept of behavior that disadvantages or harms people, diversity research foregrounds measures that foster a climate for inclusion to take full advantage of diverse assets within work groups. Indeed, promoting an organizational climate for inclusion is not only beneficial at the individual level (e.g., higher job satisfaction, better physical and psychological health) but also improves group-level outcomes such as overall team or organizational performance. As Brooke and Tyler (2011) succinctly state,

[…] by creating an environment in which all employees know they are valued and feel safe from discrimination, every employee can feel comfortable as a valued member of the organization (pp. 745–746).

Along these lines, research from Google regarding the perfect team has underlined previous insights from small group research on the importance of psychological safety for diverse teams ( Duhigg, 2016 ; Edmondson and Lei, 2014 ). Risk-taking and making errors – elements that are crucial for innovation – are only possible to the degree that employees feel safe in their team and the wider work environment. Thus, Reinwald, Huettermann, and Bruch (2019) argue – based on a sample of 82 German companies – that diversity climate has positive effects for firm performance, especially where there is a relatively high convergence among employees in their climate perceptions. Similar findings are available from research on military working groups, showing that diversity climate is consistently and positively related to work group performance and that this relationship is mediated by discrimination ( Boehm et al., 2014 ). Already in earlier work, Nishii (2012) has argued for the benefits of a “climate for inclusion” that reduces interpersonal bias and diversity conflict (see also Richard, 2000 ).

While research has established the importance of organizational climate and culture for discrimination and diversity, it is somewhat surprising that one of the major transformations over the recent decades within academic organizations has received relatively scant attention. None of the aforementioned studies thus far takes into account how academic organizations at large are affected by or confronted with decreasing public funding while having to grope with a heightened sense of accountability. The introduction of New Public Management principles aiming to reduce and streamline a supposedly oversized and inefficient public sector has certainly affected public universities and research institutions over recent decades ( Hood, 1991 ; Newman, 2005 ). A new managerialism tied to the introduction of Total Quality Management principles ( Aspinwall and Owlia, 1997 ) – for example – as well as a marketization of the public sector have undermined the autonomy and independence of the academy and provoked considerable resistance among scholars. However, although the discriminatory effects of the so-called neoliberal working conditions in academic contexts is a burgeoning field of research ( Pereira, 2016 ; Berg, Huijbens, and Larsen, 2016 ; Heath and Burdon, 2013 ; Craig, Amernic, and Tourish, 2014 ), there is clearly a dearth of studies addressing how the wider organizational culture associated with competitiveness, performance demands, or audit culture affects the perception of discrimination. As some studies suggest, especially vulnerable minorities are likely to be disproportionately affected by these more demanding, neoliberal work environments ( Anderson, Gatwiri, and Townsend-Cross, 2019 ; Cech and Rothwell, 2020 ).

Risk Factors of Discrimination in Research Organizations

From the perspective of a researcher in the European Union, it should be noted that there is hardly any other sector in which such highly-qualified personnel work under comparably insecure working conditions as in academia. As editors of this collection, we do not believe that scientific and non-scientific employees in research organizations experience discrimination or workplace misconduct more frequently than in other sectors (for a discussion for sector differences in bullying, see Keashly, 2021 ). However, depending on the contextual conditions of the academic sector, very specific patterns of structural discrimination emerge.

From a governance perspective, discrimination can take place especially in situations where effective structures are lacking that may constrain decision-makers to minimize the influence of bias on their decisions ( Williams, 2017 ). This refers to accountability structures as well as checks and balances in decision-making processes and procedures that aim to reduce or dissolve one-sided dependencies between the individual actors in the research system (e.g., staff councils, PhD schools, supervisory committees, equal opportunities officers, representatives for the severely disabled, transparent and binding promotion criteria, etc.). Where such structures are lacking, a high degree of variance in working cultures and leadership styles in the individual teams is possible, with both positive and negative consequences.

The Equal Employment Opportunity Commission (EEOC) – a US federal agency tasked with ensuring the implementation of the applicable anti-discrimination legislation in the labor market – has formulated concrete organizational risk factors for workplace harassment, which can also be applied to research organizations and academia ( Feldblum and Lipnic, 2016 ). With their understanding of the term harassment, the authors focus on intentional forms of discrimination, as opposed to unreflective discrimination due to cognitive bias or institutionalized structures (such as not counting care periods in the evaluation of performance). In our view, the risk factors named in Table 1 and explained by indicators and anecdotal examples from academia can also be largely applied to systemic discrimination. Table 1 can thus be understood as the summary of the above elaborations on the importance of national and organizational contextual factors.

Chart of Risk Factors for Harassment and Responsive Strategies (for an extended version, see US Equal Employment Opportunity Commission, 2021).

The anecdotal examples in Table 1 convey the notion that it seems inappropriate to place academia under the general suspicion that experiences of discrimination and discriminatory behavior as well as the negation of diversity are more widespread here than in other workplaces. The heterogeneity of the workforce and the prevailing workforce norms vary between different national, regional, and disciplinary contexts. Furthermore, a vertical and horizontal gender segregation as well as a status- and organization-politically elevated position of leadership personnel are not peculiarities of research organizations. However, discrimination processes in academia can be framed in particular by the following distinct characteristics of the research and higher education system:

the “customer service” provided by scientific staff – that is, teaching students – can certainly be considered an important additional stress factor, which is only present in comparable form in other teaching professions;

the important role of international mobility for scientific career development, which is explicitly promoted by national and supranational organizations such as the EU and structurally reflected in cultural and linguistic differences in the workforce;

the shared governance principle of academia (Keashly, 2021), within which the faculty makes the crucial decisions on research strategy and personnel policy. Other staff have a subordinate role. Within shared governance, other university groups are often represented alongside the faculty, and decision-making power is distributed pyramid-like according to seniority: while all of the voices of the few chair holders as “high-value employees” are often heard, early career researchers, non-tenured researchers, administrative staff and the many students are often not represented or they are only represented by a few representatives.

The principle of senior shared governance or “peer principle” is based on a collegial appreciation of the peer’s respective sphere of influence on constructiveness and cooperativeness. For academic leadership staff, shared governance is essentially a peer evaluation system in which each participant is just as powerful as any other. In cases of conflict, this system of mutual tolerance can reach its limits ( Keashly, 2021 ); for example, when the prevailing structures in the academic workplace are questioned, or when a colleague should be confronted due to a biased decision or their misconduct toward groups of people who are not involved in senior shared governance.

In order to make HR processes more professional and rational, the professionalized and clearly more sovereign university administrations in relation to the faculty ( Gerber, 2014 ) today have a variety of different tools at their disposal. As van den Brink and Benschop (2012) argue, these tools like promotion guidelines, gender equality plans, trainings, or participatory decision-making too rarely aim at structural change and take little account of disciplinary specificities (e.g., the pool of female talent strongly differs between computer science and medicine). In particular, the authors highlight that practices aimed at reducing discrimination are closely intertwined with the contextual conditions that gave rise to the discrimination to be combated in the first place. For example, the gender equality officer’s say and the rules set for the appointment of a new chair are sometimes undermined by the preferences and informal power resources of the academic management, whereby ultimately the candidate who had been preferred by the institute’s management from the beginning prevails in most cases. Accountability structures for strengthening diversity usually lack the binding force and sanctioning power to have an immediate effect (ibidem).

At the European level, we observe a growing awareness of the lack of effectiveness of the current gender equality policies and measures in academia, accompanied by the will to strengthen its effectiveness. A particular expression of this attitude is that since 2021 gender equality plans have been declared a mandatory requirement to apply for project funding within the framework of the most important European research framework program, “Horizon European” (European Commission, 2020). Furthermore, within the framework of its Gender Equality Strategy 2020–2025, the European Commission attaches importance to an intersectional approach in which discrimination is not restricted to gender but is thought of comprehensively.

Overview of Chapters

The peer principle as an element of research governance essentially ensures the scientific quality of research. Who else should evaluate the excellence of a research project, research design and researcher, if not their peers? However, as explained above, the peer principle does not guarantee modern and bias-free personnel management as required by a number of state equal opportunity acts.

It is research policy and administrative as well as scientific research managers who are decisively entrusted with the standardization and quality assurance of personnel management in the research system and who thus make an essential contribution to ensuring optimal working conditions for academic mid-level and non-scientific staff as well as equal opportunities when filling professorships. With the studies collected in this anthology, we hope to contribute to the informed action of these central actors in research policy to enable researchers and research teams to operate in optimal conditions. The articles can be roughly divided into two categories according to the guiding questions of this edited collection: macro studies surveying the extent of discrimination and harassment in research organizations and micro studies exploring the influence of the specific cultural contextual conditions of the academic workplace on experiences of discrimination and harassment related to the diversity of the workforce.

About the Extent of Discrimination in Research Organizations

Striebing’s “Max Planck studies” belong to the first category of macro analyses. These are three contributions that resulted from a research project commissioned and funded by the Max Planck Society in Germany on the work culture in its institutes and facilities and in particular on the experiences of bullying and sexual discrimination. The project was carried out in 2018 and 2019 and included a series of qualitative interviews and a full survey of the more than 23,600 scientific and non-scientific employees of the Max Planck Society, which is one of the world’s largest and most comprehensive institutions for basic research.

