This is an open access article distributed under the terms of the Creative Commons
Attribution License (Racism is a much more clandestine, much more hidden kind of phenomenon, but at the same time it's perhaps far more terrible than it's ever been.
Much progress has been made in the effort to reduce racism in the United States. Since the Civil Rights movement—which aimed to end racial segregation and discrimination against Black U.S. citizens—overt prejudice has declined in the U.S. (Brown, 2010). Despite this progress, modern racism now takes on more subtle forms, such as Whites opposing or resenting governmental programs designed to eliminate extant racial inequalities (Kinder & Sears, 1981). This symbolic racism refers to the “political role of Whites’ attitudes” (Sears, 1988, p. 54) and continues to drive inequalities between racial groups in the U.S. through policy preferences with racial implications (Kinder & Sears, 1981; Sears & Kinder, 1971; Tarman & Sears, 2005). Symbolic racism, “represents a form of resistance to change in the racial status quo based on moral feelings that Blacks violate such traditional U.S. values such as individualism and self-reliance, the work ethic, obedience, and discipline” (Kinder & Sears, 1981, p. 416). Thus, symbolic racism has two main components: (1) anti-Black sentiment and (2) “traditional American moral values” (Kinder & Sears, 1981, p. 416).
Examples of Whites’ opposition to “unfair” governmental assistance programs have included opposition to programs such as welfare, “free” busing, and “free” abortions for the poor (Kinder & Sears, 1981). Among U.S. citizens, subtle measures of racial prejudice (such as symbolic racism) consistently predict political attitudes and policies (Kinder & Sanders, 1996), and this emphasis on race in U.S. politics has increased since the election of the U.S.’s first Black President, Barack Obama (Kinder & Dale-Riddle, 2012; Tesler & Sears, 2010). The debate over universal health care in the U.S. embodies many of the qualities of these earlier social programs. Specifically, President Obama’s Affordable Care Act seeks to increase equality of access to health care through the creation of a public option for health care insurance and a universal mandate for coverage. Reflecting these former social policies, universal health care has caused much contention in the U.S. because some citizens perceive it as providing unmerited aid from the government (Napolitano, 2012) whereas others believe it provides needed access to health care for lower income citizens (Shapiro, 2012). Given the relationship between race and these types of public policies, support for universal health care may also be influenced by subtle racial prejudice.
Like other universal health care policies, the Affordable Care Act aims to reduce the number of uninsured U.S. citizens, who are composed primarily of historically disadvantaged groups (DeNavas-Walt, Proctor, & Smith, 2011). Data from 2010 demonstrate that non-Hispanic Whites had the lowest uninsured rate (11.7%) whereas racial minorities had higher uninsured rates, with Blacks (20.8%) and Hispanics (30.7%) being among the least insured (DeNavas-Walt et al., 2011). Opposition to universal health care may be partially driven by symbolic racism because individuals want to keep the “status quo” in which racial minority members are disadvantaged with regard to health care access. The U.S. public has focused largely on political ideology as a predictor for support of universal health care. For example, eight out of ten Democrats agree with the Supreme Court ruling upholding the Affordable Care Act whereas eight out of ten Republicans oppose it (CNN Political Unit, 2012). Despite this public focus on political ideology, research indicates symbolic racism may also predict universal health care attitudes among U.S. citizens. For example, White U.S. citizens who scored above the mean on a measure of racial resentment toward Black U.S. citizens were significantly less likely to support health care reform (Hetherington & Weiler, 2009). General attitudes toward Blacks, who may be perceived as benefitting more from health care reform, may also predict universal health care attitudes. Despite the possible influence of racial attitudes on support for universal health care, these attitudes have been largely unexamined as potential predictors. Better understanding how subtle racial prejudice influences support for universal health care is critical thanks to rising numbers of uninsured U.S. citizens. From 2009 to 2010, the number of uninsured U.S. citizens rose from 49.0 million to 49.9 million (16.3%; DeNavas-Walt et al., 2011). The goal of the present research was to examine how subtle racial prejudice, in addition to political ideology, predicts universal health care attitudes.i Given the long-standing history of racial attitudes in the U.S. predicting support for governmental assistance programs, it is possible that racial attitudes may also predict support for universal health care.
The theory of symbolic politics, out of which the theory of symbolic racism was originally developed, supports this approach of considering both the influence of political ideology and subtle racial prejudice on attitudes toward governmental policies such as universal health care. This broader theory was designed to examine the influence of symbolic predispositions on political attitudes and behaviors (Sears, 1988). Here the term symbolic refers to an “emotion based on some enduring predisposition rather than on the tangible costs and benefits of the matters to which the symbol [e.g., political symbol] refers” (Sears, 1993, p. 114). In the case of universal health care, symbolic would refer to emotions about what universal health care represents rather than the actual costs and benefits associated with implementing universal health care in the U.S. The theory of symbolic politics suggests individuals’ pre-adult socialization develops specific symbolic predispositions, which include attitudes and beliefs such as racial attitudes, ideology, and party identification. These symbolic predispositions, in turn, predict specific political attitudes and behaviors (Sears, 1988). This theory was developed in the U.S. and applies to a culture-specific phenomenon in which symbolic predispositions predict U.S. political attitudes and behaviors.ii Based on a history of racial conflict in the U.S., this theory suggests that racial attitudes play a unique role alongside personal and political ideologies to predict political attitudes and behavior. Supporting this theory, three symbolic predispositions —racial attitudes, ideological self-labeling, and party identification—have predicted a variety of political attitudes ranging from support for the Vietnam War (Lau, Brown, & Sears, 1978) to responses to the energy crisis in the 1970s (Sears, Tyler, Citrin, & Kinder, 1978) and opposition to bussing laws designed to increase racial integration of school children (Sears, Hensler, & Speer, 1979). Similarly, these symbolic predispositions may predict attitudes toward universal health care because it represents a political attitude commonly linked with race.
From the theoretical perspective of symbolic politics, we would expect that the more a policy is associated with race, the more powerfully symbolic attitudes about race will influence the policy. That is, symbolic racism itself (attitudes toward Black U.S. citizens) may predict attitudes toward policies associated to benefit minorities. However, given that the U.S. President championing these policies (Obama) is African American, attitudes toward Obama himself may predict support for universal health care. Although previous studies have investigated the relationship between attitudes towards Obama and support for specific universal health care policies (Tesler, 2012; Tesler & Sears, 2010), none have yet examined the broader symbolic politics theory suggesting that symbolic racism will predict a lack of support for policies assumed to benefit minorities.
Symbolic Racism and Race-Related Policies
Whereas the theory of symbolic politics was intended to be a general explanation of broad political behavior, symbolic racism was intended to predict attitudes toward U.S. policies associated with race. U.S. citizens high in symbolic racism believe that Blacks should not be given any special treatment because it violates the values of individualism and equality and is thus unfair and undeserved (McConahay, 1986). The danger of this form of prejudice is its subtlety. Prejudice expressed as a lack of support for policies designed to reduce or eliminate racial inequalities is less socially proscribed and serves to maintain these inequalities.
