This chapter first provides an overview of three aspects of public life that affect social and gender diverse (SGD) populations: public policy, social movements, and changing public opinion. It then turns to the emerging literature on how structural factors—law, public policy, and public attitudes—influence the well-being of SGD populations, including economic outcomes, experiences of victimization and violence, and mental and physical health. Collectively, this research falls under the umbrella of what researchers call structural stigma, which is defined as “societal-level conditions, cultural norms, and institutional policies that constrain the opportunities, resources, and well-being of the stigmatized” (Hatzenbuehler and Link, 2014, p. 2).
The public policy process includes defining social problems that may require policy solutions, framing public policies for the general public and policy makers, developing strategies to effect policy adoption, effectively implementing public policies, and developing accountability and evaluation mechanisms. Policies seldom change without outside social forces organizing to effect change. Thus, advocacy organizations providing services and seeking changes in public policy, which are often sponsored by government programs, are central to the policy process.
Policy Advocacy Groups
Public policies affecting SGD populations change when advocates articulate what and why changes are needed and how to implement them (Taylor, Lewis, and Haider-Markel, 2018). Given the multiple levels of government—federal, state, and local—and the division of functions associated with the separation of powers, the U.S. political and legal systems offer numerous access points to effect policy change. The complexity also means the process is susceptible to policy gridlock (Baumgartner and Jones, 1993). This means that sustained advocacy for policy change is necessary, and social movement organizing and policy advocacy groups need to have the infrastructure to maintain pressure.
Prior to the emergence of a social movement, however, are the contextual and structural factors that define choices, how individuals define problems, and how they see themselves in relation to those problems (Gusfield, 1993, 1996). Among SGD populations, early organizing centered on gay men and lesbian women who had to construct an identity in the context of high degrees of social and structural stigma (Bernstein, 2002; D’Emilio 1983). This stigma led to individuals not embracing a public gay identity until about 1958, where organizations embraced the term “homophile” as opposed to “homosexual” to de-center sex, which was often viewed in the public eye as associated with sexual deviancy (Armstrong, 2002; Bernstein, 2002; D’Emilio, 1983; Schneider and Ingram, 1993). As the social movement developed and contexts changed, the strategies, identities, and definition of problems have also changed (Gusfield, 1993, 1996).
Early organizing in what can be termed the homophile era (1958–1968) began with organizations such as the Mattachine Society and the Daughters of Bilitis pursuing strategies intended to secure civil liberties for lesbian women and gay men, effectively to remove state policies that criminalized homosexuality (Armstrong, 2002; D’Emilio, 1983). A general way to understand these efforts was a struggle for rights for gay and lesbian people to be left alone, and organizing activities were primarily about quietly lobbying elected officials and engaging with mainstream political institutions (Armstrong, 2002; D’Emilio, 1983). In April 1965, astronomer Frank Kameny and other activists began a new approach by picketing the White House. Inspired by the Civil Rights Movement and Black politics, activists Kameny and Craig Rodwell embraced the slogan, “Gay Is Good,” and hinted that a change in strategy to one of a proud and public gay identity needed to be embraced to effect change.
The “Stonewall era” (1969–1973) was characterized by a radically different view, embracing gay liberation (Armstrong, 2002; D’Emilio, 2000; Ghaziani, Taylor, and Stone, 2016). In addition to fully embracing an out-of-the-closet proud gay identity, gay liberation organizations, such
as the Gay Liberation Front (GLF), embraced a broad policy agenda that supported other liberation movements and direct action protests, seeking to advance economic issues and gender and racial justice, even though there remained sexual stigma in those other movements (Armstrong, 2002). Some gay liberation activists such as Marsha P. Johnson and Sylvia Rivera created Street Transvestite Action Revolutionaries (STAR) to serve some of the most vulnerable SGD people (Shepard, 2013), while others, frustrated with the priorities of the GLF, established the Gay Activists Alliance to pursue policies directly affecting gay and lesbian people, as well as to hold dances to create space for connection, gay identity building, and community (Armstrong, 2002).
This identity-based movement continued with the establishment of the National Gay Task Force in 1973 and the Gay Rights National Lobby in 1976 (the former was renamed the National LGBTQ Task Force and the latter eventually became the Human Rights Campaign). While still building capacity, these organizations pursued policy change through interaction with mainstream political institutions and embraced a public gay identity by engaging in pride marches (D’Emilio, 2000; Ghaziani, Tayor, and Stone, 2016).
Over time, LGBT social movements have engaged in cycles of mainstream tactics and direct action protest tactics, each with their successes and failures (D’Emilio 2000; Ghaziani, Tayor, and Stone, 2016). For example, the direct action protests by ACT UP during the HIV/AIDS crisis changed policies and practices to address the virus (Cohen, 1999; Gould, 2009). The mainstream strategy, which remains dominant, requires a wide range of organizations and the growth of capacity to take advantage of the numerous access points and political opportunities in the U.S. political system.
Because there are multiple access points, there are numerous opportunities for policy and legal change, but only if an infrastructure is present to take advantage of such opportunities (McAdam, 1982). Early efforts to create national advocacy organizations for SGD people were categorized as “weak, poorly funded, and newly created” (Stone, 2012, p. 41). The contemporary LGBT advocacy coalition has significant infrastructure and capacity. The coalition of organizations that advocate on behalf of SGD populations consists of a myriad of groups (Taylor et al., 2018); some focus on policy advocacy, many prioritize litigation, and others are issue specific, faith based, or work primarily to deliver goods and services. For example, the top-ranked grant-receiving organizations in 2017 included organizations that primarily provide public services (e.g., New York LGBT Community Center and Los Angeles LGBT Center); others that focus on national policy advocacy (e.g., the Human Rights Campaign and the National LGBTQ Task Force); many others that focus on legal advocacy (e.g., Transgender Law Center, National Center for Lesbian Rights, and Lambda
Legal Defense & Education Fund); and select organizations that focus on carrying out research on SGD populations and policies affecting them (e.g., Williams Institute). In 2017, about 29 percent of grants from private groups went to organizations focused on nationwide issues, 5 percent to those focused on regional (multistate) issues, 10 percent to those focused on state issues, 30 percent to those focused on local issues, and 26 percent to those focused on international issues (Wallace, Maulbeck, and Kan, 2019).
Advocacy coalitions and actors who leverage opportunities to effect policy change, collectively known as policy entrepreneurs, frequently share information to spread strategies, tactics, successes, and failures (Boushey, 2010; Mintrom and Norman, 2009). They set policy priorities (Kingdon, 1984), gain access to decision makers and decision-making arenas (Andrews and Edwards, 2004), and engage in public education and lobbying (Wright, 2003). Policy entrepreneurs often monitor the successful implementation of policies (Andrew and Edwards, 2004), and they look for future political opportunities to reinforce their policy priorities (Theodoulou, 2013). Occasionally, the differences between organizations create coordination conflicts that may impede their effectiveness (Engel, 2007; Haider-Markel, 1997).
Alongside the advocacy coalition for SGD people, there is a countermovement that opposes policy advancements designed to further the well-being of SGD people. These organizations also try to gain access to policy makers to advance their interests and control the policy agenda (Fetner, 2008; Stone, 2012; Wilson and Burack, 2012) and to craft arguments to particular audiences in opposition to policies that may benefit SGD people (Burack, 2008). Like advocacy organizations devoted to the advancement of rights for SGD populations, organizations opposed to such advancement also devote considerable resources to framing and tailoring their messages to the public (Flores, 2019; Stone, 2012). These frames are often delivered through costly initiative and referendum campaigns in an attempt to affect ballot measures (e.g., same-sex marriage bans) (Fetner, 2008; Stone, 2012). The use of direct democracy by the countermovement has historically maneuvered the LGBT advocacy coalition into a defensive position (Fetner, 2008; Stone, 2012).
Thus, over time, the SGD rights movement and the countermovement compete over issue priorities and how to frame those issues. In this dynamic context, structural forms of exclusion (e.g., California’s Briggs Initiative to ban gay men and lesbian women from being school teachers) and the context of competing movements propelled lesbian women and gay men into the public eye, mobilizing them to engage in canvassing and other forms of activism to advance their positions (Armstrong, 2002). In this political and social environment, the understanding of sexual and gender diversity in the United States has changed as the SGD rights movement strategically framed policies to the voting public (Stone, 2012). Changing such discourses can
also change how movements understand themselves and their identities (Gusfield, 1993, 1996), which has happened for SGD populations. This kind of change is consistent with studies of numerous social movements in the United States during the 20th and early 21st centuries.