In his first contribution, Striebing explains how the evaluation of the group climate and the leader varies according to the socio-demographic characteristics gender, nationality and responsibility for childcare of the Max Planck researchers. He examines the intersectionality, in terms of interaction effects, of these characteristics, and also considers the context of the respondents’ hierarchical position. Striebing proceeds in a similar way in his second contribution. In addition to the researchers, the non-scientific employees of the Max Planck Society are also examined. The question is pursued concerning how the socio-demographic characteristics of the employees as well as the contextual conditions of hierarchical position, scientific discipline and administrative area affect the extent of bullying experiences. In the third contribution, Striebing examines whether men and women in the academic workplace have a different understanding of bullying and sexual harassment and discrimination. The contribution explores patterns of gender-related differences in the self-reporting of acts of workplace misconduct and self-labeling as having been bullied or experienced sexual discrimination and/or harassment.

Pantelmann and Wälty offer a comprehensive insight into the prevalence of sexual harassment among students. They present data from a survey conducted at a German university and critically reflect the role of the university and the work culture in academia in preventing and managing experiences of sexual harassment on campus. The results presented by the authors come from the “Perspectives and Discourses on Sexual Harassment in International Higher Education Contexts” project in which eight research teams from very different international higher education contexts cooperated.

Sheridan, Dimond, Klumpyan, Daniels, Bernard-Donals, Kutz, and Wendt also conducted a so-called campus study, examining the prevalence of hostile and intimidating behavior at the University of Wisconsin-Madison in the US and its variance by gender among persons of color, LGBTQ persons and persons with disability at two different measurement points. More importantly, in their article the authors describe the policy package enacted by the university for prevention and conflict resolution and discuss its effectiveness using their longitudinal data as well as survey data from training interventions. The authors thus present a very rare evaluation study in the context of discrimination, which is highly relevant for theory and practice alike.

Nguyen, Tran, and Tran contribute a systemic macro analysis of a lower-investment research and innovation system and a different culture. They analyze data from 756 researchers in the Vietnam Academy of Social Sciences, examining differences in the scientific achievements of male and female researchers and investigating the factors influencing them.

Cultural Context Conditions of Academia for Diversity and Discrimination

The discourse in research organizations has a particular influence on how diverse teams and cases of discrimination are dealt with, that is, what is said, how it is said and what can be said. This discourse is the result of the respective organizational and team culture and it decisively determines which experiences are perceived and recognized as discrimination in the organization.

In an experimental survey study, Kmec, O’Connor, and Hoffman presented a representative sample of the US population with a vignette describing an incident of sexual harassment between a department director and one of his team members, asking respondents to rate whether it was inappropriate behavior, sexual harassment, or neither. The authors are interested in the question of whether the respondents’ value orientations – in terms of gender essentialism, gender egalitarianism and their belief in meritocracy – significantly influence sensitivity to the perception of sexual harassment.

Of the papers in this edited collection, Vandevelde-Rougale and Guerrero Morales most directly address the implications of the extension of managerialism and New Public Management to discrimination in research organizations. The authors examine managerial discourse, by which they mean a utilitarian, cost-benefit-oriented way of interpreting and organizing the affairs and processes of research teams. Through multiple case studies from Ireland and Chile, they explore what the focus on the pragmatic exploitation of diversity brings to bear on individuals who experience workplace bullying and discrimination, as well as what the managerial approach to conflict solutions can contribute to ensuring a safe and discrimination-free work culture.

The third discourse-related study in this edited collection is provided by Steuer-Dankert, who deals with diversity belief in a complex research organization. Diversity belief is understood as a working group’s belief in its own diversity and the positive benefits of diversity. Steuer-Dankert not only contributes the most comprehensive reflection on diversity management in research organizations among the contributions of this collection, but she also provides answers to another interesting aspect. Previous studies often examine diversity and discrimination in teams under the assumption of a relative constancy of team structures and members, but in a modern innovation system research often takes place in project-wise institutionalized and theme-oriented network structures such as the German Cluster of Excellence examined by Steuer-Dankert. The temporary network forms a further governance level horizontal to the classic university organization and features independent team interactions and ultimately also a specific organizational culture.

While the aforementioned studies describe individual specific aspects of the organizational culture of research organizations, Gewinner reconstructs the experiences of discrimination of a specific group of people based on biographical interviews. Using Russian-speaking female scholars in Germany, she develops a comprehensive and intersectional theory on the vulnerability of foreign researchers to experiences of discrimination and workplace misconduct.

Since a major aim of this edited collection is not only to understand and describe discrimination in research organizations but also to make a small contribution to reducing discrimination, we conclude by formulating a number of implications for practice. In the concluding chapter, we set out several basic features and requirements for an effective system for preventing and managing discrimination in research organizations and summarize what we consider to be the main lessons learned from this edited collection in a simple catalogue of options for action.

About Our Intersectional Approach

The intersectionality approach assumes that an individual belongs to “multiple categories of difference” defined by socially-constructed categories such as gender, age, or ethnicity that result in a specific set of opportunities and oppressions for each individual stemming from their “blended social identity” (Dennissen et al., 2020; Silva, 2020; Ghavami et al., 2016 ; Crenshaw, 1991). These intersections of identity and discrimination result in individual experiences of discrimination based on different group memberships. Accordingly, the concrete discrimination experiences of black women – for example – differ from those of black men and white women. An intersectional approach considers the addition of experiences of discrimination, but furthermore also considers interaction effects (Bowleg, 2008). As a result of the intersectional analysis, it may emerge – for example – that black women experience discrimination less frequently than black men or white women, although they experience discrimination due to their status as women and black people. The task of intersectional research is to identify the structural and situational dynamics of discrimination processes and their specific contextual conditions.

The contributions of the edited collection and their framing explicitly follow an intersectional approach. This means that the single contributions not only discuss differences between persons of different genders but also pursue taking into account intersections between identity categories (and the different systems of oppressions represented by them) in the analysis. We apply a broad understanding of intersectionality. Which categorizations are ultimately taken up in the contributions to the edited collection was open and depended on the authors’ research foci and available data. In principle, it is possible to analyze the manifold interactions of gender with racial or ethnic origin, religion or belief, disability, sexual orientation and other categorizations, which can form the starting point for systemic discrimination.

Nevertheless, an intersectional analysis in the strict sense was not always possible. Especially in quantitative studies, large numbers of cases are necessary to make statements with high statistical power and thus not only identify very strong statistical effects. In cases with low statistical power, it was not the interactions of, for example, gender and age that were analyzed, but rather the simple effects of gender and age. In addition, several authors of the edited collection adopt an intersectional perspective when discussing the generalizability of their results. For example, Kmec et al. (in this collection) discuss whether a connection between merit thinking and sexual discrimination could also be proven if the discrimination was not positioned in a heterosexual setting between an old white supervisor and a young white female researcher.

Funding Note

The present contribution is not related to externally funded research.

The text of Article 179 of the Treaty on the Functioning of the European Union (2012) paraphrased here is: “The Union shall have the objective of strengthening its scientific and technological bases by achieving a European research area in which researchers, scientific knowledge and technology circulate freely, […].”

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Introduction: The Case for Discrimination Research

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• First Online: 09 April 2021

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• Rosita Fibbi 4 ,
• Arnfinn H. Midtbøen 5 &
• Patrick Simon 6  

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Increasing migration-related diversity in Europe has fostered dramatic changes since the 1950s, among them the rise of striking ethno-racial inequalities in employment, housing, health, and a range of other social domains. These ethno-racial disadvantages can be understood as evidence of widespread discrimination; however, scholarly debates reflect striking differences in the conceptualization and measurement of discrimination in the social sciences. Indeed, what discrimination is, as well as how and why it operates, are differently understood and studied by the various scholarships and scientific fields. It is the ambition of this book to summarize how we frame, study, theorize, and aim at combatting ethno-racial discrimination in Europe.

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European societies are more ethnically diverse than ever. The increasing migration-related diversity has fostered dramatic changes since the 1950s, among them the rise of striking ethno-racial inequalities in employment, housing, health, and a range of other social domains. The sources of these enduring inequalities have been a subject of controversy for decades. To some scholars, ethno-racial gaps in such outcomes are seen as transitional bumps in the road toward integration, while others view structural racism, ethnic hostility, and subtle forms of outgroup-bias as fundamental causes of persistent ethno-racial inequalities. These ethno-racial disadvantages can be understood as evidence of widespread discrimination; however, scholarly debates reflect striking differences in the conceptualization and measurement of discrimination in the social sciences.

What discrimination is, as well as how and why it operates, are differently understood and studied by the various scholarships and scientific fields. A large body of research has been undertaken over the previous three decades, using a variety of methods – qualitative, quantitative, and experimental. These research efforts have improved our knowledge of the dynamics of discrimination in Europe and beyond. It is the ambition of this book to summarize how we frame, study, theorize, and aim at combatting ethno-racial discrimination in Europe.

1.1 Post-War Immigration and the Ethno-racial Diversity Turn

Even though ethnic and racial diversity has existed to some extent in Europe (through the slave trade, transnational merchants, and colonial troops), the scope of migration-related diversity reached an unprecedented level in the period following World War II. This period coincides with broader processes of decolonization and the beginning of mass migration from non-European countries, be it from former colonies to the former metropoles (from the Caribbean or India and Pakistan to the UK; South-East Asia, North Africa or Sub-Saharan Africa to France) or in the context of labor migration without prior colonial ties (from Turkey to Germany or the Netherlands; Morocco to Belgium or the Netherlands, etc.).