For example, symbolic racism is associated with opposition to “excessive access to welfare” (Sears, 1988, p. 56) and “compulsory bussing,” designed to enhance racial integration in school systems (McConahay, 1982). More recently, symbolic racism has been shown to predict opposition to government action to ensure fair treatment of Blacks and affirmative action, even when statistically controlling for conservative ideology and beliefs in the need to minimize government involvement (Matsueda & Drakulich, 2009). Symbolic racism has also predicted opposition to compensatory affirmative action and preferential hiring of Blacks (Rabinowitz, Sears, Sidanius, & Krosnick, 2009) as well as policies delivering federal assistance to Blacks (Sears, Van Laar, Carrillo, & Kosterman, 1997).
Many studies have focused on examining symbolic racism as a predictor of racial policies directly benefitting Blacks (e.g., affirmative action). However, symbolic racism has also been shown to predict attitudes toward U.S. policies that are presumed to benefit Blacks but are not directly targeted to benefit them (Kinder & Sanders, 1996). For instance, symbolic racism predicted a lack of support for increasing governmental spending on welfare and food stamps when statistically controlling for liberalism/conservatism and anti-egalitarian attitudes (Rabinowitz et al., 2009). Symbolic racism might also predict attitudes toward U.S. policies with no clear racial preference because, “when messages are framed in such a way to reinforce the relationship between a particular policy and a particular group, it becomes far more likely that individuals will evaluate the policy on the basis of their evaluations of the group” (Hurwitz & Peffley, 2005, p. 109). Thus, U.S. governmental programs like welfare and food stamps, which are frequently viewed as benefitting “underprivileged Blacks,” become more directly associated with benefitting Blacks. Additionally, Whites may exaggerate the proportion of poor individuals who are Black (Kinder & Sanders, 1996), exacerbating this issue.
Similarly, subtle racial prejudice (such as symbolic racism) may predict support for other U.S. governmental programs that have been racially framed, such as universal health care. As noted above, there is a significant racial divide in access to health insurance in the U.S. (DeNavas-Walt et al., 2011). Further, political journalists have begun to discuss the fight surrounding universal health care in the U.S. as “a fight for racial equality” and identifying universal health care as a potential step in addressing an “American history [that] is littered with instances in which Blacks received poor care or no care at all…” (Jackson, 2012). Although universal health care is not directly aimed at benefitting Blacks, those high in subtle racial prejudice may presume (as they do with welfare and food stamps) that Blacks will benefit more from an increase in governmental spending on universal health care. These assumptions may be well-founded, as research suggests universal health care could reduce the racial divide in health care coverage (Clemans-Cope, Kenney, Buettgens, Carroll, & Blavin, 2012). Given this potential for racial inequality reduction, it is important to examine how measures of subtle racial prejudice (such as symbolic racism) influence opposition to universal health care in pursuit of reducing these inequalities.
Opposition to Obama’s Health Care Plan
As noted earlier, many researchers have suggested that race has never been a more salient influence on U.S. political attitudes than with the first Black president, Barack Obama, in office (Kinder & Dale-Riddle, 2012; Tesler & Sears, 2010). This “chronic accessibility” of race has led racial attitudes to contribute powerfully to attitudes toward Obama and political policies associated with him (Tesler & Sears, 2010, p. 6). For instance, racial resentment predicted opposition to President Obama, especially among those with poor education (Kinder & Dale-Riddle, 2012). This racial resentment toward the president had a “spillover of racialization” such that it affected attitudes toward his polices as well (Tesler, 2012; Tesler & Sears, 2010). For example, implicit racial attitudes predicted a reluctance to vote for Obama as well as opposition to his health care reform plan (Knowles, Lowery, & Schaumberg, 2010). However, this implicit racial prejudice only predicted more negative attitudes toward the health care reform plan when it was proposed by Barack Obama, but not when it was proposed by Bill Clinton (Knowles et al., 2010). Similarly, Tesler (2012) found that White individuals were less supportive of the health care plan when it was framed as being proposed by Barack Obama (a Black presidential candidate) than Hillary Clinton (a White, female presidential candidate). Moreover, negative racial attitudes predicted endorsement of the statement: “Health care should be voluntarily left up to individuals” in Fall 2009 (after Obama had been elected) more than they did in cross-sectional surveys taken over the last two decades (Tesler, 2012).
These studies suggest that the race of the policy’s supporter explains unique variability in support for the policy. This explanation fits with findings suggesting racial prejudice predicts negative attitudes toward Obama as a presidential candidate (Dwyer, Stevens, Sullivan, & Allen, 2009). Although Obama’s race influences individuals’ likelihood of endorsing his specific health care plan, little research has examined how general racial attitudes influence support for universal health care more broadly.
Overview of the Present Research
Previous research has shown that measures of subtle racial prejudice, such as symbolic racism, did not predict attitudes toward national health insurance in the U.S. (Sears, Sidanius, & Bobo, 2000). However, this research only measured attitudes toward national health insurance with a single item asking individuals to what degree they preferred a government insurance plan to a private insurance plan, in a political context where race was less closely associated with health care reforms (e.g., in the absence of an African American president). Given the limitations of this prior research and the increasing relevance and importance of understanding attitudes toward universal health care and race relations in the U.S., we examined more closely the connection between subtle racial prejudice and universal health care attitudes among U.S. citizens. Because political ideology has been shown to play an important role in predicting attitudes toward national health insurance (Sears, Lau, Tyler, & Allen, 1980), we included it in these studies to examine if subtle racial prejudice predicted attitudes toward universal health care when statistically controlling for political ideology.
We developed a measure of universal health care and assessed its reliability and internal consistency as well as its association with political ideology (Pilot Study) to be used in the present studies. We hypothesized that subtle racial prejudice would be associated with opposition to universal health care among U.S. citizens. To test this main hypothesis, we conducted three studies. First (Study 1), we conducted a survey to test the hypothesis that a measure of subtle racial prejudice is significantly associated with a lack of support for universal health care even when statistically controlling for alternative explanations. Second (Study 2), we tested the hypothesis that increasing the salience of race (a subtle manipulation, allowing for subtle racial prejudice to be expressed) would decrease support for universal health care. Finally, in Study 3, we tested a mechanism for reducing the effect of subtle racial prejudice on support for universal health care by testing the hypothesis that humanizing information about the need for universal health care at the individual level would reduce the effect of race on universal health care support. In total, these three studies examined the overarching hypothesis that subtle forms of racial prejudice predict a lack of support for universal health care, as well as a mechanism for reducing that influence.