Political elites, social movements, and mass media can influence which issues become important for public policy and how those issues are framed (Garretson, 2018; Jones and Brewer, 2020; Iyengar and Kinder, 2010; Lee, 2002; Zaller, 1992). The way issues are communicated affects how people come to understand those issues, particularly when certain values are emphasized to frame proposed policies (Brewer, 2001, 2007). Policy advocates and social movements can activate public opinion by drawing attention to social problems (e.g., direct action protest, litigation, and canvassing) (McAdam, 1996), and they can frame those problems through mass media to reach the general population and try to control a narrative (Carroll and Ratner, 1999; Gamson and Wolfsfeld, 1993; Ryan 1991). Framing can facilitate how individuals evaluate social groups (Gamson and Modigliani, 1989).
For example, Brewer (2007) found that the lesbian and gay rights movement in the 1990s and early 2000s was framed around either egalitarianism or moral traditionalism, which worked to polarize people’s views. When HIV/AIDS was framed as a condition affecting social deviants, resources were slow to serve the communities most affected (Cohen, 1999). Early on, advocates in favor of marriage equality adopted a “rights and benefits frame,” which emphasized the rights denied to same-sex couples by denying them legal marriage recognition (Solomon, 2014; Stone, 2012). The rights frame was countered by a morality frame, which proved appealing to opponents of marriage equality (Hull, 2001). In the 2010s, there was a strategic shift in framing support for marriage equality to “love and commitment,” which emphasized the emotional foundations for why people choose to get married, including people in same-sex relationships (Harrison and Michelson, 2017). The love and commitment frame registered a stronger shift in support for LGBT rights than had the rights frame (Harrison and Michelson, 2017; Solomon, 2014). Efforts to reframe issues have profound consequences in public policies affecting SGD populations (Brewer, 2007).
Because framing and public perception are so important, the pursuit of public policies affecting SGD populations is constrained by prioritizing policies that are politically palatable and crafting respectable ways to present and discuss them (Cohen, 1999). For example, in the 1990s and 2000s the advocacy coalition in favor of LGBT rights avoided direct reference to
transgender people, rendering them invisible in its strategic communications (Stone, 2012). These tactics are tied to traditional electoral politics that primarily focus on the median or “middle” voter (Downs, 1957) and lead campaigns to pursue and present issues that are appealing to political moderates. Initiative and referendum campaigns on issues affecting SGD people tend to hone their political communications to that median (or “persuadable”) voter (Solomon, 2014; Stone, 2012), which can create conflict with advocates embracing a more transformative view of “queer politics” (Cohen, 1997) and others embracing a single-issue, pragmatic campaign (Stone, 2012).
The way the subject of sexual and gender diversity is addressed by advocacy coalitions may benefit the well-being of some individuals but fail to benefit others (Ward, 2008). The extent to which LGBT advocacy groups sustain normative practices and ideologies (Ward, 2008) may increase stigmatization of marginalized SGD groups by increasing minority stress (Cyrus, 2017) and decreasing community belonging (Barr, Budge, and Adelson, 2016). Some groups that have felt underrepresented by LGBT advocacy coalitions, such as transgender people and people of color, have challenged how the coalitions have approached diversity, which in many cases led to greater inclusion, representation, and greater outreach (Armstrong, 2002). However, challenges remain. In policy and legal discourses on LGBT rights, for example, Marcus (2015) found that bisexual people have effectively been erased. Even intersectional coalitions like the coordination between LGBTQ and immigrant rights advocacy organizations can advance some policy goals but may perpetuate a single-issue framework that further marginalizes immigrant LGBTQ people who do not meet a “respectable” image (Mayo-Adam, 2020).
Thus, the policy process creates an apparent tension between policy priorities and how inclusive those priorities are of the most vulnerable SGD populations (Hindman, 2017; Murib, 2017; Strolovitch, 2007, 2012). For some, the policies that may affect the well-being of SGD people most may be along other dimensions of marginalization (e.g., race, class, immigration status). As a result, the identity politics framework of LGBT advocacy can overlook policy proposals that can have the most impact on the well-being of multiply marginalized SGD people (Cohen, 1999; Mayo-Adam, 2020; Strolovitch, 2007). In addition, the policies that most affect multiply marginalized SGD populations (e.g., policies relating to sex work) may be avoided due to the political system and the politics of respectability.
The way groups are socially constructed affects whether and how public policies distribute costs and benefits. Schneider and Ingram (1993) noted that policy makers might design policies to create, sustain, or reduce disparities among numerous social strata. They also established that social
groups may be categorized into one of four typologies based on their degree of deservingness and political power: those who lack deservingness or power (deviants); those who are deserving but lack power (dependents); those who lack deservingness but have power (contenders); and those who are seen as both deserving of and having political power (advantaged). Just as changing frames can shift the way people come to understand issues, the social construction of groups can change over time. In their original categorization scheme, Schneider and Ingram (1993) categorized gay men and lesbian women as deviants, which aligns with research showing that lesbian, gay, and bisexual populations have lacked political power and have been stigmatized (Sherrill, 1996). More recently, people have perceived LGBT people as slightly more deserving of support but still lacking political power relative to other groups (Kreitzer and Smith, 2018). Policy makers and the public may support policies benefiting SGD populations based on how such populations are socially constructed. This perception varies geographically, temporally, and contextually.
Because they still make up a small percentage of the U.S. population, SGD people have had to depend on heterosexual and cisgender individuals to advance their interests in elections (Haider-Markel, 2010) and institutions (Hansen and Treul, 2015; Proctor, 2020). Given their high propensity to vote for the Democratic Party, lesbian and gay people may be considered to be electorally captured—when a political party does not seem compelled to respond to the demands of a constituent group because the group is unlikely to vote for the other political party (Smith, 2007)—though research is inconclusive (Bishin and Smith, 2013; McThomas and Buchanan, 2012). Direct democracy and electoral politics also mean that the attitudes of the general public, both directly and indirectly, affect policies pertaining to the well-being of SGD populations. The frequent use of ballot initiatives and referendums in the passage of state and local policies affecting SGD populations directly involves the attitudes of voters in policy making (Stone, 2012), and it is far more likely than other approaches to position LGBT rights on the losing end of policy debates (Haider-Markel, Querze, and Lindaman, 2007; Lewis, 2019; Stone, 2012).
Public Opinion and Public Policy
Although there is a strong correlation between public opinion on specific gay and transgender rights and whether public policies exist on those specific issues, studies find policies are sometimes out of step with the majority opinion (Flores, Herman, and Mallory, 2015; Lax and Phillips, 2009; Lax and Phillips, 2012). On many issues affecting SGD populations, there is a “democratic deficit,” which means that a majority view is not reflected in public policy; in such a situation, a super-majority is needed (Flores,
Herman, and Mallory, 2015; Krimmel, Lax, and Phillips, 2016; Lax and Phillips, 2009). One source of this difference may be that elected officials, particularly Republican officials, frequently overestimate how conservative their constituents are (Broockman and Skovron, 2018; Krimmel, Lax, and Phillips, 2016). Although policy makers are more likely to vote for gay rights when their constituents include a relatively larger share of same-sex couples (Bishin, 2009; Bishin and Smith, 2013), this effect may be conditioned by local acceptance of such rights (Hansen and Treul, 2015).
Changing Public Attitudes
Because public opinion affects both law and policy, social movements engage in policy and legal strategies to try to affect the hearts and minds of the general public. In addition to issue framing and strategic communications (Solomon, 2014; Stone, 2012), advocates and academics have examined various strategies to change public opinion to be more favorable to SGD populations. This section reviews some of those strategies. At times, these strategies have been developed by advocacy organizations who recruit academics to determine through rigorous experimental and quasi-experimental designs whether their tactics are effective.