The ethnic and racial diversity in large demographic figures began in the 1960s (Van Mol and de Valk 2016 ). At this time, most labor migrants were coming from other European countries, but figures of non-European migration were beginning to rise: in 1975, 8% of the population in France and the UK had a migration background, half of which originated from a non-European country. By contrast, in 2014, 9.2% of the population of the EU28 had a migration background from outside of Europe (either foreign born or native-born from foreign-born parent(s)), and this share reached almost 16% in Sweden; 14% in the Netherlands, France, and the UK; and between 10 and 13% in Germany, Belgium, and Austria. The intensification of migration, especially from Asia and Africa, has heightened the visibility of ethno-racial diversity in large European metropolises. Almost 50% of inhabitants in Amsterdam and Rotterdam have a “nonwestern allochthon ” background (2014), 40% of Londoners are black or ethnic minorities (2011), while 30% of Berliners (2013) and 43% of Parisians (metropolitan area; 2009) have a migration background. The major facts of this demographic evolution are not only that diversity has reached a point of “super-diversity” (see Vertovec 2007 ; Crul 2016 ) in size and origins, but also that descendants of immigrants (i.e., the second generation) today make up a significant demographic group in most European countries, with the exception of Southern Europe where immigration first boomed in the 2000s.

The coming of age of the second generation has challenged the capacity of different models of integration to fulfill promises of equality, while the socio-cultural cohesion of European societies is changing and has to be revised to include ethnic and racial diversity. Native-born descendants of immigrants are socialized in the country of their parents’ migration and, in most European countries, share the full citizenship of the country where they live and, consequently, the rights attached to it. However, an increasing number of studies show that even the second generation faces disadvantages in education, employment, and housing that cannot be explained by their lack of skills or social capital (Heath and Cheung 2007 ). The transmission of penalties from one generation to the other – and in some cases an even higher level of penalty for the second generation than for the first – cannot be explained solely by the deficiencies in human, social, and cultural capital, as could have been the case for low-skilled labor migrants arriving in the 1960s and 1970s. Indeed, the persistence of ethno-racial disadvantages among citizens who do not differ from others except for their ethnic background, their skin color, or their religious beliefs is a testament to the fact that equality for all is an ambition not yet achieved.

Citizenship status may represent a basis for differential treatment. Undoubtedly, citizenship status is generally considered a legitimate basis for differential treatment, which is therefore not acknowledged as discrimination. Indeed, in many European countries, the divide between nationals and European Union (EU) citizens lost its bearing with the extension of social rights to EU citizens (Koopmans et al. 2012 ). Yet, in other countries, and for non-EU citizens, foreign citizenship status creates barriers to access to social subsidies, health care, specific professions, and pensions or exposure to differential treatment in criminal justice. In most countries, voting rights are conditional to citizenship, and the movement to expand the polity to non-citizens is uneven, at least for elections of representatives at the national parliaments. Notably, in countries with restrictive access to naturalization, citizenship status may provide an effective basis for unequal treatment (Hainmueller and Hangartner 2013 ). The issue of discrimination among nationals, therefore, should not overshadow the enduring citizenship-based inequalities.

The gap between ethnic diversity among the population and scarcity of the representation of this diversity in the economic, political, and cultural elites demonstrate that there are obstacles to minorities entering these positions. This picture varies across countries and social domains. The UK, Belgium, or the Netherlands display a higher proportion of elected politicians with a migration background than France or Germany (Alba and Foner 2015 ). Some would argue that it is only a matter of time before newcomers will take their rank in the queue and access the close ring of power in one or two generations. Others conclude that there is a glass ceiling for ethno-racial minorities, which will prove as efficient as that for women to prevent them from making their way to the top. The exception that proves the rule can be found in sports, where athletes with minority backgrounds are often well represented in high-level competitions. The question is how to narrow the gap in other domains of social life, and what this gap tells us about the structures of inequalities in European societies.

1.2 Talking About Discrimination in Europe

Discrimination is as old as human society. However, the use of the concept in academic research and policy debates in Europe is fairly recent. In the case of differential treatment of ethnic and racial minorities, the concept was typically related to blatant forms of racism and antisemitism, while the more subtle forms of stigmatization, subordination, and exclusion for a long time did not receive much attention as forms of “everyday racism” (Essed 1991 ). The turn from explicit racism to more subtle forms of selection and preference based on ethnicity and race paved the way to current research on discrimination. In European societies, where formal equality is a fundamental principle protected by law, discrimination is rarely observed directly. Contrary to overt racism, which is explicit and easily identified, discrimination is typically a hidden part of decisions, selection processes, and choices that are not explicitly based on ethnic or racial characteristics, even though they produce unfair biases. Discrimination does not have to be intentional and it is often not even a conscious part of human action and interaction. While it is clear that discrimination exists, this form of differential treatment is hard to make visible. The major task of research in the field is thus to provide evidence of the processes and magnitude of discrimination. Beyond the variety of approaches in the different disciplines, however, discrimination researchers tend to agree on the starting point: stereotypes and prejudices are nurturing negative perceptions, more or less explicit, of individuals or groups through processes of ethnicization or racialization, which in turn create biases in decision-making processes and serve as barriers to opportunities for these individuals or groups.

Although the concepts of inequality, discrimination, and racism are sometimes used interchangeably, the concept of discrimination entails specificities in terms of social processes, power relations, and legal frameworks that have opened new perspectives to understand ethnic and racial inequalities. The genealogy of the concept and its diffusion in scientific publications still has to be studied thoroughly, and we searched in major journals to identify broad historical sequences across national contexts. Until the 1980s, the use of the concept of discrimination was not widespread in the media, public opinion, science, or policies. In scientific publications, the dissemination of the concept was already well advanced in the US at the beginning of the twentieth century in the aftermath of the abolition of slavery to describe interracial relations. In Europe, there is a sharp distinction between the UK and continental Europe in this regard. The development of studies referring explicitly to discrimination in the UK has a clear link to the post-colonial migration after World War II and the foundation of ethnic and racial studies in the 1960s. However, the references to discrimination remained quite limited in the scientific literature until the 1990s – even in specialized journals such as Ethnic and Racial Studies , New Community and its follower Journal for Ethnic and Migration Studies , and more recently Ethnicities  – when the number of articles containing the term discrimination in their title or keywords increased significantly. In French-speaking journals, references to discrimination were restricted to a small number of feminist journals in the 1970s and became popular in the 1990s and 2000s in mainstream social science journals. The same held true in Germany, with a slight delay in the middle of the 2000s. Since the 2000s, the scientific publications on discrimination have reached new peaks in most European countries.

The year 2000 stands as a turning point in the development of research and public interest in discrimination in continental Europe. This date coincides with the legal recognition of discrimination by the parliament of the EU through a directive “implementing the principle of equal treatment between persons irrespective of racial or ethnic origin,” more commonly called the “Race Equality Directive.” This directive put ethnic and racial discrimination on the political agenda of EU countries. This political decision contributed to changing the legal framework of EU countries, which incorporated non-discrimination as a major reference and transposed most of the terms of the Race Equality Directive into their national legislation. The implementation of the directive was also a milestone in the advent of the awareness of discrimination in Europe. In order to think in terms of discrimination, there should be a principle of equal treatment applied to everyone, regardless of their ethnicity or race. This principle of equal treatment is not new, but it has remained quite formal for a long time. The Race Equality Directive represented a turning point toward a more effective and proactive approach to achieve equality and accrued sensitivity to counter discrimination wherever it takes place.

The first step to mobilize against discrimination is to launch awareness-raising campaigns to create a new consciousness of the existence of ethno-racial disadvantages. The denial of discrimination is indeed a paradoxical consequence of the extension of formal equality in post-war democratic regimes. Since racism is morally condemned and legally prohibited, it is expected that discrimination should not occur and, thus, that racism is incidental. Incidentally, an opinion survey conducted in 2000 for the European Union Monitoring Center on Racism and Xenophobia (which was replaced in 2003 by the Fundamental Rights Agency [FRA]), showed that only 31% of respondents in the EU15 at the time agreed that discrimination should be outlawed. However, the second Eurobarometer explicitly dedicated to studying discrimination in 2007 found that ethnic discrimination was perceived as the most widespread (very or fairly) type of discrimination by 64% of EU citizens (European Commission 2007 ). Almost 10 years later, in 2015, the answers were similar for ethnic discrimination but had increased for all other grounds except gender. Yet, there are large discrepancies between countries, with the Netherlands, Sweden, and France showing the highest levels of consciousness of ethnic discrimination (84%, 84%, and 82%, respectively), whereas awareness is much lower in Poland (31%) and Latvia (32%). In Western Europe, Germany (60%) and Austria (58%) stand out with relatively lower marks (European Commission 2015 ).

These Eurobarometer surveys provide useful information about the knowledge of discrimination and the attitudes of Europeans toward policies against it. However, they focus on the representation of different types of discrimination rather than the personal experience of minority members. To gather statistics on the experience of discrimination is difficult for two reasons: (1) minorities are poorly represented in surveys with relatively small samples in the general population and (2) questions about experiences of discrimination are rarely asked in non-specific surveys. Thanks to the growing interest in discrimination, more surveys are providing direct and indirect variables that are useful in studying the personal experiences of ethno-racial disadvantage.