Pilot Study
The purpose of the pilot study was: 1) to develop a single-factor measure of universal health care attitudes and 2) to replicate past research demonstrating universal health care attitudes are associated with political ideology (Sears et al., 2000). It was hypothesized that self-identifying as politically liberal would be significantly associated with support of the newly created measure of universal health care attitudes.
Method
Participants
Three hundred sixty-eight individuals (125 males, 239 females, 4 missing; mean age = 32.57 years, SD = 12.62) filled out an online survey. Data were collected from individuals across the U.S. through Amazon’s Mechanical Turk (MTurk) service, which has been shown to provide reliable and more diverse data than college samples (cf. Behrend, Sharek, Meade, & Wiebe, 2011; Buhrmester, Kwang, & Gosling, 2011; Mason & Suri, 2012). Because past research indicates that MTurk samples can lead to people participating in several related studies (Chandler, Mueller, & Paolacci, 2014), we screened all participants for unique IP numbers to reduce the possibility of replication of participants across studies. All participants received $0.10 in exchange for their completion of a five-minute survey. The sample was comprised of the following races/ethnicities: 79.1% White, 10.9% Asian/Pacific Islander, 5.4% African-American/Black, 2.2% Hispanic, 1.6% “other”, .5% Native American, and .3% missing.
Measures
Demographics and political ideology
Several demographic variables were included to measure sex, age, race, education, and socio-economic status (SES). A single-item measure was used to measure political ideology (1 = extremely conservative, 7 = extremely liberal).
Universal health care attitudes
Four items were used to measure universal health care attitudes (see Table 1). Attitudinal items were created based on Bodenheimer's (2005) hypothesis that politically liberal individuals support universal health care because they view it as a human right and necessity (Items 2 and 4), an assessment of general support for universal health care (Item 1), and on popularly held views that universal health care takes advantage of hard-working individuals to support “lazy” individuals (Item 3). These items were selected from an initial list of 10 items and narrowed down based on expert feedback which selected items most representative of these three main areas and which reduced overlap in items or concepts. Items were rated on a 7-point Likert type scale ranging from 1 (strongly disagree) to 7 (strongly agree).
Table 1
Items in Attitudes Toward Universal Health Care Scale (Pilot Study, U.S. Sample, n = 368).
| Item | Cronbach’s α if item deleted |
|---|---|
| “I support the recently passed health care bill.” | .87 |
| “Our government needs health reform because the underprivileged are not getting their basic needs met.” | .85 |
| “Universal health care is just designed to make the hard-working people of America pay for the health care of the lazy people of America.” † | .82 |
| “Access to medical care and insurance is a basic, inherent right of man.” | .86 |
| Overall α | .88 |
† = reverse-coded item.
Analyses
To test the hypothesized factor structure of universal health care attitudes, a maximum-likelihood confirmatory factor analysis was performed. Four statistics reflecting fit were reported: the chi-square (χ2) test statistic; the root mean square error of approximation (RMSEA; Browne & Cudeck, 1993); the Tucker Lewis Index (TLI), also known as the Non-Normed Fit Index (NNFI); and the Comparative Fit Index (CFI; Bentler, 1990). Standardized path coefficient values and their accompanying levels of significance are reported in Figure 1.
Results and Discussion
Confirmatory Factor Analysis
The one-factor model of universal health care showed good fit. The chi-square goodness of fit statistic was not significant, χ2 (2, N = 368) = 5.52, p = .06, indicating the single-factor model fit the data well. The RMSEA compensating for the effects of model complexity was .069 (CI90: .000; .141), which according to Browne and Cudeck (1993) indicates acceptable fit of the model at less than .08. The value of the TLI/NNFI was .977, and the value of the CFI was .995. Hu and Bentler (1999) note that fit index values of .95 (or better) are indicative of good fit. As indicated in Figure 1, all path values were statistically significant at the .05 level or less. This scale also had good internal consistency (α = .88; see Table 1).
Figure 1
Single-factor universal health care model. Pilot Study, U.S. sample, n = 368 / Study 1, college sample, n = 144.
*p < .05. **p < .01. † = reverse-coded items.
Support for Universal Health Care
Correlations between variables are included in Table 2. In order to examine demographics and political ideology as predictors of support for universal health care, a regression analysis was run (see Table 3). These combined predictors explained 38% (adjusted) of the variance in universal health care attitudes. As hypothesized, being more liberal predicted favoring universal health care.
Table 2
Correlations Between Demographics, Ideology, Prejudice, and Attitudes Toward Universal Health Care [Pilot Study (n = 368)]
| Demographic/attitudes | 1 | 2 | 3 | 4 | 5 | 6 | 7 | M | SD |
|---|---|---|---|---|---|---|---|---|---|
| 1. Universal health care | --- | 4.67 | 1.60 | ||||||
| 2. † Race (dummy-coded, 0 = non-White, 1 = White) | -.09 | --- | .79 (%) | -- | |||||
| 3. † Sex (dummy-coded, 0 = female, 1 = male | -.23** | .06 | --- | .34 (%) | -- | ||||
| 4. †Age | -.07 | .14** | .04 | --- | 32.57 | 12.62 | |||
| 5. †SES | -.10 | .05 | -.13* | -.02 | --- | 2.84 | .83 | ||
| 6. † Education | .02 | -.05 | .07 | .20** | -.26** | --- | 5.07 | 1.34 | |
| 7. † Political ideology | .59** | -.03 | -.14** | -.10 | .04 | .06 | --- | 4.35 | 1.72 |
*p < .05. **p < .01. † = single-item measure.
Table 3
Regression Equation Predicting Attitudes Toward Universal Health Care [Pilot Study (n = 368)].
| Demographics/attitudes | Stand. β | t-value | p-value |
|---|---|---|---|
| Race (dummy-coded, 0 = non-White, 1 = White) | -.07 | -1.65 | .099 |
| Sex (dummy-coded, 0 = female, 1 = male) | -.13 | -2.94 | .004 |
| Age | -.01 | -.13 | .897 |
| SES | -.07 | -1.66 | .098 |
| Education | .02 | .40 | .689 |
| Political ideology | .57 | 13.09 | <.001 |
| R2 | .38 | ||
| Adjusted R2 | .37 | ||
| F-value | 35.13*** | <.001 |
Study 1
In the pilot study, we demonstrated that the universal health care attitudes scale was a reliable measure with a single-factor structure and that political ideology predicted universal health care attitudes as expected. Study 1 aimed to test our central hypothesis that subtle racial prejudice would predict attitudes toward universal health care, even when controlling for political ideology. Study 1 also included additional variables to rule out alternative explanations for the relationship between racial prejudice and universal health care support. For example, because race and poverty are often confounded due to higher rates of poverty among Blacks (DeNavas-Walt et al., 2011), attitudes toward the poor could account for variance in universal health care attitudes.