Using a canvassing strategy to have face-to-face conversations with people about LGBT rights (Lempinen, 2020), Broockman and Kalla (2016) found in a field experiment that having these conversations about transgender people and having people imagine themselves in the shoes of transgender people—a process known as perspective taking—can reduce transphobia and make people more resistant to arguments opposing the inclusion of gender identity in public accommodations policies. Kalla and Broockman (2020) further found that in-depth conversations between canvassers and individuals are effective when individuals are asked about their own narratives, but ineffective when the canvasser provides arguments for why the individual should support an issue.
In a survey experiment, Flores and colleagues (Flores, Hatzenbuehler, and Gates, 2018; Flores et al., 2018) found that introducing the concept of transgender to people and providing them faces of transgender people can reduce transphobia, thereby potentially increasing support for transgender rights. Harrison and Michelson (2017) showed through a series of experiments that priming a shared identity unrelated to sexual orientation or gender identity (e.g., a sports fan identity) and then emphasizing support for LGBT rights can persuade people to be more supportive of LGBT rights. Michelson and Harrison (2020) showed through a series of experiments that reminding people that they are moral individuals who want do “the right thing” can increase their expressed support for transgender people and rights.
Experimental, quasi-experimental, and observational studies also found that the presence of LGBT characters in mass media can reduce prejudice toward LGBT people (Billard, 2019; Garretson, 2014, 2015, 2018; Schiappa, Gregg, and Hewes, 2005, 2006). These effects are generally explained by Allport’s (1954) contact hypothesis, which states that interacting with members of social outgroups can result in prejudice reduction and notes the various ways contact can occur in a mediated fashion, such as through mass media (Schiappa, Gregg, and Hewes, 2005). Garretson (2018) showed that social movement activism rooted in ACT UP eventually led to mass media and entertainment media representing SGD populations. Such representation may be one key driver of the mass opinion change that shifted favorably toward lesbian women and gay men in the United States (Garretson, 2018). Thus, activism and social movement organizing played a role in mass opinion change.
Public Policy Adoption and Diffusion
The presence of SGD elected officials affects the adoption of public policies that advance SGD rights. Haider-Markel (2010) traced the difficulties and accomplishments of “out” gay and lesbian candidates and elected officials and found that gay and lesbian elected officials can translate their descriptive diversity into substantive policies. Reynolds (2013) showed that countries with more out LGBT legislators have more SGD-inclusive policies, and Reynolds (2018) emphasized the work done by openly LGBT legislators in building legislative coalitions to advance policies inclusive of SGD populations. This area of research is nascent, particularly because of the slowly growing number of self-identified SGD elected officials since Harvey Milk won elected office in San Francisco in 1977 and Barney Frank came out as the first out gay congressman in 1987. The first out transgender elected official in a U.S. state legislature, Danica Roem, was elected in 2017 in Virginia.
In 2020, 843 self-identified SGD people held elected office in the United States (Victory Institute, 2020), a noticeable but small minority of the 519,682 total elected officials in the country (Lawless, 2012). Of the 843 holding office, approximately 39 identified their gender as transgender, gender-nonconforming, genderqueer, Two Spirit, or intersex; 458 as gay; 252 as lesbian; 52 as bisexual; 41 as queer; and 11 as pansexual (Victory Institute, 2020).1 “Out” LGBTQ elected officials often engage in discussions and work on legislation to advance policies that are inclusive of SGD populations (Haider-Markel, 2010; Reynolds, 2018).
Racially and ethnically diverse elected officials have formed coalitions to further advance policies, with some of those policies favorable
1 Numeric totals converted from percentages.
to SGD communities. These elected officials perceive an intersectional linked fate in which several policy issues cross-cut numerous groups (Tyson, 2016). For example, homeless youth issues intersect with race, class, sexual orientation, and gender identity, such that furthering policies to deal with homeless youth requires a diverse coalition of policy makers. In Congress, this coalition involves members of numerous identity-based caucuses (e.g., the LGBT Equality Caucus and the Congressional Hispanic Caucus). However, the identity politics framework of the LGBT advocacy coalition may make it more difficult to further policies that might benefit multiply marginalized SGD people (Strolovitch, 2007), which may limit policy innovation.
New policies tend to spread at both state and local levels, making it more likely that they are adopted in other locations (Berry and Berry, 2014). Such horizontal diffusion results in states and localities adopting policies similar to their neighbors, which occurred with such innovations as gender identity nondiscrimination protections (Sellers and Colvin, 2014). Innovations can be influenced by a number of factors, including the characteristics of local areas (Colvin, 2007; Taylor et al., 2014), policies in nearby states (Taylor et al., 2012), partisan control of lawmaking bodies (Lewis et al., 2014), and the capacity of local advocacy organizations (Taylor et al., 2018).
Model policies can also shape state or local law through vertical diffusion. For example, the Centers for Disease Control and Prevention has influenced state laws regarding updating birth certificates for transgender people (Taylor, Tadlock, and Poggione, 2013) and policies relevant to HIV (Rugg et al., 1999). Another form of vertical diffusion and innovation is the use of state preemption (Movement Advancement Project, 2018). Although each state constitution differs, local governments have limited powers and are subject to state laws that can further preempt their legislative authority. As a result, as policies change locally, countermovement organizations have sought legislation that removes local authority in certain fields, including anti-discrimination laws (Gossett, 1999; Movement Advancement Project, 2018).
More inclusive laws and policies are perceived as a signal that society has changed to be less stigmatizing to SGD populations (Andersen, 2017; Valelly, 2012). Just as advocates seek to win over the hearts and minds of the general public in the pursuit of policy or legal change, once they achieve policy changes, the public may respond in different ways. A pro-rights policy change has the capacity to produce both backlash or further positive change for SGD populations (Egan, Persily, and Wallsten, 2008), though recent empirical research tends to show mass attitudes become more favorable of SGD populations following adoption of pro-rights laws (Flores and Barclay, 2016; Ofosu et al., 2018; Tankard and Paluck, 2017). Sometimes
legal inclusion produces opinion backlash. National public support for legalization of same-sex marriage and anti-sodomy laws dropped following Lawrence v. Texas in 2003 (Egan, Persily, and Wallsten, 2008), which decriminalized consensual same-sex sexual acts. Ofosu and colleagues (2018) found that when marriage equality was introduced federally, residents of states that did not yet legally recognize marriages for same-sex couples had increases in implicit and explicit antigay bias, suggesting a backlash to federal policy change.
Backlash may follow adoption of inclusive policies that are new to the general public, but the public’s response may be different when policies become more familiar. For example, Barclay and Flores (2017) found that increased public familiarity with debates over marriage equality increased support for legalization of same-sex marriage, even if the particular dispute resulted in an exclusionary law.
There are intricate connections among social movements, the public policy process, and changing public opinion. Public policy and public opinion represent structures that establish the overall context for SGD populations. Social movements and advocacy organizations represent the ongoing struggle of SGD people to change those structures to improve their well-being. However, those structures are resistant to change, greatly affecting the well-being of SGD populations.
As discussed in Chapter 2, stigma is conceptualized as a multilevel construct (Link and Phelan, 2001), ranging from individual (e.g., self-stigma) and interpersonal processes (e.g., discriminatory treatment) to structural factors (e.g., laws and policies, institutional practices). Until recently, the vast majority of research on stigma had been directed at the individual and interpersonal levels (Major and O’Brien, 2005), despite the acknowledgment by researchers that structural forms of stigma were prevalent and likely played a significant role in shaping the lives of the stigmatized (Corrigan, Markowitz, and Watson, 2004; Corrigan et al., 2005; Link and Phelan, 2001). In the past decade, researchers have begun to address this gap, and research as it specifically relates to SGD populations has proliferated since the Institute of Medicine (2011) report.
In this section we summarize the emerging literature on structural stigma and the well-being of SGD populations, organized around four issues: measurement approaches used to study structural stigma; an evaluation of the evidence on the consequences of structural stigma for the well-being of SGD populations; the challenge of establishing causal inferences regarding the effects of structural stigma on adverse outcomes among SGD populations; and future directions to advance this emerging literature.
The measures used to study structural stigma have tended to follow one of three approaches: legal and policy analysis, aggregated measures of social attitudes, and composite indicators. In legal and policy analysis, the content of laws or policies (whether at the country, state, or municipal level) is coded to determine the presence of structural stigma in institutions (Corrigan et al., 2005). The main advantage of this approach is that it relies on objective data sources to code the policies; the primary limitation is that such analyses often do not capture the unwritten customs or procedures that undergird informal institutional practices (Livingston, 2013).