The European Social Survey, for example, has introduced a question on perceived group discrimination (which is not exactly a personal self-reported experience of discrimination, see Chap. 4 ). In 2007 and 2015, the FRA conducted a specialized survey on discrimination in the 28 EU countries, the Minorities and Discrimination (EU-MIDIS) survey, to fill the gap in the knowledge of the experience of discrimination of ethnic and racial minorities. The information collected is wide ranging; however, only two minority groups were surveyed in each EU country, and the survey is not representative of the population.

Of course, European-wide surveys are not the main statistical sources on discrimination. Administrative statistics, censuses, and social surveys at the national and local levels in numerous countries bring new knowledge of discrimination, either with direct measures when this is the main topic of data collection or more indirectly when they provide information on gaps in employment or education faced by disadvantaged groups. The key point is to be able to identify the relevant population category in relation to discrimination, as we know that ethno-racial groups do not experience discrimination to the same extent. Analyses of immigrants or the second generation as a whole might miss the significant differences between – broadly speaking – European and non-European origins. Or, to put it in a different way, between white and non-white or “visible” minorities. Countries where groups with a European background make up most of the migration-related diversity typically show low levels of discrimination, while countries with high proportions of groups with non-European backgrounds, especially Africans (North and Sub-Saharan), Caribbean people, and South Asians, record dramatic levels of discrimination.

1.3 Who Is Discriminated Against? The Problem with Statistics on Ethnicity and Race

Collecting data on discrimination raises the problem of the identification of minority groups. Migration-related diversity has been designed from the beginning of mass migration based on place of birth of the individuals (foreign born) or their citizenship (foreigners). In countries where citizenship acquisition is limited, citizenship or nationality draws the boundary between “us” and “the others” over generations. This is not the case in countries with more open citizenship regimes where native-born children of immigrants acquire by law the nationality of their country of residence and thus cannot be identified by these variables. If most European countries collect data on foreigners and immigrants, a limited number identify the second generation (i.e., the children of immigrants born in the country of immigration). The question is whether the categories of immigrants and the second generation really reflect the population groups exposed to ethno-racial discrimination. As the grounds of discrimination make clear, nationality or country of birth is not the only characteristic generating biases and disadvantages: ethnicity, race, or color are directly involved. However, if it seems straightforward to define country of birth and citizenship, collecting data on ethnicity, race, or color is complex and, in Europe, highly sensitive.

Indeed, the controversial point is defining population groups by using the same characteristics by which they are discriminated against. This raises ethical, political, legal, and methodological issues. Ethical because the choice to re-use the very categories that convey stereotypes and prejudices at the heart of discrimination entails significant consequences. Political because European countries have adopted a color-blind strategy since 1945, meaning that their political philosophies consider that racial terminologies are producing racism by themselves and should be strictly avoided (depending on the countries, ethnicities receive the same blame). Legal because most European countries interpret the provisions of the European directive on data protection and their transposition in national laws as a legal prohibition. Methodological because there is no standardized format to collect personal information on ethnicity or race and there are several methodological pitfalls commented in the scientific literature. Data on ethnicity per se are collected in censuses to describe national minorities in Eastern Europe, the UK, and Ireland, which are the only Western European countries to produce statistics by ethno-racial categories (Simon 2012 ). The information is collected by self-identification either with an open question about one’s ethnicity or by ticking a box (or several in the case of multiple choices) in a list of categories. None of these questions explicitly mention race: for example, the categories in the UK census refer to “White,” “black British,” or “Asian British” among other items, but the question itself is called the “ethnic group question.”

In the rest of Europe, place of birth and nationality of the parents would be used as proxies for ethnicity in a limited number of countries: Scandinavia, the Netherlands, and Belgium to name a few. Data on second generations can be found in France, Germany, and Switzerland among others in specialized surveys with limitations in size and scope. Moreover, the succession of generations since the arrival of the first migrants will fade groups into invisibility by the third generation. This process is already well advanced in the oldest immigration countries, such as France, Germany, Switzerland, and the Netherlands. Asking questions about the grandparents and the previous generations is not an option since it would require hard decisions to classify those with mixed ancestry (how many ancestors are needed to belong to one category?), not to mention the problems in memory to retrieve all valuable information about the grandparents. This is one of the reasons why traditional immigration countries (USA, Canada, Australia) collect data on ethnicity through self-identification questions.

The discrepancies between official categories and those exposed to discrimination have fostered debates between state members and International Human Rights Organizations – such as the UN Committee for the Elimination of Racial Discrimination (CERD), European Commission against Racism and Intolerance (ECRI) at the Council of Europe, and the EU FRA – which claim that more data are needed on racism and discrimination categorized by ethnicity. The same applies to academia and antiracist NGOs where debates host advocates and opponents to “ethnic statistics.” There is no easy solution, but the accuracy of data for the measurement of discrimination is a strategic issue for both research and policies.

1.4 Discrimination and Integration: Commonalities and Contradictions

How does research on discrimination relate to the broader field of research on immigrant assimilation or integration? On one hand, assimilation/integration and discrimination are closely related both in theory and in empirical studies. Discrimination hinders full participation in society, and the persistence of ethnic penalties across generations contradicts long-term assimilation prospects. On the other hand, both assimilation and integration theory tend to assume that the role of discrimination in shaping access to opportunities will decrease over time. Assimilation is often defined as “the decline of ethnic distinction and its corollary cultural and social difference” (Alba and Nee 2003 , 11), a definition that bears an expectation that migrants and their descendants will over time cease to be viewed as different from the “mainstream population,” reach parity in socioeconomic outcomes, and gradually become “one of us.” In the canonical definition, integration departs from assimilation by considering incorporation as a two-way process. Migrants and ethnic minorities are expected to become full members of a society by adopting core values, norms, and basic cultural codes (e.g., language) from mainstream society, while mainstream society is transformed in return by the participation of migrants and ethnic minorities (Alba et al. 2012 ). The main idea is that convergence rather than differentiation should occur to reach social cohesion, and mastering the cultural codes of mainstream society will alleviate the barriers to resource access, such as education, employment, housing, and rights.

Of course, studies of assimilation and integration do not necessarily ignore that migrants and ethnic minorities face penalties in the course of the process of acculturation and incorporation into mainstream society. In the landmark book, Assimilation in American Life , Milton Gordon clearly spelled out that the elimination of prejudice and discrimination is a key parameter for assimilation to occur; or to use his own terms, that “attitude receptional” and “behavioral receptional” dimensions of assimilation are crucial to complete the process (Gordon 1964 , 81). Yet, ethnic penalties are believed to be mainly determined by human capital and class differences and therefore progressively offset as education level rises, elevating the newcomers to conditions of the natives and reducing the social distance between groups. Stressing the importance of generational progress, assimilation theory thus tends to consider discrimination as merely a short-run phenomenon.

The main blind spots in assimilation and integration theories revolve around two issues: the specific inequalities related to the ethnicization or racialization of non-white minorities and the balance between the responsibilities of the structures of mainstream society and the agencies of migrants and ethnic minorities in the process of incorporation. Along these two dimensions, discrimination research offers a different perspective than what is regularly employed in studies of assimilation and integration.

Discrimination research tends to identify the unfavorable and unfair treatment of individuals or groups based on categorical characteristics and often shows these unfair treatments lie in the activation of stereotypes and prejudices by gatekeepers and the lack of neutrality in processes of selection. In this perspective, what has to be transformed and adapted to change the situation are the structures – the institutions, procedures, bureaucratic routines, etc. – of mainstream society, opening it up to ethnic and racial diversity to enable migrants and ethnic minorities to participate on equal footing with other individuals, independent of their identities. By contrast, in studies of assimilation and integration, explanations of disadvantages are often linked to the lack of human capital and social networks among migrants and ethnic minorities, suggesting that they have to transform themselves to be able to take full part in society. To simplify matters, studies of assimilation and integration often explain persistent disadvantages by pointing to characteristics of migrants and ethnic minorities, while discrimination research explains disadvantages by characteristics of the social and political system.

Both assimilation and integration theories have gradually opened up for including processes of ethnicization and racialization and the consequences of such processes on assimilation prospects. Most prominently, segmented assimilation theory (Portes and Rumbaut 2001 ; Portes and Zhou 1993 ) shifts the focus away from migrants’ adaptation efforts and to the forms of interaction between minority groups – and prominently the second and later generations – and the receiving society. In this variant of assimilation theory, societies are viewed as structurally stratified by class, gender, and race, which powerfully influence the resources and opportunities available to immigrants and their descendants and contribute to shaping alternative paths of incorporation. According to segmented assimilation theory, children of immigrants may end up “ascending into the ranks of a prosperous middle class or join in large numbers the ranks of a racialized, permanently impoverished population at the bottom of society” (Portes et al. 2005 , 1004), the latter outcome echoing worries over persistent ethnic and racial disadvantage. Another possible outcome is upward bicultural mobility (selective acculturation) of the children of poorly educated parents, protected by strong community ties.

The major question arising from these related fields of research – the literature on assimilation and integration, on the one hand, and the literature on discrimination, on the other – is whether the gradual diversification of Europe will result in “mainstream expansion,” in which migrants and their descendants over time will ascend the ladders into the middle and upper classes of the societies they live in, or whether we are witnessing the formation of a permanent underclass along ethnic and racial lines. This book will not provide the ultimate answer to this question. However, by introducing the main concepts, theories, and methods in the field of discrimination, as well as pointing out key research findings, policies that are enacted to combat discrimination, and avenues for future research, we hope to provide the reader with an overview of the field.