Method
Participants
Two hundred thirty-one individuals from the U.S. (91 males, 132 females, 8 missing; mean age = 35.84 years, SD = 13.54) filled out an online survey through MTurk. All participants received $0.15 in exchange for their completion of a five-minute survey. Since these studies investigate subtle racial prejudice towards Blacks, members of the target group (African Americans) were removed from all analyses in this (n = 29) and subsequent studies. The final sample consisted of 202 individuals from the U.S. (88 males, 113 females, 1 missing; mean age = 36.12, SD = 13.61) and was approximately 81.2% White, 9.4% Asian/Pacific Islander, 5.4% “other”, and 4.0% Hispanic.
Measures
Demographics, political ideology, RWA, and universal health care attitudes
Several demographic variables were included to measure sex, age, race, and socioeconomic status (SES). SES was measured by asking individuals what SES bracket they were raised in (1 = upper class, 5 = lower class). We utilized a 4-item measure of political ideology that assessed general political ideology (“How would you describe yourself politically?” 1 = very conservative, 7 = very liberal) and political ideology in relation to foreign policy, economic, and social issues (1 = very conservative, 7 = very liberal; cf. Pratto, Sidanius, Stallworth, & Malle, 1994). RWA was assessed with a 10-item measure (Mavor, Macleod, Boal, & Louis, 2009; Smith & Winter, 2002). The universal health care attitudes scale developed in the pilot study was used to assess universal health care attitudes.
Subtle racial prejudice
Subtle racial prejudice was measured with the Modern Racism Scale (MRS; McConahay, 1986). The MRS is a 7-item scale originally developed to measure symbolic racism toward African Americans (e.g., “Over the past few years Blacks have gotten more economically than they deserve;” 1 = disagree strongly, 5 = agree strongly).
Attitudes toward the poor
A 12-item scale was used to measure attitudes toward the poor (Cozzarelli, Wilkinson, & Tagler, 2001). Items were rated on a 5-point Likert-type scale, indicating the degree to which individuals endorsed negative attitudes toward the poor (e.g., “I try to avoid contact with poor people;” 1 = strongly disagree, 5 = strongly agree).
Results and Discussion
Correlations, means, and standard deviations for all measures are included in Table 4. To examine the association between racial prejudice and attitudes toward universal health care and to rule out political ideology and attitudes toward the poor as potential confounds, a hierarchical regression was performed (see Table 5).iii Power for the hierarchical regression was calculated based on the following information: 1) sample size (n = 231), 2) α set at .05, 3) medium effect size (d = .50), and 4) the number of predictors. The power for this hierarchical regression was (1-β) = .99, representing adequate power. In the first step, all demographic variables (sex, race, age, and SES), political ideology, and RWA were added as predictors of universal health care attitudes. In the second step, attitudes toward the poor was added as a predictor. In the third and final step, modern racism was added. Combined predictors from the final step of the three-step regression accounted for 64.0% (adjusted) of the overall variance in universal health care attitudes. In the first step, being more liberal was associated with more positive attitudes toward universal health care and was also the strongest predictor in the regression model. Consistent with the Pilot Study, being male was also a predictor of negative attitudes toward universal health care. In the second step, attitudes toward the poor explained significant additional variance in universal health care attitudes. Political ideology and attitudes toward the poor were both predictors of universal health care attitudes in the second step. Finally, in the third and final step, modern racism explained unique variance in universal health care attitudes. The only other significant predictor in the full regression model was political ideology, where liberalism predicted more support of universal health care.
Table 4
Correlations Between Demographics, Ideology, Prejudice, and Attitudes Toward Universal Health Care [Study 1 (n = 202)]
| Demographic/attitudes | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | M | SD | α |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. Universal health care | --- | 4.74 | 1.61 | .85 | ||||||||
| 2. † Race (dummy-coded, 0 = non-White, 1 = White) | .00 | --- | .81 (%) | -- | -- | |||||||
| 3. † Sex (dummy-coded, 0 = female, 1 = male) | -.09 | .09 | --- | .44 (%) | -- | -- | ||||||
| 4. † Age | -.11 | .22** | -.05 | --- | 36.12 | 13.61 | -- | |||||
| 5. † Socioeconomic status | .09 | .15* | .09 | .16* | --- | 3.40 | .84 | -- | ||||
| 6. Political ideology (conservative/liberal) | .70** | -.12 | .07 | -.28* | .11 | --- | 4.46 | 1.74 | .91 | |||
| 7. Right-wing authoritarianism | -.38** | -.20** | .00 | .00 | -.19** | -.60** | --- | 2.96 | 1.31 | .88 | ||
| 8. Attitudes toward the poor | -.24** | -.04 | .17* | -.19** | -.22** | -.27* | .14* | --- | 2.22 | .74 | .93 | |
| 9. Modern racism scale | -.57** | -.04 | .05 | .06 | -.03 | -.50** | .44** | .29** | --- | 2.31 | .90 | .89 |
*p < .05. **p < .01. † = single-item measure.
Table 5
Regression Equation Predicting Attitudes Toward Universal Health Care [Study 1 (n =202)]
| Demographics/attitudes | Step 1 - Stand. β | t-test (p-value) | Step 2 – Stand. β | t-test (p-value) | Step 3 – Stand. β | t-test (p-value) |
|---|---|---|---|---|---|---|
| Race (dummy-coded, 0 = non-White, 1 = White) | -.01 | -.14 (p = .89) | .02 | .18 (p = .86) | .02 | .28 (p = .78) |
| Sex (dummy-coded, 0 = female, 1 = male) | -.19* | -2.19 (p = .03) | -.15 | -1.72 (p = .09) | -.06 | -.70 (p = .49) |
| Age | .04 | .39 (p = .69) | -.02 | -.22 (p = .83) | .00 | .01 (p = .99) |
| SES | .08 | .84 (p = .40) | .06 | .66 (p = .51) | .04 | .45 (p = .65) |
| Political ideology | .66*** | 5.58 (p = .00) | .62*** | 5.40 (p = .00) | .56*** | 5.38 (p = .00) |
| RWA | -.05 | -.41 (p = 68) | -.01 | -.07 (p = .94) | .14 | 1.19 (p = .24) |
| Attitudes toward the poor | --- | -.24** | -2.70 (p = .01) | -.13 | -1.54 (p = .13) | |
| Modern racism scale | --- | --- | -.39*** | -3.87 (p = .00) | ||
| R2 | .51 | .56 | .64 | |||
| Adjusted R2 | .46 | .51 | .59 | |||
| F-value | 11.68*** | p < .001 | 11.97*** | p < .001 | 14.53*** | p < .001 |
| R2 change | .05** | p = .009 | .08*** | p < .001 |
Note. SES = socioeconomic status, RWA = right-wing authoritarianism.
*p <.05. **p < .01. ***p < .001.