In the second approach, aggregated measures, researchers obtain data on individuals’ attitudes toward members of stigmatized groups and aggregate them to the community level (defined at various geographic scales, such as counties), so that the level of stigma can be compared across communities. This approach has been used to study structural forms of stigma related to mental illness (Evans-Lacko et al., 2012), sexual orientation (Hatzenbuehler, Flores, and Gates, 2017), and HIV/AIDS (Miller et al., 2011). A methodological strength of this approach is that members of stigmatized groups are not asked about their perceptions of community attitudes; instead, the community attitudes are derived from residents’ own attitudes.
This approach overcomes same-source bias, which can introduce spurious results when the independent and dependent variables are measured with the same method (Diez Roux, 2007). However, this approach can underestimate levels of structural stigma because self-reported attitudes toward stigmatized groups may be subject to social desirability biases (Livingston, 2013). To address this limitation, researchers have begun to use alternative approaches to capture attitudes that do not rely on self-reported measures. These alternative approaches include measures of implicit attitudes that are assessed with response latencies on computerized tasks, such as the Implicit Association Test (Leitner et al., 2016); aggregation of Google searches of racial epithets (Chae et al., 2015); and objective media market data on exposure to thousands of television campaign ads for and against a topic, such as same-sex marriage (Flores, Hatzenbuehler, and Gates, 2018).
These first two approaches measure a single aspect of structural stigma (i.e., laws, policies, or social attitudes), which may be appropriate for research questions that seek to evaluate which individual components of structural stigma are most robustly associated with the well-being of SGD populations. Under some circumstances, however, it is desirable to develop comprehensive measures of structural stigma that tap into shared variance in order to eliminate or minimize unique variance (e.g., unmeasured variables that reflect constructs other than structural stigma), especially given the high correlation among different components of structural stigma.
Some studies (Hatzenbuehler, 2011; Hatzenbuehler and McLaughlin, 2014; Pachankis et al., 2015) have begun to develop these more comprehensive measures of structural stigma that capture its multiple components (e.g., laws, institutional practices, social norms). This approach reduces measurement error, thereby increasing both construct and statistical validity.
Review of Research
This section reviews and provides illustrative examples of studies of the effects of structural stigma on the well-being of SGD populations, organized by kind of study: cross-sectional, longitudinal, quasi-experimental, field, and laboratory. Table 6-1 summarizes these research examples.
Much of the work on structural stigma and SGD populations began with cross-sectional, observational designs in order to establish whether structural stigma was associated with health inequalities. In an early example of this work, Hatzenbuehler, Keyes, and Hasin (2009) coded all 50 states for the presence or absence of hate crime statutes and employment nondiscrimination policies that included sexual orientation as a protected class (the measure of structural stigma). They then linked this policy information to individual-level data on mental health and sexual orientation from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a nationally representative health survey of U.S. adults. They found that sexual orientation disparities in psychiatric morbidity were more pronounced in states that measured high in structural stigma than in states that measured low in structural stigma. For instance, LGB adults who lived in states with no protective policies were nearly 2.5 times more likely to have dysthymia (a mood disorder) than were heterosexuals in those same states, controlling for established risk factors. In contrast, there were no disparities in dysthymia by sexual orientation in states with protective policies (Hatzenbuehler, Keyes, and Hasin, 2009).
SGD populations are not passive victims as they experience structural forms of stigma, but instead they engage in a variety of coping responses that buffer the negative effects of structural stigma and lead to positive psychosocial outcomes. Retrospective cross-sectional studies of LGB respondents have revealed sources of resiliency associated with campaign ballot initiatives, including an enhanced sense of personal and communal efficacy, experiences of personal growth (e.g., having a greater understanding of how prejudice affects their lives), and support from certain heterosexual allies; these factors helped to minimize feelings of isolation and powerlessness (Rostosky et al., 2010; Russell and Richards, 2003).
TABLE 6-1 Studies Examining Structural Stigma and Well-Being among SGD Populations
|Design||Measure of Stigma|
|Composite variable of state laws and attitudes toward homosexuality|
|Five legislative protections for LGB status at the country level: (1) recognition of same-sex relationships; (2) possibility of same-sex marriage; (3) possibility of same-sex adoption; (4) opportunity to serve openly as gay in the military; and (5) the presence of a legal framework to address all anti-gay discrimination|
|Composite variable of two state laws: hate crimes and employment nondiscrimination acts|
|Constitutional amendments banning same-sex marriage|
|Voter referendum on sexual orientation-based discrimination|
|Voter referendum on same-sex marriage (Proposition 8)|
|Prevalence of school districts whose anti-bullying policies include sexual orientation as an enumerated class|
|Composite variable of four factors: (1) density of same-sex couples; (2) proportion of gay-straight alliances in public high schools; (3) five policies related to sexual orientation discrimination (e.g., same-sex marriage bans, employment nondiscrimination acts that included sexual orientation); and (4) public opinion toward LGB-related policies (e.g., same-sex adoption, public accommodations)|
|Lesbian, gay, bisexual, and transgender assault hate crimes obtained from police records|
|Tobacco and alcohol use||Nonprobability sample of young adult sexual minority men (N = 119)||Pachankis, Hatzenbuehler, and Starks (2014)|
|Internalized homonegativity||Nonprobability sample of sexual minority men from 38 European countries in the European Men Who Have Sex with Men Internet Survey (N = 144,177)||Berg et al. (2013)|
|Psychiatric disorders||Nationally representative sample of non-institutionalized adults from the National Epidemiologic Survey on Alcohol and Related Conditions (N = 577 LGB respondents)||Hatzenbuehler, Keyes, and Hasin (2009)|
|Psychological distress (negative affect, stress, depressive symptoms), minority stress experiences, political participation||Nonprobability sample of LGB adults (N = 1,552)||Rostosky et al. (2010)|
|Stressors and resilience factors||Nonprobability sample of LGB adults (N = 316)||Russell and Richards (2003)|
|Affect, social relationships, support and conflict||Nonprobability sample of LGB adults (N = 354)||Maisel and Fingerhut (2011)|
|Suicide attempts||Population-based sample of youth in 11th grade from the Oregon Healthy Teens Survey (N = 1,413 LGB respondents)||Hatzenbuehler and Keyes (2013)|
|Suicide attempts, tobacco use||Population-based sample of youth in 11th grade from the Oregon Healthy Teens Survey (N = 1,413 LGB respondents)||Hatzenbuehler, (2011); Hatzenbuehler, Wieringa, and Keyes, (2011)|
|Suicide ideation or attempts, illicit drug use, bullying||Population-based sample of public high school students from the Boston Youth Survey Geospatial Dataset (N = 102 sexual minority youth)||Duncan and Hatzenbuehler (2014); Duncan, Hatzenbuehler, and Johnson (2014); Hatzenbuehler, Duncan, and Johnson (2015)|
TABLE 6-1 Continued
|Design||Measure of Stigma|
|Composite indicator of five factors of school climate: (1) have a gay-straight alliance and safe space for LGBTQ youth; (2) provide curricula on health matters relevant to LGBTQ youths (e.g., HIV); (3) prohibit harassment based on sexual orientation or gender identity; (4) encourage staff to attend trainings on creating supportive environments for LGBTQ youths; and (5) facilitate access to providers off school property that provide health and other services specifically targeted to LGBTQ youths (from School Health Profile Data of the Centers for Disease Control and Prevention)|
|Composite measure of country-level policies related to sexual orientation and aggregated social attitudes toward homosexuality held by the citizens of each country|
|Composite measure of country-level policies related to sexual orientation and aggregated social attitudes toward homosexuality held by the citizens of each country|
|Voter referendum on same-sex marriage|
|Aggregate measure of community attitudes on same-sex marriage|
|Sexual orientation enumeration in state anti-bullying statutes|
|Religious Freedom Restoration Acts|
|Longitudinal panel||Composite variable of (1) density of same-sex couples; (2) proportion of gay-straight alliances in public high schools; (3) five policies related to sexual orientation discrimination (e.g., same-sex marriage bans, employment nondiscrimination acts that included sexual orientation); and (4) public opinion toward LGB-related policies (e.g., same-sex adoption, public accommodations)|