1.5 The Content of the Book

The literature on discrimination is flourishing, and it involves a wide range of concepts, theories, methods, and findings. Chapter 2 provides the key concepts in the field. The chapter distinguishes between direct and indirect discrimination as legal and sociological concepts, between systemic and institutional discrimination, and between discrimination as intentional actions, subtle biases, and what might be referred to as the cumulative effects of past discrimination on the present. Chapter 3 reviews the main theoretical explanations of discrimination from a cross-disciplinary perspective. Mirroring the historical development of the field, it presents and discusses theories seeking the cause of prejudice and discrimination at the individual, organizational, and structural levels.

Of course, our knowledge of discrimination depends on the methods of measurement, since the phenomenon is mainly visible through its quantification. Hence, Chapter 4 offers an overview of the strengths and weaknesses of available methods of measurement, including statistical analysis of administrative data, surveys among potential victims and perpetrators, qualitative in-depth studies, legal cases, and experimental approaches to the study of discrimination (including survey experiments, lab experiments, and field experiments).

Importantly, discrimination does not occur similarly in all domains of social life, and it takes different forms according to the domain in question (e.g., the labor market, education, housing, health services, and public services). Chapter 5 taps into the large body of empirical work that can be grouped under the heading “discrimination research” in order to provide some key findings, while simultaneously highlighting a distinction between systems of differentiation and systems of equality.

What happens when discrimination occurs? Chapter 6 addresses the consequences of unfair treatment for targeted individuals and groups, as well as their reaction to it. These individual and collective responses to discrimination are seconded by policies designed to tackle discrimination. However, antidiscrimination policies vary greatly across countries, and Chapter 7 provides an overview of the different types of policies against discrimination in Europe and beyond, both public policies and schemes implemented by organizations. The chapter also reflects on some of the key political and societal debates about the implementation and the future of these policies. Chapter 8 concludes on the future of discrimination research in Europe, stressing the main challenges ahead for a burgeoning scientific field.

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Fibbi, R., Midtbøen, A.H., Simon, P. (2021). Introduction: The Case for Discrimination Research. In: Migration and Discrimination. IMISCOE Research Series. Springer, Cham. https://doi.org/10.1007/978-3-030-67281-2_1

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160 Disabilities Topics for Research Papers & Essays

Looking for interesting disability topics for a research paper or project? This field is hot, controversial, and definitely worth studying!

🏆 Best Disability Topics for Research Papers

👍 disability essay topics, 📑 research questions about disabilities, 🎓 good research topics about disabilities.

The disability study field includes the issues of physical, mental, and learning disabilities, as well as the problem of discrimination. In this article, we’ve gathered great disability essay topics & research questions, as well as disability topics to talk about. We hope that our collection will inspire you.

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• v.8; 2019 Aug

Prevalence of workplace discrimination and mistreatment in a national sample of older U.S. workers: The REGARDS cohort study

Desta fekedulegn.

a Biostatistics and Epidemiology Branch, Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Morgantown, WV, USA

Toni Alterman

b Surveillance Branch, Division of Surveillance, Hazard Evaluations, and Field Studies, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, OH, USA

Luenda E. Charles

Kiarri n. kershaw.

c Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

Monika M. Safford

d Weill Cornell Medicine, Weill Cornell Medical College, New York, NY, USA

Virginia J. Howard

e Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA

Leslie A. MacDonald

f Industrywide Studies Branch, Division of Surveillance, Hazard Evaluations, and Field Studies, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, OH, USA

Associated Data

Although workplace discrimination and mistreatment (WDM) has recently drawn widespread media attention, our understanding of the prevalence of these phenomena remains limited. In the current study, we generated national prevalence estimates of WDM from a community-based cohort of employed black and white men and women aged ≥48 years. Measures of WDM in the current job were obtained by computer-assisted telephone interview (2011–2013) involving dichotomous responses (yes or no) to five questions and deriving a composite measure of discrimination (yes to at least one). Prevalence estimates and age- and region-adjusted prevalence ratios were derived with use of SUDAAN software to account for the complex sample design. Analyses were stratified by race and sex subgroups. This sample represents over 40 million U.S. workers aged ≥48 years. The prevalence of workplace discrimination ranged from a high of 25% for black women to a low of 11% for white men. Blacks reported a 60% higher rate of discrimination compared to whites; women reported a 53% higher prevalence of discrimination, compared with men. The prevalence of workplace mistreatment ranged from 13% for black women to 8% for white men. Women reported a 52% higher prevalence of mistreatment compared to men, while differences by race were not significant. Mistreatment was 4–8 times more prevalent among those reporting discrimination than among those reporting none. Subgroup differences in mistreatment were confined to the wage-employed. Findings suggest that middle age and older wage-employed blacks and women experience the highest prevalence of WDM; moreover, discrimination is strongly associated with mistreatment. This study contributes to our understanding of at-risk segments of the U.S. labor market and the need for targeted interventions to reduce WDM.

• • US workplace discrimination and mistreatment for those aged ≥48 years is reported.
• • Workplace discrimination and mistreatment varied significantly by race and sex.
• • Workplace discrimination and mistreatment is most prevalent among black women.
• • Mistreatment is 4–8 times more prevalent among workers reporting discrimination.
• • Among self-employed and those aged ≥65, mistreatment did not vary by race or sex.

1. Introduction

Despite more than five decades of federal legislation in the United States designed to protect workers against discrimination based on sex, race, color, national origin, religion (Title VII of the Civil Rights Act of 1964), age (Age Discrimination in Employment Act of 1967), and disability (Title I and Title V of the Americans with Disabilities Act of 1990), workplace discrimination remains a pervasive problem. A recent report by the U.S. Equal Employment Opportunity Commission (EEOC) indicates that over 80,000 workplace discrimination charges were filed in 2017 (30% sex-based, 34% race-based, and 22% age-related), resulting in nearly $400 million in compensation for victims across the private sector and state and local governments ( EEOC, 2018 ). Moreover, age discrimination is a costly problem representing $810 million in monetary benefits between 2010 and 2018 ( EEOC, 2019 ), and the proportion of the older U.S. workforce (≥55 years) has been on the rise for more than a decade and represents the fastest growing segment of the U.S. workforce ( Fisher, Matthews, & Gibbons, 2016 ; Toossi, 2013 ).

Definitions of workplace discrimination vary by discipline ( Okechukwu, Souza, Davis, & de Castro, 2014 ), generally characterized as unfair terms or conditions (e.g., reduced opportunity) or negative treatment based on personal characteristics or membership in a particular social group such as race, sex or age ( Chou & Choi, 2011 ; Dhanani, Beus, & Joseph, 2017 ; Rospenda, Richman, & Shannon, 2009 ). Age-based discrimination, for example, may stem from stereotypes about the willingness of older workers to accept change and their level of competence, which may manifest as a reluctance to hire, promote, train or otherwise extend opportunities due to age. ( Rippon, 2018 ). Workplace discrimination can occur at the organizational or the interpersonal level, and may vary in severity, source, and motive ( McCord, Joseph, Dhanani, & Beus, 2018 ).

A separate but related subject, not currently prohibited by law, is workplace mistreatment ( WBI, 2017a , WBI, 2017b ). Workplace mistreatment is defined as interpersonal behaviors that inflict physical or psychological harm to a worker, and can originate from sources within the workplace (e.g., supervisors or coworkers) or from outside the organization (e.g., clients, customers, or patients) ( Schat & Kelloway, 2005 ). Workplace mistreatment is often broadly characterized as threats, harassment, or bullying – interpersonal behaviors that can manifest more specifically as incivility, ostracism, conflict, aggression, unwanted sexual attention, and abusive supervision.

While the national prevalence of workplace discrimination and mistreatment (WDM) in the U.S. workforce has been previously reported ( Alterman, Luckhaupt, Dahlhamer, Ward, & Calvert, 2013 ; Avery, McKay, & Wilson, 2008 ; Chavez, Ornelas, Lyles, & Williams, 2015 ; Chou & Choi, 2011 ; Lutgen-Sandvik & Namie, 2009 ; Rospenda et al., 2009 ; Schat, Frone, & Kelloway, 2006 ), existing research suffers from a number of limitations. First, most studies have relied on small or moderately sized samples ( Chou & Choi, 2011 (n = 420); Avery et al., 2008 (n = 763); Rospenda et al., 2009 (n = 2151); Schat et al., 2006 (n = 2500)). A number of studies have used the Health and Retirement Survey ( Giasson, Queen, Larkina, & Smith, 2017 ; Han and Richardson, 2015 ; Rippon, Zaninotto, & Steptoe, 2015 ) and another used data from the Midlife in United States II (MIDUS II) study ( Chou & Choi, 2011 ) to look at the prevalence of age discrimination in the workplace within the older segment of the workforce (e.g., those aged ≥ 50 years who represent over two-fifths of the U.S. workforce and growing) ( BLS, 2017 ; Toossi, 2013 ). Although the Health and Retirement Survey ( Giasson et al., 2017 ; Han and Richardson 2015; ; Rippon et al., 2015 ), MIDUS II ( Chou & Choi, 2011 ), the National Health Interview Survey ( Alterman et al., 2013 ), and the Equal Employment Opportunity Commission 40th Anniversary Civil Rights in the Workplace Survey, (conducted by Gallup) ( Avery et al., 2008 ) oversampled minorities for more reliable prevalence estimates, other studies have not. Findings from the most recent national studies on discrimination were based on data collected nearly a decade ago. Only one prior study examined both workplace discrimination and mistreatment ( Rospenda et al., 2009 ). Despite growing research on the effects of WDM, little is known about the magnitude of differences in the prevalence of WDM by race-sex subgroups ( McCord et al., 2018 ). Prior studies able to explore race- or sex-specific differences were confined to convenience samples or population-based surveys with limited geographical representation, narrow labor market representation and/or demographic composition, and were often limited by small sample sizes ( Hammond, Gillen, & Yen, 2010 ; Lutgen-Sandvik, Tracy, & Alberts, 2007 ; Nunez-Smith et al., 2009 ; Simons, 2008 ; Triana, Jayasinghe, & Pieper, 2015 ).