These results support our central hypothesis that subtle racial prejudice is associated with a lack of support for universal health care, even when statistically controlling for political ideology and underlying attitudes toward the poor.
Study 2
Study 1 demonstrated that subtle racial prejudice predicted opposition to universal health care, even when statistically controlling for political ideology and other alternative explanations. Although subtle racial prejudice was shown to predict attitudes toward universal health care, it is unclear whether increasing the salience of race in the context of universal health care would have any effect on attitudes toward universal health care. As described above, previous research indicates perceptions of minority benefit moderate the relationship between racial prejudice and policy. For example, symbolic racism better predicted opposition to race-associated policies like affirmative action and government-mandated equality for Blacks than it did less explicitly racial policies like government-mandated equality for everyone. Moreover, symbolic racism predicted opposition to governmental aid when individuals were led to believe the beneficiaries were Black but not when they thought they were women (Rabinowitz et al., 2009). Based on these findings, we hypothesized that participants would be less supportive of universal health care when race was salient, that is, if they read about a Black individual in need of health care than if they read about a White individual in need of health care. This allowed for a subtle manipulation of race to examine causality.
Method
Participants
Sixty-nine (12 males, 57 females; mean age = 19.45 years, SD = 1.76) U.S. undergraduate students at a Southwestern U.S. university participated in this study in exchange for one hour of psychology research credit. After removing African American participants (n=8) from all analyses, the final sample consisted of 61 students (11 males, 50 females; mean age = 19.41 years, SD = 1.76). This sample was comprised of the following ethnicities: 73.8% White, 14.8% Hispanic, 8.2% Asian/Pacific Islander, and 3.3% “other.” On a scale from 1 (very liberal) to 7 (very conservative), participants rated being an average of 4.82 (SD = 1.36) in political ideology, indicating a slight conservative leaning. Only 8.2% of participants had voted in the previous election, which is reflective of an undergraduate population in which most of the individuals included were not until recently old enough to vote. An online research participation scheduling program, SONA systems human subject pool management software, was utilized to recruit participants.
Materials and Procedures
Participants completed this study in a controlled lab environment in order to reduce random error. The scenarios and surveys were filled out through an online survey program (Qualtrics) on a computer in an isolated room in a controlled lab. To reduce the possible influence of an experimenter or social desirability effect, none of the research assistants who helped set up the online study were Black. Participants were randomly assigned to one of two conditions in which they read about an individual in need of health care who was either Black (n = 33) or White (n = 28).iv These scenarios were randomly assigned by and read on the online survey program. After reading this scenario, participants were asked about their attitudes toward the individual they read about receiving health care benefits as well as their general universal health care attitudes. At the end of the online survey, participants were thanked (by research assistants) and given course credit in exchange for participation.
Race manipulation
As noted, individuals were assigned to read a scenario about an individual in need of health care who was either Black (n = 33) or White (n = 28) (see Appendix A for scenario). All information was held constant and neutral across both conditions except for a change of race and names. In the Black condition, the individual was named Lakisha Jones and was identified as an African American whereas the individual in the White condition was named Deborah Williams and was identified as White. These names were chosen because they represent typical African American names (Lakisha Jones) or White, Anglo-Saxon Protestant names (Deborah Williams). They were based on prior research, which used these names to prime individuals with African American stereotypes (Bertrand & Mullainathan, 2004). Women were chosen in the present experiment: 1) to maintain consistency across conditions and minimize potential cross-gender effects and 2) because there is a gender gap in earnings and employment that may make women more likely to need access to healthcare through governmental assistance (U.S. Census Bureau, 2012).
Attitudes toward universal health care, political ideology, and RWA
Participants’ universal health care attitudes were measured using the universal health care attitudes scale developed in the pilot study (α = .73). A three-item measure of political ideology was utilized which contained items assessing the degree of conservatism/liberalism regarding social, economic, and foreign policy issues (α = .81). A three-item RWA aggression subscale of the 10-item measure of RWA (Mavor et al., 2009; Smith & Winter, 2002) used in Study 1 was used to measure RWA aggression in the present study (α = .72). RWA aggression was included instead of the full RWA scale because previous research has demonstrated the RWA aggression component of RWA has the strongest association with racial prejudice out of all three factors (Johnson et al., 2011; Mavor et al., 2009).
Attitudes toward individual receiving universal health care
After reading one of the race manipulation scenarios, individuals were asked to indicate to what degree they believed the individual they read about deserved health care. A six-item Likert-type scale was used to measure these attitudes by asking individuals to what degree they thought the individual in the scenario (“I believe this woman…”) deserved better health care (e.g., “…needs the government to provide more aid in covering the cost of medical care”) or was taking advantage of the system (reverse coded item; “…was taking advantage of the health care system”; 1 = very strongly disagree, 7 = very strongly agree) (α = .81) (see Appendix B for full measure). All reverse-keyed items were reverse-scored, and then all items were aggregated to obtain a measure of attitudes toward individuals receiving universal health care. Higher scores indicated more support for individuals receiving universal health care aid.
Results and Discussion
Attitudes Toward General Universal Health Care
An ANOVA was computed to examine the effects of race on attitudes toward generalized universal health care. Additionally, an ANCOVA was computed to examine the effects of race on attitudes toward generalized universal health care statistically controlling for political ideology and RWA aggression. These two covariates were included in the model because they have been shown to be strong predictors of universal health care attitudes in past research (Sears et al., 2000) as well as in Study 1. Power for this ANCOVA was calculated based on the following information: 1) sample size (n = 69), 2) α set at .05, 3) large effect size, and 4) the number of groups (n = 2). The power for this ANCOVA (controlling for two covariates) was (1-β) = .91, representing adequate power. Initial analyses were run to make sure that the condition did not influence these two covariates. A MANOVA examined the effects of condition (Black, White) on political ideology and RWA aggression. Results indicated that race condition had no significant effects on political ideology [F(1, 59) = 2.48, p = .12] or RWA aggression [F(1, 59) = .16, p = .69].
The ANOVA examining the effect of race indicated that race did not have a significant effect on attitudes toward universal health care, F(1, 59) = 1.60, p = .21, Partial η2 = .03. The ANCOVA examining the effect of race condition (controlling for political ideology and RWA aggression) indicated that participants who read about a Black individual needing universal health care reported significantly less support of universal health care (M = 3.69, SD = 1.03) than those who read about a White individual needing universal health care (M = 4.04, SD = 1.16), F(1, 57) = 6.19, p = .02, Partial η2 = .10) once controlling for these covariates.