|Suicide ideation, plan, and attempts||Population-based sample of public high school students in 8 states and cities from the Youth Risk Behavior Surveillance System (N = 2,782 LGB youth)||Hatzenbuehler et al. (2014a)|
|Concealment||Nonprobability sample of sexual minority men from 38 European countries in the European Men Who Have Sex with Men Internet Survey (N = 174,209)||Pachankis et al. (2015)|
|Life satisfaction, concealment, discrimination, and victimization||Nonprobability sample of sexual minorities from 28 countries participating in the European Union Lesbian, Gay, Bisexual, and Transgender survey (N = 85,582)||Pachankis and BrÃ¤nstrÃ¶m (2018)|
|Life satisfaction, mental health, overall health, perceived social support||Probability-based sample of adults from the Household, Income, and Labour Dynamics in Australia Survey (N = 554 LGB respondents)||Perales and Todd (2018)|
|Self-rated health, tobacco use||Population-based sample from the Gallup Daily Tracking survey (N = 11,949 LGBT respondents)||Hatzenbuehler, Flores, and Gates (2017)|
|Bullying, suicidal ideation and attempts in the past 12 months||Population-based sample of youth from the Youth Risk Behavior Surveillance System (N = 2,000 sexual minority youth)||Meyer et al. (2019)|
|Unhealthy days in the past 30 days||Probability sample of adults from the Behavior Risk Factor Surveillance System (N = 4,911 sexual minorities)||Blosnich et al. (2018)|
|Cigarette smoking, illicit drug use||Nonprobability sample of youth from the Growing Up Today Study, a longitudinal cohort (N = 2,190 sexual minorities)||Hatzenbuehler et al., (2014b, 2015)|
TABLE 6-1 Continued
|Design||Measure of Stigma|
|Repeated crosssectional surveys linked prospectively to mortality data in the National Death Index||Aggregate measure of community attitudes on same-sex sexuality|
|Daily diary study||Voter referendum on same-sex marriage in 4 states|
|Repeated cross-section||Composite measure of laws and aggregated community attitudes in Sweden|
|Longitudinal panel||Constitutional amendments banning same-sex marriage|
|Longitudinal panel||Massachusetts Supreme Court decision on constitutionality of same-sex marriage|
|Longitudinal panel||Illinois law legalizing civil unions (Religious Freedom Protection and Civil Union Act)|
|Interrupted time series||Voter referendum on same-sex marriage (“Proposition 8”)|
|Repeated crosssectional samples with fixed effects||Same-sex marriage policies|
|Repeated crosssectional samples with fixed effects||State laws permitting the denial of services to same-sex couples (“religious exemption laws”)|
|All-cause mortality||Probability-based sample from the General Social Survey (N = 1,524 individuals reporting same-sex sexual partners)||Hatzenbuehler et al. (2019a)|
|Psychological and relational well-being||Nonprobability sample of 62 samesex couples who completed a baseline survey and 10 daily diary reports during the month before the election||Frost and Fingerhut (2016)|
|Psychological distress||Population-based sample of Swedish adults from the Swedish National Public Health Survey (N = 565 LGB respondents)||Hatzenbuehler, BrÃ¤nstrÃ¶m, and Pachankis (2018)|
|Psychiatric disorders in the past year||Nationally representative sample of non-institutionalized U.S. adults from the National Epidemiologic Survey on Alcohol and Related Conditions (N = 577 LGB respondents)||Hatzenbuehler et al. (2012)|
|Health care utilization and expenditures||Nonprobability data from a health clinic serving LGBT individuals (N = 1,211 sexual minority male patients)||Hatzenbuehler et al. (2012)|
|Hazardous drinking, depressive symptoms, perceived discrimination, stigma consciousness||Nonprobability sample from the Chicago Health and Life Experiences of Women Study (N = 517 sexual minority women)||Everett, Hatzenbuehler, and Hughes (2016)|
|Homophobic bullying in the past year||Nonprobability sample from the California Healthy Kids Survey (N = 4,977,557 children)||Hatzenbuehler et al. (2019b)|
|Suicide attempts in the past year||Population-based data from the Youth Risk Behavior Surveillance System (N = 231,413)||Raifman et al. (2017)|
|Poor mental health in the past 30 days||Population-based data from the Behavioral Risk Factor Surveillance System (N = 4,656 LGB and “unsure” respondents)||Raifman et al. (2018)|
TABLE 6-1 Continued
|Design||Measure of Stigma|
|Repeated crosssectional samples with fixed effects||Three state policies: (1) same-sex partner recognition, (2) constitutional amendments banning same-sex marriage, and (3) employment nondiscrimination and hate crime laws|
|Cross-sectional analysis, examining “spillover” into states where “treated” individuals were accidentally exposed to the campaign ads||Media market data of television ads during a voter referendum on same-sex marriage|
|Audit experiment||Legal protections related to employment discrimination|
|Composite variable of (1) density of same-sex couples; (2) proportion of gay-straight alliances in public high schools; (3) five policies related to sexual orientation discrimination (e.g., same-sex marriage bans, employment non-discrimination acts that included sexual orientation); and (4) public opinion toward LGB-related policies (e.g., same-sex adoption, public accommodations)|
*NOTE: Studies on presence of gay-straight alliances in schools are discussed in Chapter 10.
|Hate crimes based on sexual orientation||Federal Bureau of Investigationâ€™s Uniform Crime Reporting Program on hate crimes related to sexual orientation||Levy and Levy (2017)|
|Psychological distress, negative affect||Probability-based sample of LGBT adults (N = 939)||Flores, Hatzenbuehler, and Gates (2018)|
|Employment discrimination (percentage of gay men who received a callback)||1,769 job postings in states; one resume in each pair was randomly assigned experience in a gay campus organization, and the other resume was assigned a control condition||Tilcsik (2011)|
|Physiological stress response, measured by cortisol||Nonprobability sample of LGB young adults (N = 74)||Hatzenbuehler and McLaughlin (2014)|
Although cross-sectional studies provide important insights into associations, prospective designs improve the ability to establish temporal ordering of the relationship between structural stigma and the well-being of SGD populations. Longitudinal designs involve an assessment of the same respondents over time. A typical longitudinal design involves panel or cohort studies, in which the same respondents are repeatedly assessed. Below, we describe three types of longitudinal designs that have been used: respondents followed over time, daily diary studies, and repeated cross-sectional samples that examine trends over time.
Respondents Followed over Time
Hatzenbuehler and colleagues (2014b, 2015) constructed a composite measure of structural stigma surrounding LGB youth, which included four items at the state level: density of same-sex couples, proportion of gay-straight alliances in public high schools, policies related to sexual orientation, and public opinion toward homosexuality (using aggregated responses from national polls). The researchers linked this information on state-level structural stigma to individual-level data on tobacco and illicit drug use from the Growing Up Today Study, a prospective cohort study of youth. They found that sexual minority youth living in states with low structural stigma were less likely to smoke over time than sexual minority youth in states with high structural stigma states, controlling for individual- and state-level confounders (Hatzenbuehler et al., 2014b).
Daily Diary Studies
Experience sampling methods (also known as ecological momentary assessments and daily diary studies) offer a number of methodological strengths, including capturing reported events and psychological reactions longitudinally in their natural context, thereby permitting the examination of person-by-situation interactions; reducing recall bias (because the approach minimizes the amount of time that elapses between an experience and the reporting of the experience); improving the validity of modeling within-individual changes (because of the much larger number of assessments that are possible with this design); and affording researchers the opportunity to examine the temporal sequence of events and to control for third variables by using individuals as their own controls, thereby improving causal inferences (Bolger, Davis, and Rafaeli, 2003).
Daily diary studies are increasingly being used to study structural stigma among SGD populations. For instance, Frost and Fingerhut (2016) used this design to obtain daily reports on health and stress exposure from 62 same-sex couples from four states in the month before state voting on same-sex marriage in voter referenda. Self-reported exposure to negative campaign messages was associated with increased negative affect, as well as with decreased positive affect and relationship satisfaction, controlling
for baseline measures of depression and daily fluctuations in general stress among both members of the couple. Thus, even though all four states voted in favor of same-sex marriage, the negative social environment created by public debates about the rights of SGD individuals affected the mental health of same-sex couples.