The purpose of this study was to generate national prevalence estimates of WDM in middle-age and older U.S. workers by race-sex subgroups, to examine the magnitude of subgroup differences, and to investigate whether individuals who experienced discrimination reported more frequent mistreatment than those who did not. Using data from a national population-based sample of middle aged and older black and white men and women employed across a range of sectors within the U.S. labor market, we generate national prevalence estimates of perceived WDM by race-sex subgroups and examine the magnitude of subgroup differences. This study also examined the cross-sectional association between workplace discrimination and mistreatment.

This study contributes to our understanding of WDM in four specific ways: (1) provides national prevalence estimates of WDM; discrimination and mistreatment originating from a work context is considered more damaging than in other life domains, both for those who experience and for those who witness it ( Dhanani et al., 2017 ); (2) strengthens the literature on age discrimination at the workplace; (3) includes a large sample of black and white men and women aged ≥48 years, representing 44% of the employed U.S. workforce ( BLS, 2017 ); and (4) identifies subgroups within the U.S. workforce disproportionately affected by WDM. Relative to existing national studies, the current study improves estimates of the prevalence of WDM through (a) use of a larger sample size; (b) the assessment of age discrimination, which is a neglected area of research; (c) the assessment of both discrimination and mistreatment; (d) sampling among older workers who comprise the fastest growing segment of the U.S. labor force; (e) oversampling of blacks to obtain more reliable prevalence estimates; and (g) more recent data that would serve as important benchmark for prevalence of WDM prior to the widespread and continuing national news reports of workplace sexual harassment and mistreatment in the media.

2.1. Study sample

The REasons for Geographic and Racial Differences in Stroke (REGARDS) study involves a national, population-based, longitudinal cohort of 30,239 non-Hispanic black and non-Hispanic white participants aged ≥45 years enrolled between 2003 and 2007. Enrollment consisted of a Computer Assisted Telephone Interview (CATI), followed by completion of an in-home clinical exam and self-administered questionnaires ( Howard et al., 2005 ). The study sought to elucidate reasons for regional and racial differences in stroke incidence in the United States, specifically, the excess stroke-related mortality among blacks and residents of the southeast.

The study design provided for approximately equal representation by race and sex, through recruitment of participants via stratified random sampling with strata defined by region, race, and sex. The design involved intentional oversampling of blacks and residents of the geographic regions referred to as the “stroke buckle” (coastal North Carolina, South Carolina, and Georgia) and “stroke belt” (remainder of North Carolina, South Carolina, and Georgia, as well as Alabama, Mississippi, Tennessee, Arkansas, and Louisiana). Nearly one-half of the study participants were from the “stroke belt/buckle” region, while the remaining half were from the remaining 40 contiguous U.S. states and the District of Columbia. Participants gave consent verbally by phone and later in writing during a clinical exam. The Institutional Review Board at the University of Alabama at Birmingham (UAB) approved the study methods.

The sample for the current analyses was drawn from the REGARDS occupational ancillary study ( MacDonald, Pulley, Hein, & Howard, 2014 ). All active REGARDS study participants were asked to complete an occupational survey during routine bi-annual follow-up by CATI, a median 6.5 years after enrollment. Over a 2-year period (2011–2013), 17,648 participants consented to the occupational survey (87% response). Further details on data collection methods and measures are available elsewhere ( MacDonald et al., 2014 ). Institutional review boards at the UAB and the National Institute for Occupational Safety and Health (NIOSH) approved the ancillary study. Participants were eligible for inclusion in the current analyses if they were employed at the time of the occupational survey (n = 4949). Individuals who did not answer all the questions related to workplace discrimination and mistreatment (n = 130), whose occupational status (n = 3) or educational status (n = 2) was missing, or who were employed in farming, fishing, and forestry (n = 16, due to small sample size) were excluded. After these exclusions, data from 4798 participants were analyzed, from which the weighted proportions were 11% black (n = 1616) and 47.4% women (2,581).

2.2. Measures

Measures of workplace discrimination and mistreatment were selected from the NIOSH Quality of Work Life Questionnaire (NIOSH QWL) ( NIOSH, 2010 ). We assessed workplace discrimination at the current job by asking the following four single-item binary (yes, no) questions:

• (1) “On your job, do you feel in any way discriminated against because of your race or ethnic origin?”
• (2) “On your job, do you feel in any way discriminated against because of your sex?”
• (3) “On your job, do you feel in any way discriminated against because of your age?”
• (4) “On your job, do you feel in any way discriminated against for any other reason?”

In addition, a composite measure of discrimination was derived to represent the occurrence of any type of discrimination (i.e., yes to at least one of the 4 discrimination measures). We assessed workplace mistreatment by the following single-item binary (yes, no) question: “In the last 12 months, were you threatened, bullied, or harassed by anyone while you were on the job?”

2.3. Statistical analysis

Survey procedures in the SAS-callable SUDAAN software (version 11.0.1, Research Triangle Institute, Research Triangle Park, North Carolina) were used to estimate population-level summary measures, accounting for sample weights, stratification, and other complex design features similar to those described for other national surveys ( Korn & Graubard, 2011 ; Mirel et al., 2013 ). The REGARDS sampling weights derived for the full cohort were revised to reflect the race/sex/age/region composition of the occupational ancillary study sample. Descriptive analyses to characterize the sociodemographic characteristics of the sample were performed with a PROC CROSSTAB procedure. Adjusted prevalence and prevalence ratios (PRs) of discrimination and mistreatment and their associated 95% confidence intervals (CIs) were estimated with weighted logistic regression (PROC RLOGIST) ( Bieler, Brown, Williams, & Brogan, 2010 ). All estimates (prevalence and PRs) were adjusted for race, sex, age, and region (stroke belt, stroke buckle, and other). A PR was considered statistically significant if the 95% CI did not contain the null value (PR = 1.00). All proportions and prevalence results reported have been weighted.

Adjusted prevalence and PRs by race-sex subgroups, race, and sex were estimated from logistic regression models for each discrimination and mistreatment measure as a function of race (2 levels), sex (2 levels), interaction between race and sex (4 levels), age (continuous), and region (3 levels). Sensitivity analyses were performed to examine the influence of age strata when the discrimination data were collected (aged 48–64 versus ≥65 years). Additional sensitivity analyses were performed to evaluate the influence of employment type (wage vs. self-employed).

Logistic regression analyses were used to examine the association between discrimination and mistreatment. Estimates of adjusted prevalence and PRs of mistreatment were derived from models with the following predictors: discrimination type (2 level), race (2 levels), sex (2 levels), three-way interaction between discrimination type, race, and sex (8 levels), age (continuous), and region (3 levels). Separate models were fitted for four forms of discrimination and the composite discrimination measure (five models total).

3.1. Sociodemographic characteristics

The study sample comprised employed 4798 participants, representing a population of >40 million U.S. workers aged 48 years or older. Sociodemographic characteristics of the sample are shown overall and by race-sex subgroups in Table 1 . The study population was half male (53%), and the majority were white (89%); the race-sex composition was 6% black women (BW), 5% black men (BM), 42% white women (WW), and 47% white men (WM). At the time of the occupational survey, 27% were aged 48–54 years, 50% were aged 55–64 years, and 23% were aged ≥65 years. Nearly 60% were college graduates. The majority were wage-employed (76%), with nearly 60% employed in management and professional occupations, 20% employed in sales and office, 10% in service, and <10% in skilled and general manual labor occupations. Seventeen percent lived in the stroke belt/buckle region and 44% had a household income of ≥$75,000. Median tenure in the current job was nearly 13 years. There were significant differences in education, occupation, household income, and type of employment across the four race-sex subgroups (p < 0.01).

Sociodemographic characteristics of U.S. workers aged ≥48 years, by race-sex subgroups.

Percentages (that is, prevalences) might not sum to 100 because of rounding.

Type of employment, supervisory status, self-employed type of work, representation by union, and work hours preference were all defined for the current job the participants held at the time of the occupational survey. “Ever on shift work” reflects lifetime shift work status, whereas “currently on shift work” reflects shift work status at the time of the occupational survey.

Note: after application of sampling weights, the 4798 participants in the sample represent 40,352,947 workers in the U.S. population (5.9% black women, 5.1% black men, 41.5% white women, and 47.4% white men).