Attitudes Toward Individuals Receiving Universal Health Care
To examine the effects of the race of the target receiving health care aid on attitudes toward those individuals receiving universal health care aid, an ANOVA was computed. Additionally, an ANCOVA was computed with political ideology and RWA aggression included as covariates. Power for this ANCOVA was calculated based on the following information: 1) sample size (n = 69), 2) α set at .05, 3) large effect size, and 4) the number of groups (n = 2). The power for this ANCOVA (controlling for two covariates) was (1-β) = .91, representing adequate power. Results indicated that there was no significant effect of race on attitudes toward individuals receiving universal health care, F(1, 58) = .23, p = .63, Partial η2 = .01. These results were not significant, even when controlling for political ideology and RWA aggression as covariates, F(1, 56) = 1.18, p = .28, Partial η2 = .02.
Our hypothesis was partially supported, in that individuals would be less supportive of generalized universal health care when reading about a Black individual receiving health care than when reading about a White individual receiving health care when covariates were controlled. However, this effect only occurred when controlling for political ideology and RWA. This may have occurred because political ideology and authoritarian views predict a large amount of variance in attitudes toward universal health care (as seen in Study 1), such that statistically controlling them is necessary to discover any effect of race on support of universal health care. Manipulation of race, however, did not significantly influence attitudes toward specific individuals receiving universal health care. This could have been due to a non-significant effect or an improper estimate of the size of the effect. If the effect, for instance, were medium in size this ANCOVA would have been underpowered to test for significant differences in the effects of race on attitudes toward individuals receiving universal health care (1-β = .53).
An alternative explanation as to why the race manipulation influenced general attitudes toward universal health care, but not attitudes towards specific individuals receiving universal health care, is that symbolic racism has been shown to predict a lack of support for policies that seem to benefit Black individuals but not a lack of support for specific individuals receiving these benefits. It is possible that when individuals are faced with considering a single individual being in need of governmental aid, they may hold lower levels of subtle racial prejudice and thus may show more support for these policies being implemented on an individual basis. Future research is needed to better test this hypothesis, however, it points to a potential way to intervene on individuals’ symbolically racist attitudes toward policies designed to support underprivileged citizens. Namely, highlighting the need of individuals in need of aid may reduce levels of symbolic racism.
In short, results from this study partially support symbolic politics theory, demonstrating that racial salience of a policy combined with symbolic racism influences support for this racially-relevant social policy even if the race of the target does not influence attitudes towards a specific individual’s need. Nevertheless, as noted above, these manifestations of symbolic racism are particularly insidious precisely because they manifest at the policy, rather than individual level. Given this connection between racial bias and opposition to universal health care, Study 3 set out to examine how policymakers might reduce the effect of racial bias on opposition to universal health care.
Study 3
Previous research in the U.S. has shown that the framing of political discourse influences the role of various attitudes (such as racial prejudice) in predicting policy support (Kinder & Sanders, 1996). As Kinder and Sanders (1996, p. 281) noted, “What considerations turn out really to matter depends on what comes to mind. And this is what frames do: they spotlight some considerations and neglect others, thereby altering the mix of ingredients that citizens consider as they form their opinions.” For instance, when Whites’ attention was focused on racial frames (i.e., seeing an issue as whether Blacks deserved help), racial resentment became a dominant predictor of attitudes toward governmental policies (Kinder & Sanders, 1996). Other frames, however, shifted focus toward other attitudes to shape policy support. Given the power of framing, policymakers could encourage more deliberate and complex approaches toward forming opinions on universal health care in an attempt to avoid the influence of racial biases. For example, racial frames may activate free riding stereotypes such that individuals improperly assume Black individuals are free riders of governmental systems, such as universal health care. However, if race is salient, but this free riding stereotype is countermanded by information about the individual’s need, the effect of racial attitudes on policy support may be reduced. By framing universal health care rhetoric to provide more explicit information about the degree to which people (Black or White) need universal health care, policymakers may reduce the effects of subtle racial prejudice on attitudes toward universal health care as seen in Studies 1 and 2 by providing more information than just a racial context.
In the present study, we hypothesized that the effect of race on support of universal health care would be moderated by whether or not that individual was described as free riding or not free riding. In short, we hypothesized that there would be a significant interaction between race and free riding such that the presence of free riding might increase the effects of race (i.e., reading about black individuals who free ride would lead to the least amount of support for universal health care) and the lack of free riding would decrease the effects of race (i.e., Black and White individuals who were not free riders would lead to equal amounts of support for universal health care).
Method
Participants
Two hundred eight (70 males, 129 females, 9 unspecified; mean age = 35.62 years, SD = 13.03) adult U.S. individuals completed an online experiment through MTurk. All participants received $0.25 in exchange for their completion of a ten-minute survey. After removing African American participants (n = 24) from all analyses, the final sample consisted of 184 individuals (63 males, 119 females, 2 unspecified; mean age = 35.98, SD = 13.04). The sample was 83.7% White, 7.1% Asian/Pacific Islander, 6.5% Hispanic, 1.6% Native American, and 1.1% “other.”
Materials and Procedures
The materials and procedures for this study were similar to Study 2. Instead of solely manipulating race as in Study 2, however, we manipulated race (White, Black) and free riding (free riding the system, not free riding the system). Participants were randomly assigned to one of four conditions [a 2 (White, Black) x 2 (free riding, no free riding) experimental design] in which they read about a person in one of the following scenarios: 1) White individual not free riding universal health care (White, no free riding; n = 45), 2) Black individual not free riding universal health care (Black, no free riding; n = 46), 3) White individual free riding universal health care (White, free riding; n = 43), or 4) Black individual free riding universal health care (Black, free riding; n = 50) (see Appendix C for scenarios). After reading this scenario, participants were asked about their universal health care attitudes. After assessing these attitudes, racial prejudice, political ideology, and RWA were measured to control for these constructs statistically.
Free riding manipulation
To manipulate free riding, individuals were portrayed as not taking unfair advantage of the universal health care (no free riding) or taking advantage of the universal health care system (free riding). In the free riding condition, individuals were portrayed as staying on unemployment in order to receive free benefits from the government such as food stamps and Medicaid. In the no free riding condition, individuals were portrayed as working a low-income job but not being able to afford health care (due to lack of insurance) or receive governmental aid (due to being employed).
Control variables
As in Studies 1 and 2, we included political ideology and RWA as control variables in our model for Study 3. The same four-item measure of political ideology from Study 1 was utilized in this study (1 = very conservative, 7 = very liberal). The same 7-item Modern Racism Scale (MRS; McConahay, Hardee, & Batts, 1981) utilized in Study 1 was used to measure subtle racial prejudice in the present study. Subtle racial prejudice was measured in this study because we wanted to examine how the race and free riding conditions affected attitudes toward universal health care differentially, controlling for pre-existing levels of subtle racial prejudice. Finally, the full 10-item measure of RWA utilized in Study 1 (Mavor et al., 2009; Smith & Winter, 2002) was also used in the present study to measure RWA. Because both racial prejudice and RWA were included as control variables, we included the full measure of RWA (rather than the 3-item measures included in Study 2. This decision was made to ensure that the measure of RWA assessed the entire spectrum of authoritarianism, rather than just the RWA aggression subscale which has strong statistical and conceptual overlap with racial prejudice. Whereas racial prejudice was not a control variable in Studies 1 or 2, it was a control variable in Study 3. Thus, the utilization of RWA aggression only (as in Study 2) would be problematic due to RWA aggression’s overlap with racial prejudice.