Repeated Cross-Sectional Samples
Repeated cross-sectional samples are used to examine trends over time. In one example of this approach, researchers used a population-based dataset in Sweden that has assessed sexual orientation and mental health every 5 years since 2005 (2005, 2010, 2015). Over this 10-year period, there were marked declines in structural forms of stigma, including changes in laws and policies that provided protections to sexual minorities, as well as declines in prejudicial attitudes towards homosexuality. These declines in structural stigma were associated with a significant reduction in the magnitude of the sexual orientation disparity in mental health: in 2005, gay men and lesbian women were nearly three times more likely to meet criteria for elevated psychological distress than heterosexual men and women, but in 2015 the sexual orientation disparity was eliminated (Hatzenbuehler, Bränström, and Pachankis, 2018). This finding is important because it suggests that sexual orientation disparities in mental health are responsive to changes in the social context.
Researchers have complemented observational designs through the use of several different methods, such as quasi-, or natural, experiments, which permit stronger inferences regarding the relationship between structural stigma and outcomes in well-being. Quasi-experiments are used in situations in which it is not possible or ethical to randomly assign individuals to a particular condition, as is the case in studying structural forms of stigma. Three types of quasi-experimental designs have been used: those that use longitudinal panel studies, those that use repeated cross-sectional samples, and those that use interrupted time-series designs.
Quasi-Experiments Using Longitudinal Panel Studies
In this approach, researchers use quasi-experiments to examine changes in health following changes in structural stigma (usually through a change in a social policy) among the same set of respondents who have been assessed both before and after the policy change. In one example of this work, Hatzenbuehler and colleagues (2010) took advantage of the fact that, leading up to and during the 2004 election, several states passed constitutional amendments banning same-sex marriage. These events occurred between two waves of data collection of NESARC. Respondents were first interviewed in 2001 and then reinterviewed in 2005, following the adoption of bans on same-sex marriage. LGB adults who lived in states that passed same-sex marriage bans
experienced a 37 percent increase in mood disorders, a 42 percent increase in alcohol use disorders, and a 248 percent increase in generalized anxiety disorder between the two waves (Hatzenbuehler et al., 2010). In contrast, LGB respondents in states that did not adopt such bans did not experience a significant increase in psychiatric disorders during the study period. The mental health of heterosexuals in states that adopted the bans was largely unchanged between the two waves.
Complementing this study, which suggests that implementing structural stigma through state laws may have negative mental health consequences for LGB populations, there is evidence that abolishing structural forms of stigma may improve their health. When Massachusetts became the first state to legalize same-sex marriage in 2003, researchers obtained data (from previously collected medical records) from a community-based health clinic in Massachusetts to examine the influence of the law on health care use and costs among sexual minority men. There was a 15 percent reduction in mental and medical health care utilization and costs among these men in the 12 months following the legalization of same-sex marriage, compared with the 12 months before (Hatzenbuehler et al., 2012).
Quasi-experimental designs cannot rule out the possibility that some other factor that occurred contemporaneously with the change in structural stigma affected the results. However, the plausibility of alternative factors can be evaluated by examining whether they occurred during the same time period and, if so, whether they could have contributed to the results. For example, in the aforementioned study by Hatzenbuehler and colleagues (2012), the researchers examined data from the Centers for Medicare & Medicaid Services to determine trends in health care costs during the study period, 2002–2004. These data revealed that health care costs in the general population of Massachusetts residents increased during the study period. This pattern was in the opposite direction of those observed in the study’s sample of sexual minority men, suggesting that external factors in the Massachusetts health care environment were unlikely to have influenced the results.
Quasi-Experiments Using Repeated Cross-Sectional Samples
A second quasi-experimental approach uses repeated cross-sectional samples with state fixed effects to examine the consequences of structural stigma for SGD populations. In this approach, the same respondents are not followed, as in the studies reviewed above; instead, different “snapshots” of a population are followed over time to determine whether changes in structural stigma affect outcomes in well-being.
2 Difference-in-difference-in-differences is a statistical technique that studies the status of a “treatment” group” and a “control group” before a treatment is administered, as well as studying the outcomes of each group after the treatment.
mental distress among LGB and heterosexual respondents in three states that implemented laws in 2015 denying public accommodations services to same-sex couples (treatment group) with changes in mental distress among LGB and heterosexual respondents in six geographically nearby states with similar demographics but without these laws (control group). Data on mental health and sexual orientation came from the Behavioral Risk Factor Surveillance System. The only group experiencing an increase in mental distress during this period was that of the sexual minorities living in states with the denial law. This increase was equivalent to a 46 percent relative increase in sexual minority adults experiencing mental distress in these states (Raifman et al., 2018). This study used state fixed effects, which controlled for baseline differences in rates of mental distress across states, and for time-invariant characteristics (e.g., political climate) that could have affected both the independent and dependent variables.
Levy and Levy (2017) used a similar quasi-experimental approach in a study looking at a different well-being outcome: hate crimes targeting LGBT populations. The authors used repeated cross-sectional data on hate crimes from the Federal Bureau of Investigation’s Uniform Crime Reporting Program, examining whether state laws (constitutional amendments banning same-sex marriage, same-sex partner recognition, employment nondiscrimination, and hate crime laws) were associated with reduced incidence of hate crimes against LGBT individuals. Results indicated that the presence of hate crime and employment nondiscrimination laws that include sexual orientation as a protected class resulted in a small but statistically reliable reduction in the incidence of hate crimes against LGBT populations. For instance, states instituting a nondiscrimination law had one fewer reported hate crime per 900,000 people during the year the policy was adopted and an additional one fewer reported crime per 1.2 million people in the following year (Levy and Levy, 2017).
Quasi-Experiments Using Interrupted Time Series
Another quasi-experimental approach is the use of interrupted time-series designs, a statistical tool used in nonexperimental data for assessing associations between policy or legislation and outcomes of interest. With a series of repeated observations, this approach compares the rates of a phenomenon before and after a policy or legislative change. Hatzenbuehler and colleagues (2019b) used this approach to examine the associations between a voter referendum that restricted marriage to heterosexuals in California (Proposition 8, in 2008) and homophobic bullying among youth. They strategically combined data from nearly 5 million youth in more than 5,000 schools across 14 school years, linked to statewide data on school gay-straight alliances, to determine whether rates of homophobic bullying increased as a result of the referendum. The interrupted time-series analyses found that the 2008–2009 academic year, during which Proposition 8 was passed, served as a turning
point in homophobic bullying (Hatzenbuehler et al., 2019b). Specifically, the rate of homophobic bullying increased and accelerated in the period prior to Proposition 8 and then gradually declined in the years following the vote. Specificity analyses showed that these trends were not observed among students who reported that they were bullied because of their race, ethnicity, religion, or gender, but not because of their sexual orientation. The analysis also showed that the presence of gay-straight alliances served as a protective factor specific to school contexts among LGBT youth; they were associated with a smaller increase in homophobic bullying during the pre-Proposition 8 period.
One of the strengths of field experiments is that they retain the internal validity of a traditional randomized experiment but improve external validity by examining stigma processes in “real-world” settings. One particular type of field experiment is the audit experiment, which has been used in several studies on discrimination. An innovative example of this approach was conducted by Tilcsik (2011), who explored discrimination based on sexual orientation in employment outcomes among men. The researcher submitted a pair of fictitious, but ostensibly real, resumes to job postings of white-collar, entry-level jobs in seven states that were chosen on the basis of whether they had employment nondiscrimination laws that included sexual orientation as a protected class. The sexual orientation of the applicant was randomly assigned to each pair before the resumes were sent: the sexual orientation of the apparent applicant was signaled through the applicant’s membership in a campus organization during college. Although the resumes differed slightly to avoid raising suspicion, there was no systematic relationship between resume quality and sexual orientation; as such, any difference that was observed in call-back rates (the dependent variable of interest) could be attributed to the sexual orientation of the applicant.
Gay men were approximately 40 percent less likely to be offered a job interview than similarly qualified heterosexual men, an effect that is similar to previous audit studies on Black-white disparities in employment outcomes (Tilcsik, 2011). However, there was also substantial variation in the level of hiring discrimination across the seven states. Specifically, rates of employment discrimination against gay men were higher in states that did not have employment nondiscrimination policies that protected gay men. Thus, this study provided experimental evidence not only that both interpersonal and structural discrimination influence employment outcomes, but also that these forms of discrimination interact to produce adverse employment outcomes for gay men.