3.2. Prevalence of workplace discrimination and mistreatment

There were no statistically significant differences in the prevalence of age discrimination by race-sex subgroups, race, or sex ( Table 2 ), which ranged from a high of 10% for BW to a low of 6% for WM ( Fig. 1 ). The prevalence of racial discrimination was seven times higher for blacks than whites (PR = 7.01, 95% CI: 4.27–11.5) ( Table 2 ) and ranged from a high of 17% for BW and 12% for BM to a low of 2% for WW and WM ( Fig. 1 ). Moreover, racial discrimination was 10 times higher among BW than WW (PR = 10.1, 95% CI: 5.01–20.4), whereas racial discrimination was 5 times higher among BM than WM (PR = 5.03, 95% CI: 2.48–10.2) ( Table 2 ). The prevalence of sex discrimination was 5 times higher among women than among men (PR = 5.36, 95% CI: 2.89–9.92) ( Table 2 ), ranging from a high of 11% for BW and 8% for WW to a low of 2% for BM and WM ( Fig. 1 ). The comparison of sex discrimination between men and women was similar between blacks and whites (BW vs BM: PR = 5.45, 95% CI: 2.41–12.3; and WW vs. WM: PR = 5.34, 95% CI: 2.63–10.8). The prevalence of sex discrimination did not differ significantly by race ( Table 2 ).

Prevalence ratio (PR) of workplace discrimination and mistreatment among U.S. workers aged ≥48 years, by race-sex subgroups, race, and sex.

Prevalence of workplace discrimination and mistreatment among U.S. workers aged ≥48 years, by race-sex subgroups.

The prevalence of “any other” form of workplace discrimination was 82% higher among blacks than among whites (PR = 1.82, 95% CI: 1.19–2.77) ( Table 2 ), ranging from a high of 9% for BM and 8% for BW to lows of 5% for WW and 4% for WM ( Fig. 1 ). Reports from BM of other forms of workplace discrimination were more than twofold higher than those from WM (PR = 2.37, 95% CI: 1.21–4.65).

The prevalence of experiencing at least one form of workplace discrimination ranged from a high of 25% for BW (18% for BM and 16% for WW) to a low of 11% for WM ( Fig. 1 ), with significant differences by race-sex subgroups, race, and sex. Overall, blacks experienced a 60% higher prevalence of discrimination compared to whites (PR = 1.60, 95% CI: 1.27–2.00) ( Table 2 ). Specifically, BW experienced a 51% higher prevalence of discrimination than WW (PR = 1.51, 95% CI: 1.17–1.95), and BM experienced a 71% higher prevalence of discrimination than WM (PR = 1.71, 95% CI: 1.15–2.56). Overall, the reported prevalence of discrimination was 53% higher for women than for men (PR = 1.53, 95% CI: 1.16–2.02), whereas WW experienced 56% higher prevalence of discrimination than WM (PR = 1.56, 95% CI: 1.13–2.16).

The prevalence of workplace mistreatment was 52% higher among women than men (PR = 1.52, 95% CI: 1.07–2.17), ranging from a high of 13% for BW to a low of 8% for WM ( Fig. 1 ). Race-sex subgroups were not significantly different except for WW, who had a 57% higher prevalence of mistreatment than WM (PR = 1.57, 95% CI: 1.05–2.35) ( Table 2 ).

3.3. Sensitivity analysis

The pattern of results reported previously for the full sample were replicated by age strata (48–64 and ≥ 65 years) ( Table S1 and Fig. S1 ). Prevalence ratios for exposure to at least one form of discrimination did not change among younger workers (aged 48–64 years). However, among workers aged ≥65 years, there were no significant subgroup differences in the prevalence of mistreatment. Differences in the prevalence of “any discrimination” (i.e., at least one) were confined to black and white men and race overall. The prior pattern of subgroup results for the prevalence ratios for racial discrimination and any discrimination were mostly consistent when analyses were run by employment type (wage- and self-employed) ( Table S2 and Fig. S2 ). Mistreatment did not vary by race or sex among the self-employed. However, wage-employed blacks experienced a higher prevalence of age and sex discrimination than did wage-employed whites ( Table S2 ), while self-employed blacks experienced a lower prevalence of age discrimination than did self-employed whites.

3.4. Association of discrimination with mistreatment

The prevalence of mistreatment, stratified by discrimination type, is presented in Fig. 2 . Among workers who experienced any discrimination, the prevalence of mistreatment ranged from a high of 34% for WM, 34% for WW, and 31% for BW, to a low of 26% for BM ( Fig. 2 ). Among those who did not report any discrimination, the prevalence of mistreatment was low, ranging from 5% for WM to 7% for BW. The data in Fig. 2 show that those reporting discrimination experienced a substantially higher prevalence of mistreatment compared with those who did not report discrimination. Mistreatment was 4–8 times more prevalent among those reporting at least one form of discrimination compared with those reporting none ( Table 3 ). For example, the prevalence of mistreatment among black women who reported at least one form of discrimination was nearly 5 times higher than those reporting no discrimination (PR = 4.71, 95% CI: 2.71–8.19; BM: PR = 3.65, 1.65–8.10; WW: PR = 4.40, 2.84–6.84; and WM: PR = 7.54, 4.13–13.8) ( Table 3 ).

Prevalence of workplace mistreatment among U.S. workers aged ≥48 years, by discrimination in race-sex subgroups.

Association between workplace discrimination and mistreatment among U.S. workers aged ≥48 years, by race-sex subgroups.

Values (%) in the table represent the prevalence ratios (PRs) comparing prevalence of mistreatment in those who experienced discrimination relative to those who did not experience discrimination in each race-sex subgroup.

4. Discussion

We generated national estimates of the prevalence of workplace discrimination and mistreatment by race, sex, and race-sex subgroups for a sample of black and white men and women aged ≥48 years. By including measures of both discrimination (race, sex, age, any other reason) and mistreatment, we provide a more complete understanding of WDM in the U.S. workforce than many prior studies. The prevalence of workplace discrimination varied significantly by race, sex, and race-sex subgroups, with a higher prevalence among blacks compared with whites and a higher prevalence among women compared with men. The prevalence of workplace mistreatment varied by sex, with a higher prevalence among women compared with men (overall) and a higher prevalence among white women compared with white men.

Our findings corroborate prior research indicating that racial minorities experience race-based workplace discrimination at higher rates compared to whites ( Avery et al., 2008 ; ( Rospenda et al., 2009 ). In our study, the prevalence of race-based workplace discrimination was 7 times higher among blacks compared to whites but there was no significant difference in race-based discrimination by sex. Similarly, findings from the Behavioral Risk Factor Surveillance System (BRFSS, 2004–2010, n = 70,080) showed that the prevalence of racial discrimination was significantly higher among blacks compared to whites (21.2% vs 4.2%), whereas differences in the prevalence of racial discrimination by sex were not significant (Chavez at al., 2015).

In addition, our finding that blacks and women have a higher prevalence of exposure to at least one form of workplace discrimination compared with whites and men is also consistent with prior findings in occupation-specific studies ( Hammond et al., 2010 ; Nunez-Smith et al., 2009 ; Sellers, Cherepanov, Hanmer, Fryback, & Palta, 2013 ). Following a survey of U.S. physicians conducted in 2006–2007 (n = 529), Nunez-Smith et al. (2009) reported substantial differences in prevalence of perceived racial/ethnic workplace discrimination at the current job, by race: 59% of black, 39% of Asian, 35% of “other” race, 24% of Hispanic/Latino, and 21% of white physicians reported experiencing discrimination “sometimes, often, or very often.” In a study of hospital workers in northern California, Hammond et al. (2010) reported that the prevalence of race-based workplace discrimination (in the past year) was significantly higher among blacks than among whites (19.7% vs. 3.1%), whereas racial differences in the prevalence of sex and age discrimination were not significant. In the current study, the prevalence of age discrimination was similar across subgroups, ranging from a high of 9.5% among BM to a low of 6.3% among WM; the overall prevalence of age discrimination among older workers was 6.9% but did not manifest differentially across subgroups.

A study of employees from five organizations reported that minority women were subject to double jeopardy at work, experiencing the most sexual harassment because they were both women and members of a minority group ( Berdahl & Moore, 2006 ). Although black women in the current study experienced a 32% higher prevalence of sex discrimination compared to white women, the difference was not statistically significant. The difference between the two studies may be due to differences in the sex discrimination measure used (Berdahl and Moore used a 19-item questionnaire to assess sexual harassment, while the current study used a single question) or sample size.

Our findings are consistent with prior research suggesting that women experience elevated levels of workplace discrimination ( Avery et al., 2008 ; Rospenda et al., 2009 ) and mistreatment compared to men ( Berdahl & Moore, 2006 ; Magley, Gallus, & Bunk, 2010 ; McCord et al., 2018 ; Okechukwu et al., 2014 ; Saad, 2015 ). Results of a recent Gallup poll indicate that 12% of working women, versus 5% of working men, reported feeling they had been passed over for a promotion or other opportunity because of their sex ( Saad, 2015 ). A recent meta-analysis indicated that women report significantly more sex-based workplace mistreatment than men ( McCord et al., 2018 ). While our global measure of mistreatment (threatened, bullied or harassed) did not illicit whether the mistreatment was sex-based, women in our study were 50 percent more likely to experience mistreatment than men. Because our findings were gathered in 2011–2013, they serve as important benchmarks for WDM prevalence prior to the widespread and continuing national news reports of sexual workplace harassment and mistreatment reported among high-profile individuals in the entertainment and media industries ( Cobb & Horeck, 2018 ).