Attitudes toward individual taking advantage of the health care system
As a manipulation check, a four-item Likert-type scale (1 = very strongly disagree, 7 = very strongly agree) was used to measure the degree to which individuals believed the person in the scenario (Deborah or Lakisha) would take advantage of the governmental welfare system (e.g., “Lakisha/Deborah would be likely to have children in order to receive extra government welfare.”) (α = .91).
Attitudes toward individual receiving universal health care
The same six-item Likert-type scale (1 = very strongly disagree, 7 = very strongly agree) used in Study 2 was used to measure attitudes toward the individual receiving universal health care. Higher scores indicate more support for individuals receiving universal health care aid.
Attitudes toward universal health care
After reading this scenario, individuals were asked to indicate to what degree they supported universal health care. The universal health care attitudes scale developed in the pilot study was utilized to measure universal health care attitudes.
Results and Discussion
Manipulation Check
A two-way ANOVA was computed to examine the effects of the racial and free riding manipulations on perception of individuals taking advantage of the health care system.v Both race and free riding were included to examine: 1) if the manipulation worked (e.g., those in free riding conditions were viewed as taking significantly more advantage of the universal health care system); 2) to examine if race was viewed as a proxy for free riding (e.g., if race significantly influenced perceptions about taking advantage of the universal health care system); and 3) to ensure there was not an interaction between race and free riding, which would qualify the results of the main effects. Results indicated that race and free riding had a significant main effect on perception of the individual’s taking advantage of the universal health care system, but there was no significant interaction, F(1, 179) = .00, p = .96, Partial η2 = .00. Individuals perceived those in the free riding condition as taking significantly more advantage of the universal health care system (M = 5.41, SD = .99) than those in the no free riding condition (M = 3.07, SD = 1.06), F(1, 179) = 240.84, p <.001, Partial η2 = .57. Race also had a significant effect on perception of degree to which individuals would take advantage of the health care system. Individuals perceived Blacks as significantly more likely to take advantage of the health care system (M = 4.48, SD = 1.52) than Whites (M = 3.99, SD = 1.56), F(1, 179) = 8.25, p = .01, Partial η2 = .04. As indicated by effect sizes, the effect of race was small whereas the effect of free riding was large, which indicates that our manipulation of free riding was effective and that race had very little effect on the perception of taking advantage. Both of these effects remained significant when statistically controlling for racial prejudice, political ideology, and RWA.vi
Attitudes Toward Individuals Receiving Universal Health Care
A two-way ANOVA was computed to examine the effects of the racial and free riding manipulations on attitudes toward individuals receiving universal health care. Power for this ANOVA was calculated based on the following information: 1) sample size (n = 208), 2) α set at .05, 3) medium effect size, and 4) and the number of groups (n = 4). The power for this ANOVA was (1-β) = .95, representing adequate power. There was no significant main effect of race on attitudes toward individuals receiving universal health care, F(1, 179) = .03, p = .86, Partial η2 = .000. Only free riding had a significant main effect on attitudes toward individuals receiving universal health care. Individuals perceived those in the no free riding condition as being more deserving of receiving universal health care (M = 5.97, SD = 1.06) than those in the free riding condition (M = 3.47, SD = 1.61), F(1, 179) = 152.09, p < .001, Partial η2 = .46. There was no significant interaction effect between the race and free riding conditions, F(1, 179) = .23, p = .63, Partial η2 = .001. The main effect of free riding remained significant (and increased in size) when statistically controlling for racial prejudice, political ideology, and RWA, F(1, 170) = 184.21, p < .001, Partial η2 = .52. See Table 6 for cell means.
Table 6
Means on Attitudes Toward Individuals Receiving Universal Health Care for all Conditions/Cells.
| Free Riding
|
||
|---|---|---|
| Race | Free riding | Not free riding |
| White | M = 3.50 (SD = 1.50) | M = 5.90 (SD = 1.16) |
| Black | M = 3.44 (SD = 1.71) | M = 6.04 (SD = .95) |
Generalized Universal Health Care Attitudes
A two-way ANOVA was computed to examine the effects of the racial and free riding manipulations on general attitudes toward universal health care. Power for this ANOVA was calculated based on the following information: 1) sample size (n = 208), 2) α set at .05, 3) medium effect size, and 4) the number of groups (n = 4). The power for this ANOVA was (1-β) = .95, representing adequate power. There was no significant main effect of race on attitudes toward universal health care, F(1, 180) = .00, p = .99, Partial η2 = .000. Only free riding had a marginally significant main effect on attitudes toward universal health care. Individuals in the no free riding condition showed marginally higher levels of support for universal health care (M = 4.96, SD = 1.48) than those in the free riding condition (M = 4.47, SD = 1.83), F(1, 180) = 3.76, p = .05, Partial η2 = .02. There was no significant interaction effect between the race and free riding conditions, F(1, 180) = 1.07, p = .30, Partial η2 = .006. The main effect of free riding became significant when statistically controlling for racial prejudice, political ideology, and RWA, F(1, 180) = 5.07, p = .03, Partial η2 = .03. See Table 7 for reporting of cell means.
Table 7
Means on Attitudes Toward Universal Health Care for all Conditions/Cells
| Free Riding
|
||
|---|---|---|
| Race | Free riding | Not free riding |
| White | M = 4.60 (SD = 1.66) | M = 4.83 (SD = 1.67) |
| Black | M = 4.36 (SD = 1.97) | M = 5.09 (SD = 1.28) |
Surprisingly, race did not have a main effect on support for universal health care nor did it exacerbate the effect of free riding on support for universal health care, as hypothesized or as demonstrated in prior work by Sniderman and colleagues (Peffley, Hurwitz, & Sniderman, 1997). Sniderman and colleagues’ prior work demonstrates that Whites who hold negative stereotypes about Blacks are more likely to judge them harshly in areas of welfare and crime but when they are confronted with contradicting information about their stereotypes, they respond quite favorably to Blacks. This effect was not replicated in the present experiment; these results indicate that our hypothesis was not supported. This could have been due to a non-significant effect or to an improper estimate of the size of the effect. If the effect, for instance, were small in size, the ANOVAs run in the present study would have been underpowered to test for significant differences in the effects of race and free riding on attitudes toward individuals receiving universal health care [(power) 1-β = .30]. Additionally, these results could be due to an ineffective experimental manipulation. The manipulation check clearly indicates the free riding condition was successful, however, it is less clear if the race manipulation was successful and/or distinct from the free riding manipulation.