The primary advantage of laboratory designs is that researchers can examine how structural stigma moderates responses to the same stimuli as measured in a controlled setting. In these studies, individuals are recruited on the basis of their prior exposure to structural stigma (high or low) and then are assigned to different conditions to examine how structural stigma influences their behavioral, psychosocial, and physiological responses.
In one example of this work, researchers recruited 74 LGB young adults who were raised in 24 different states as adolescents. The states differed widely in terms of structural stigma, which was coded on the basis of a composite measure that included, among other factors, state laws and attitudes (Hatzenbuehler and McLaughlin, 2014). All respondents were currently living in New York, a low structural stigma state. In order to examine how prior exposure to structural stigma during adolescence affected subsequent physiological stress responses during young adulthood, participants completed a validated laboratory stressor, the Trier Social Stress Test (TSST), and neuroendocrine measures were collected. LGB young adults who were raised in high structural stigma states as adolescents evidenced a blunted cortisol response following the TSST compared with LGB young adults raised in low structural stigma states. This blunted cortisol response has been similarly documented in other groups that have experienced chronic stressors, including children exposed to childhood maltreatment (Gunnar et al., 2009). Thus, these results suggest that the stress of growing up in high structural stigma environments may exert biological consequences that are similar to those from other chronic life stressors.
Establishing Causal Inferences
Researchers have used several different approaches to achieve the strongest inferences possible regarding the effects of structural stigma on the well-being of SGD populations. Below, we briefly discuss six of these strategies.
First, as shown in the studies above, researchers have used a multimeasure, multimethod, multi-outcome approach to examine the consequences of structural stigma for SGD populations. This is an established approach to assessing validity; when convergence is demonstrated, one can be relatively confident that the results are not spuriously confounded by particular methods, measures, or outcomes (Campbell and Fiske, 1959). Relatedly, the findings of structural stigma have been documented across multiple research groups using different methods, samples, and measures, providing further support for the robustness of these findings.
Second, researchers have explored whether the effects of structural stigma are apparent among SGD populations and not among cisgender, heterosexual populations. When associations between structural stigma and well-being outcomes are observed only among members of the stigmatized group, it is likely that this result is due to structural stigma itself rather than to factors that may be associated with it (e.g., better economic conditions). Studies have generally documented this kind of specificity (e.g., Blosnich et al., 2018; Duncan and Hatzenbuehler, 2014; Hatzenbuehler and Keyes, 2013; Hatzenbuehler et al., 2010, 2014a; Raifman et al., 2018), or they have shown that the association between structural stigma and well-being outcomes is more pronounced for SGD populations than for non-SGD populations (e.g., Hatzenbuehler, Bränström, and Pachankis, 2018; Raifman et al., 2017); however, there are some studies that have shown that structural stigma is associated with health outcomes among both stigmatized and non-stigmatized groups (e.g., Hatzenbuehler, 2011; Meyer et al., 2019).
A third approach for improving causal inferences comes through the direct assessment of plausible alternative explanations. One alternative explanation for the relationship between structural stigma and health is that people with better health move away from policy regimes and attitudinal contexts that disadvantage them, leaving unhealthy respondents behind. If this occurs, differential selection by health status could contribute to the observed association between structural stigma and health. Studies have begun to address this possibility and have thus far not found strong evidence for this selection hypothesis. For instance, using data from the General Social Survey (2008–2014), Hatzenbuehler, Flores, and Gates (2017) found that among participants who self-reported fair or poor health, sexual minorities were more likely to have moved out of state than heterosexuals (43 percent and 37 percent, respectively), the opposite of what the social selection hypothesis would predict. This finding indicates that differential selection by health status is unlikely to be responsible for the observed association between structural stigma and well-being outcomes among SGD populations.
Fourth, researchers have controlled for a variety of potential individual- and structural-level confounders to rule out spurious associations between structural stigma and well-being. By and large, results remain robust to the inclusion of these confounders. In addition, researchers have used fixed effects analyses (e.g., Levy and Levy, 2017; Raifman et al., 2017, 2018), which control for baseline differences across geographic units (e.g., states) in the analysis, as well as for time-invariant characteristics that could affect both structural stigma and health outcomes.
Fifth, researchers have conducted falsification tests that show structural stigma does not predict outcomes it theoretically should not influence,
Finally, one potential methodological limitation that can affect internal validity (and therefore causal inferences) is expectancy effects, meaning that researchers’ biases in obtaining support for their hypotheses about the effects of structural stigma may influence their coding behaviors of the independent (i.e., structural stigma) or dependent (e.g., health) variables. The studies discussed above have largely minimized the threat of expectancy effects because of the methodological approaches that were used. Specifically, researchers first obtained data on structural stigma, typically from external sources. Data on policies were either collected by outside groups that use legal and policy experts to independently code the policies or were obtained from publicly available data sources whose accuracy can be objectively verified by comparisons with legislative records (Krieger et al., 2013; Pachankis et al., 2015). In studies that used data on aggregated social attitudes as the indicator of structural stigma, researchers usually obtained these data from publicly available data sources (e.g., the General Social Survey) rather than collecting the data themselves, thereby reducing the likelihood of expectancy effects. Information on structural stigma was then linked to datasets in which the outcomes were previously collected by other researchers who were, by definition, blind to study hypotheses (because the data were not originally collected for the purposes of studying structural stigma). This approach further minimizes the threat of expectancy effects.
Advancing Research on Structural Stigma
Although research has advanced understanding of how structural stigma affects the well-being of SGD populations, several gaps remain. In this section we review these gaps, as well as needed data. In addition, we identify key barriers that have hindered work in this area and offer suggestions for addressing these data needs in order to advance the evidence base.
For research that is needed to advance the emerging field of structural stigma and SGD well-being, we focus on five areas: mediating pathways, expanding measurement of structural stigma, life course and developmental trajectories, structural stigma relevant to individuals with diverse genders and sexualities, and intersectionality.
Although most research to date has focused on main effect relations between structural stigma and well-being outcomes among SGD populations, research has begun to identify potential mechanisms explaining this association. This work has largely focused on two
primary pathways: stress mechanisms and psychosocial mechanisms. Evidence for a stress pathway comes from both direct tests—e.g., research indicating that structural stigma is associated with dysregulated physiological stress responses among LGB young adults (Hatzenbuehler and McLaughlin, 2014)—and from indirect tests (Hatzenbuehler et al., 2012).
The second potential pathway involves psychosocial mechanisms, such as social isolation and maladaptive forms of emotion regulation, which have been shown to mediate the health effects of individual and interpersonal forms of stigma (Hatzenbuehler, 2009; Hatzenbuehler, Phelan, and Link, 2013). For example, LGB respondents who live in countries with higher levels of structural stigma report greater identity concealment, which in turn predicts lower life satisfaction (Pachankis and Bränström, 2018). In addition, in Australia, LGB respondents who lived in communities with higher levels of structural stigma (i.e., constituencies with higher proportions of residents voting against same-sex marriage) reported less social support, which in turn was associated with worse life satisfaction, as well as poorer mental health and overall health (Perales and Todd, 2018).
These initial findings have been important, but research is needed to identify additional mediating pathways—including material (e.g., income, educational attainment), psychosocial (e.g., emotion regulation), and biological (e.g., inflammation) pathways. This topic represents an important avenue for future inquiry and can inform potential targets for preventive interventions to reduce the negative consequences of structural stigma for SGD well-being.
Expanding Measurement of Structural Stigma
As reviewed above, studies have measured structural stigma in a variety of ways. While this diversity of measurement represents a methodological strength, the work has thus far focused on a limited set of social institutions (largely, state laws and aggregated social norms). Research that expands the measurement of structural stigma to include social institutions that have thus far not received as much empirical attention in the literature is needed: those institutions include health care settings, policing, and the criminal justice and juvenile justice systems. Research is also needed that more comprehensively examines the implementation of social policies relevant to SGD populations, as well as the social, economic, and political factors that affect variability in implementation and enforcement.