The prevalence of workplace mistreatment was significantly higher for women than for men (12.1% vs. 8.0%), but racial differences (11.8% for blacks vs. 9.7% for whites) were not statistically significant. Comparing our results to the 2010 National Health Interview Survey, which has a nearly identical measure of mistreatment, we report a marginally higher prevalence of mistreatment overall (9.9% vs. 7.8%) and for women (12.1% vs. 9.3%), blacks (11.8% vs. 8.2%), and whites (9.7% vs. 7.9%) ( Alterman et al., 2013 ). Our findings are also consistent with results from the 2017 national survey by the Workplace Bullying Institute (WBI), which reported that 9% of workers were bullied in the past year, and that women were most often the targets of workplace bullying ( WBI, 2017c ).

In sensitivity analyses, results for exposure to at least one form of discrimination and for mistreatment in the overall sample were consistent for all sub-group comparisons in the lower age strata (48–64 years). In the higher age strata (≥65 years), results were consistent only for discrimination involving comparisons between black men vs. white men and blacks vs. whites; the non-significant findings for the other subgroup comparisons may be due to true smaller subgroup differences among older workers combined with reduced statistical power. Discordant findings for exposure to mistreatment among older workers (aged ≥ 65 years) involving comparisons between white women and white men and women vs men are similarly impacted by reduced statistical power; however, a change in the direction of the effect estimates from positive to negative for subgroup comparisons by sex suggests possible effect modification that will need to be confirmed in future research with a larger sample.

Results for exposure to at least one form of discrimination and for mistreatment in the overall sample were consistent with the results for all sub-group comparisons involving wage, but not self-employed, individuals. The non-significant sub-group differences in exposure to discrimination among the self-employed may be due to true smaller differences in combination with reduced statistical power. Discordant findings for exposure to mistreatment among the self-employed may also be influenced by reduced statistical power but, more importantly, changes in the direction of the effect estimates from positive to negative for most subgroup comparisons suggests possible effect modification by employment type that will need to be confirmed in future research with a larger sample.

Differential exposure to WDM by race, sex, and race-sex subgroups has important public health implications. Previous research has shown that exposure to WDM can be physically and psychologically harmful to the targeted individuals ( Dhanani et al., 2017 ; Høgh, Mikkelsen, & Hansen, 2011 ; Lewis, Cogburn, & Williams, 2015 ; Nielsen & Einarsen, 2012 ; Okechukwu et al., 2014 ; Pascoe & Smart Richman, 2009 ; Rospenda et al., 2009 ). It has been theorized by Dhanani et al. (2017) that workplace discrimination threatens a person's sense of self and increases feelings of marginalization, which induces a stress response manifesting in adverse mental and physical health as well as poor employee performance outcomes (negative job attitudes, decreased positive and increased negative workplace behaviors, sickness-related absenteeism, turnover, grievance, compensation and litigation, and reduced productivity) ( Dhanani et al., 2017 ; Hoel, Sheehan, Cooper, & Einarsen, 2011 ; Triana et al., 2015 ). The negative impacts of discrimination on physical health outcomes ( Lewis et al., 2015 ) includes objective clinical disease outcomes (all-cause mortality, hypertension, incident breast cancer, and incident asthma) and preclinical outcomes with established linkages to later disease (carotid intima media thickness, coronary artery calcification, nighttime blood pressure elevation, increase in visceral fat, and inflammation). WDM also can influence the adoption or exacerbation of unhealthy behaviors such as smoking and drinking ( Chavez et al., 2015 ; Pascoe & Smart Richman, 2009 ; Rospenda et al., 2009 ). Even subtle and interpersonal forms of discrimination, which are often overlooked, are as detrimental to those targeted as are the more typical, overt forms of discrimination ( Jones, Peddie, Gilrane, King, & Gray, 2016 ). These reports of adverse effects, combined with our findings of differential exposure, suggest that WDM may be an important under-recognized determinant of health disparities by race and sex.

This study has several limitations. Due to constraints on survey administration time, we used single-item measures to characterize WDM. Single-item measures of complex psychological constructs have shortcomings ( Fisher et al., 2016 ; Hoeppner, Kelly, Urbanoski, & Slaymaker, 2011 ; Krieger, Smith, Naishadham, Hartman, & Barbeau, 2005 ): they are more vulnerable than multiple-item measures to random measurement errors and internal-consistency reliability statistics cannot be computed. The global single-item measure of mistreatment used in our study (i.e., threatened, bullied, or harassed on the job in the past 12 months) makes it infeasible to learn the prevalence of different forms of mistreatment and how exposure to specific types of mistreatment (e.g., sexual harassment, bullying) vary by race-sex subgroups. Worker populations whose jobs involve greater social or interpersonal interactions (e.g., healthcare or service workers) may have more opportunities for being subject to mistreatment or discrimination. As is true for much of the WDM research conducted to date, the source of discrimination or mistreatment (such as a customer or client, a superior, peer, or subordinate) was not identified in our study.

Data collection for exposure to WDM was restricted to the current job; a participant who held multiple jobs concurrently reported their experiences at the job where they spent the majority of their working hours. Sensitivity analyses were likely underpowered; therefore, we cannot rule out that differences reported by age strata and employment type are due to chance. Because data on sex-race composition of the participant's workplace were not collected, we cannot examine whether race-sex differences in the prevalence of WDM varies by minority/majority status. This study collected self-reported sex as a binary variable when other identifications of sex and gender relevant to the study of WDM are possible (e.g., transsexual, transgender). It is not possible to know if those exposed to “any other form of discrimination” included individuals with non-binary identities.

While the racial diversity of the sample was limited to non-Hispanic whites and blacks, we expect our findings to be generalizable to the majority of the U.S. workforce aged ≥48 years because the racial composition of the older segment of the U.S. workforce is majority white and black (US Senate Special Committee on Aging Report ( ADD, 2017 ). However, our results are not generalizable to other racial and ethnic minority groups. Despite the aforementioned limitations, this study represents an important contribution to our understanding of the prevalence of discrimination and mistreatment among workers in the United States. Strengths of this study include the large national population-based sample of middle-aged and older (aged ≥ 48 years) black and white men and women employed across 77% of all detailed U.S. Census occupation codes. This is one of the first national studies to examine associations between discrimination and mistreatment in an employed sample.

In conclusion, our results suggest that women and blacks employed across a broad range of the US labor market perceived more workplace discrimination than men and whites, respectively. Race differences were more pronounced for race-based discrimination, whereas sex differences were more pronounced for sex-based discrimination, relative to other forms of discrimination. Although women experienced more workplace mistreatment than men, there were no significant differences in mistreatment by race. Overall, our findings regarding race and sex differences are consistent with other research with younger employed samples. Our results also suggest that discrimination may be a determinant of mistreatment, with those experiencing discrimination reporting a higher prevalence of mistreatment compared with their counterparts. However, due to the cross-sectional design, we cannot establish that discrimination precedes mistreatment; it is possible that mistreatment precedes discrimination. It is also worth noting that mistreatment may be a way to circumvent illegal forms of harassment and discrimination (e.g., to sexually harass without the risk of being accused of sexual harassment). Investigation using a longitudinal rather than cross-sectional design would be appropriate to establish casual direction. The imbalance in prevalence of WDM among women and racial minorities represents an important focus for both prevention and intervention.

Acknowledgments

This research project is supported by cooperative agreement U01 NS041588, co-funded by the National Institute of Neurological Disorders and Stroke and the National Institute on Aging, National Institutes of Health, Department of Health and Human Services. The occupational ancillary study is supported by intramural funding by the National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention. The authors thank the other investigators, the staff, and the participants of the REGARDS study for their valuable contributions. A full list of participating REGARDS investigators and institutions is available at www.regardsstudy.org/ . The authors additionally thank Cathy Tinney-Zara (Biostatistics and Epidemiology Branch, HELD/NIOSH) for proofreading and Seleen Collins (Information Resources and Dissemination Branch, EID/NIOSH) for editing the manuscript.

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.ssmph.2019.100444 .

The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the NINDS, NIA, CDC, or NIOSH. Representatives of NINDS and NIOSH were involved in the review of the manuscript but not directly involved in the collection, management, analysis, or interpretation of the data.

Ethical approval

The Institutional Review Boards at the University of Alabama at Birmingham (UAB) and the National Institute for Occupational Safety and Health (NIOSH) approved the study.

The prevalences represent weighted population estimates and were adjusted for stratification variables (race, sex, age at time of enrollment, and region of residence at time of enrollment). “At least one” refers to experiencing at least one of the four discrimination types (age, racial, sex, or other).

The error bars represent the estimate plus/minus the standard error (SE), not the confidence interval (CI) and hence conclusions about the statistical significance of differences between groups cannot be made by looking at whether the error bars overlap or not.

The prevalences represent weighted population estimates and were adjusted for stratification variables (race, sex, age at time of enrollment, and region of residence at time of enrollment). “At least one” refers to experiencing at least one of the four discrimination types (age, racial, sex, or other). The error bars represent the estimate plus/minus the standard error (SE), not the confidence interval (CI) and hence conclusions about the statistical significance of differences between groups cannot be made by looking at whether the error bars overlap or not.

Appendix A. Supplementary data

The following is the Supplementary data to this article:

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