In addition, the advent of “big data” sources—such as Google searches, social media (e.g., Twitter feeds), and exposure to various media content (e.g., television ads)—offers new ways of measuring the presence and scope of structural stigma, as reflected in aggregated social norms and attitudes, that affect SGD populations. To date, studies are only beginning to use these big data sources to study structural stigma as it relates to diverse sexual orientations and gender identities (Flores et al., 2018), and compre-
hensive information on the psychometric properties of these data sources does not yet exist. This area represents an important avenue for future research on structural stigma.
Life Course and Developmental Trajectories
Research on structural stigma and the well-being of SGD people has been conducted among adolescents (Duncan and Hatzenbuehler, 2014; Hatzenbuehler and Keyes, 2013; Raifman et al., 2017), young adults (Hatzenbuehler and McLaughlin, 2014; Pachankis, Hatzenbuehler, and Starks, 2014), and adults (Hatzenbuehler et al., 2010, 2012; Pachankis and Bränström, 2018; Perales and Todd, 2018; Raifman et al., 2018). However, most research examines exposure to structural stigma at a single point in development, and attention to developmental timing and chronicity of exposure to structural stigma has been relatively lacking. Thus, although it is clear that structural stigma matters for the health and well-being of SGD populations, how this develops over the life course is not well understood. Future research should therefore consider how structural stigma unfolds using life course and developmental trajectories in order to advance this line of work. Researchers could also study dose–response relationships between length of exposure to structural stigma over a person’s life course and adverse outcomes among SGD populations.
Structural Stigma Relevant to Individuals of Diverse Genders and Sexualities
Most research has examined structural stigma related to sexual orientation, with a particular focus on same-sex sexuality. Comparatively fewer studies have been conducted about structural stigma related to other sexual orientations, such as bisexuality, as well as to individuals with intersex traits. In addition, there is a dearth of research on structural stigma related to gender identity (for an exception, see Perez-Brumer et al., 2015), despite acknowledgment that transgender populations confront several sources of structural stigma (Hughto, Reisner, and Pachankis, 2015).
There are at least two reasons for this relative dearth of research. One is the lack of data structures that include measures of diverse genders and sexualities and that sample respondents across multiple contexts that vary in the level of structural stigma against these groups. Another reason is the lack of measurement development regarding structural forms that may be unique to specific groups of SGD populations. For instance, prejudice related to bisexuality involves different stereotypic content than prejudice related to homosexuality (Dodge et al., 2016; Worthen, 2013), indicating the importance of developing new measures that capture the facets of structural stigma and prejudice that are distinct to bisexuality, as well as to other diverse sexualities and genders.
Research to date has largely explored structural forms of stigma that are shared by LGBT populations related to their sexual orientation. This work is important, but it has tended to obscure the fact that
LGBT individuals have other identities that are relevant to their well-being, including race, ethnicity, gender, and socioeconomic status (for a notable exception, see Everett, Hatzenbuehler, and Hughes, 2016). Thus, how structural forms of stigma across multiple axes of social stratification interact to confer risk for, or protection against, adverse outcomes among SGD people with intersecting identities is not well understood. Recent research has begun to address this gap, using novel approaches to testing intersectionality (Pachankis et al., 2017), but more work is needed.
The most widely used approaches for studying structural stigma and well-being among SGD populations include multilevel or population-average models that provide an estimate of the effect of structural stigma on well-being outcomes, net of individual and contextual factors (Hatzenbuehler, 2017). In order to conduct these studies, researchers require datasets with the four variables (1) demographic measures of sexual orientation and gender identity (at the individual level); (2) covariates to control for potential confounders and plausible alternative explanations (measured at the individual and contextual levels); (3) dependent variables (e.g., health outcomes or other indicators of social and economic well-being, measured at the individual level); and (4) geographic information on respondents’ residence (e.g., ZIP codes) that enables researchers to link structural stigma variables (i.e., the independent/predictor variable) to individual-level data.
This last point is particularly important, because without geographic measures of where respondents are located, it is not possible to examine the influence of structural stigma on SGD well-being. Currently, numerous datasets either do not provide this information on geographic residence or else release data at only one geographic level of analysis (e.g., state), which restricts researchers’ ability to examine structural forms of stigma across multiple geographic levels simultaneously (e.g., state, county, city, and school). This lack of data on geographic residence across different spaces in which SGD individuals live, work, and play has created a significant barrier to advancing the literature on structural stigma.
Another data and methodological challenge in conducting research on structural stigma is the lack of a centralized mechanism by which government or private actors initiate and track surveillance of laws and policies relevant to SGD populations and their enforcement (Blake and Hatzenbuehler, 2019). This hinders the ability of researchers to longitudinally track how laws and policies, as well as their enforcement (or lack thereof), affect the well-being of SGD populations.
There are numerous advocacy organizations devoted to the advancement of rights for SGD populations. The contemporary LGBT advocacy coalition has growing infrastructure and capacity, and hundreds of foundations and corporations have invested in issues addressing sexual and gender diversity. At the same time, however, there are organizations opposed to the advancement of rights for SGD populations that also try to control the policy agenda and reach the public through counter campaigns and social movements.
The way issues are communicated affects how people come to understand them. The strategic shift of a frame, as with marriage equality, for example—from an “egalitarian” movement to one that was centered on “love and commitment”—can cause a shift in support and have a profound effect on public policy. However, the pursuit of polices likely to garner public support may stigmatize or erase certain SGD groups, such as bisexual and transgender men and women.
Because SGD populations make up a small percentage of the U.S. population, they have had to depend on heterosexual and cisgender individuals to advance their interests in elections, which means that the attitudes of the general public both directly and indirectly affect public policies. Contextual factors, such as the geographic distribution of the population density of SGD people, can result in differences in levels of acceptance. Policy makers are more likely to vote for gay rights when their constituencies have a larger share of same-sex couples, though this may be conditioned by local attitudes.
The majority of U.S. adults support nondiscrimination protections for LGBT people in employment, public accommodations, and housing and support transgender people being able to serve openly in the military. The public is more divided on such issues as gender identity protections in public accommodations, such as public restrooms, and businesses’ right to deny services to LGBT people because of religious belief. Personalizing sexual and gender diverse people when placing them in context for poll respondents—i.e., highlighting a shared identity unrelated to sexual orientation or gender identity—can bolster support for LGBT rights.
The presence of sexual and gender diverse elected officials affects SGD public policy adoption. “Out” LGBT elected officials often work to advance policies that are inclusive of sexual and gender diverse populations, but they make up a small minority of all elected officials. Policies can diffuse horizontally, when states and localities adopt policies similar to neighboring legislations, or vertically, when national organizations effect changes to state laws or states do so to localities. More inclusive laws and policies are perceived as a signal that society has changed to be less stigmatizing of SGD populations.
The well-being of SGD populations is affected not only by legal and political institutions and public attitudes, but also by structural factors, including structural stigma. There is now a growing body of evidence that structural stigma affects the health and well-being of people of diverse sexualities and genders.
Research using multiple methods has documented associations between structural stigma and well-being. The multiple dimensions of well-being across which the effects of structural stigma can be found include mental health (e.g., psychiatric diagnoses, suicide attempts, psychological distress); physiological stress response (e.g., cortisol reactivity); victimization experiences (e.g., hate crimes, homophobic bullying); and employment (e.g., employment discrimination).
In looking at the effects of structural stigma, studies have begun identifying mediating pathways, such as stress and psychosocial mechanisms, but work is needed to understand whether other pathways (e.g., material and biological) underlie the established associations between structural stigma and the well-being of SGD people. Research is also need to expand beyond the study of large social institutions and federal and state policies to include less-studied institutions, such as health care settings and criminal justice systems.
Big data sources may also provide insight on the ways structural stigma affects diverse sexual orientations and gender identities. Research has been
conducted among adolescents, young adults, and adults, but it has not been conducted on how structural stigma develops and evolves over the life course. Furthermore, most structural stigma research has focused on gay men and lesbian women and has not considered intersectional characteristics, such as race, ethnicity, gender identity, and socioeconomic status, that are relevant to well-being. Also needed are studies that focus on less-represented SGD subgroups and consider the role of intersectionality in structural stigma. For this research, there are a number of data needs, including developing systems and methods that identify geographic indicators for SGD respondents (e.g., state or city of residence) and remove barriers in access to or use of such indicators in datasets.
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