Nevertheless, from these results, it appears that when more information is given about an individual’s circumstances, free riding but not race predicts attitudes toward universal health care. Free riding may have had such a strong effect on attitudes toward universal health care due to the nature of the manipulation which depicted someone clearly taking advantage of several welfare systems (e.g., Medicaid, food stamps) that are commonly linked with racial minorities. Thus, this experiment may not have allowed for a true test of the potential interaction between race and free riding because the free riding manipulation itself may have contained elements of symbolic racism. In line with this point, it should be noted that results from the manipulation check indicate that race significantly affected the perception that an individual is taking advantage of the health care system or free riding. This finding indicates that the manipulation check questions asking if the individual is taking advantage of the health care system may be inherently race-relevant. By bringing up the topic of race and welfare, this experiment may have unintentionally made a “welfare queen” script readily accessible. The “welfare queen” script is one that has been shown to be particularly associated with Black women (as examined in this study) in which Black women fit a stereotype of what a welfare recipient should look like (Gilliam, 1999). Future research could explore if more complex framing or narratives could modify the influence of symbolic prejudice on support for universal health care, rather than more simple “free riding” framing.
General Discussion
Our purpose in the present research was to contribute to the existing literature on symbolic racism as a predictor of political attitudes and behaviors. Following Sears' (1988) framework, we examined the model that symbolic predispositions predict support of or opposition to a critical political issue, universal health care. Utilizing a variety of measures and methods, three studies examined a symbolic predisposition, subtle racial prejudice, as a predictor of opposition to universal health care. Across these studies, we found results partially consistent with prior research on the relationship between symbolic predispositions and racial policy preferences (Kinder & Dale-Riddle, 2012; Kinder & Sanders, 1996; Tesler & Sears, 2010). Previous research revealed that racial prejudice and political conservatism predicted lack of support for policies that directly (affirmative action, busing laws) and indirectly (welfare, food stamps) benefit Black U.S. citizens (Kluegel & Smith, 1983; Rabinowitz et al., 2009; Sears et al., 1979). The present data provided partial support for our central hypothesis that subtle racial prejudice predicts negative attitudes toward universal health care, even when statistically controlling for political ideology. Specifically, Study 1 provided support for our specific hypothesis that subtle racial prejudice would predict opposition to universal health care, even when controlling for alternative explanations (i.e., attitudes toward the poor). Study 2 provided partial, but not full, support for our hypothesis. Namely, individuals who read about a Black individual needing universal health care expressed higher levels of opposition to universal health care than those who read about a White individual needing universal health care, but only when controlling for covariates. This indicates that controlling for pre-existing levels of political ideology and RWA is necessary for the race effect on support for universal health care to emerge. Of significance, the effect of race on attitudes in Study 2 only affected attitudes toward social policies (e.g., support of universal health care) but not attitudes toward individuals receiving healthcare, which is in line with symbolic politics theoretical framework (Sears, 1988). Although this could be due to a lack of statistical power to test this hypothesis, it is also possible that race of recipients of governmental aid programs only influence attitudes at the policy level and not at the individual level. Finally, Study 3 did not support our hypothesis. Namely, manipulation of free riding but not of race influenced the degree to which individuals supported universal health care. Moreover, race did not exacerbate the effects of free riding.
Combined, Studies 1-3 indicate that there is a correlational relationship between subtle racial prejudice and opposition to universal health care but the causal links are less clear. Whereas Study 1 provided correlational evidence for a link between racial prejudice and opposition to universal health care, Study 2 provided only some causal evidence for the link between subtle racial prejudice and opposition to universal health care. Consistent with previous findings that the race of individuals benefitting from policies influences individuals’ support of those policies (e.g., affirmative action; Rabinowitz et al., 2009), the race of individuals seeking universal health care influenced the degree to which participants were supportive of universal health care. However, no support was found for the influence of race on attitudes toward individuals receiving UHC. In addition to identifying a partial causal link between racial prejudice and opposition to universal health care, the present research also investigated a means to reduce the influence of racial cues on attitudes toward universal health care (Study 3). Results from Study 3 provided partial support for the framing hypothesis, which suggests that different frames of the same issue may evoke different attitudes and judgments about political policies (Kinder & Sanders, 1996). Providing more nuanced information or multiple frames could potentially reduce the influence of subtle racial prejudice.
Together, the results of these three studies provide partial support to suggest that attitudes toward Blacks explain unique variability in attitudes toward and opposition to universal health care policies even when controlling for other strong predictors such as political ideology and attitudes toward the poor. However, as noted, the causal effect of race on opposition to universal health care is less clear. Participants may perceive Blacks as more likely to free ride, but given the lack of a significant interaction between target race and the free riding manipulation in Study 3, future research should examine more specific ways to reduce the effects of race on attitudes toward universal health care.
Opposition to Universal Health Care: More Than Just Political Ideology
Although fewer Republicans (2 in 10) than Democrats (8 in 10) agree with the Supreme Court decision upholding the Affordable Care Act (CNN Political Unit, 2012), political ideology is not the sole determinant of universal health care attitudes. According to Sears' (1988) theory and supported by the present studies, both political ideology and symbolic racism play a role in predicting policy attitudes. These results extend prior findings demonstrating that symbolic racism predicts attitudes toward racial policy preferences (Kluegel & Smith, 1983) as well as policies inferred to benefit Black U.S. citizens, such as welfare (Rabinowitz et al., 2009).
So why does subtle racial prejudice predict universal health care attitudes? We suggest that it is because individuals view Blacks as being more likely to receive and take advantage of universal health care benefits (Study 3). Many Whites view the poor and recipients of federal aid as being disproportionately Black (Gilens, 2000). Given that the primary recipients of welfare programs are assumed to be Black, racial prejudice predicts attitudes toward and support for those programs (Rabinowitz et al., 2009). These data indicate that this assumption extends to universal health care policies as well; attitudes towards Blacks play an important role in predicting support for universal health care. Future research could examine beliefs that Blacks benefit from welfare (or take advantage) as a potential mediator between racial prejudice and opposition to universal health care to test this theory.
One possible alternative explanation comes from the theory of principled conservatism (Sniderman, Piazza, Tetlock, & Kendrick, 1991), which argues that political conservatives’ opposition to affirmative action and other such policies are not driven by racism but instead are driven by a desire for “equity” and “color-blindness.” Research supporting this theory has shown that conservatives do not have significantly higher levels of racism than non-conservatives (Sniderman et al., 1991). Similarly, political conservatisms’ value for “equity” may be what is driving the relationship between political ideology and attitudes toward universal health care. However, more recent research indicates that the correlation between political conservatism and racism is fully accounted for by their mutual association with social dominance orientation, indicating that political conservatism may not be as strongly associated with “equity” as previously thought (Sidanius, Pratto, & Bobo, 1996). Additionally, the present study results demonstrated that subtle racial prejudice remained a significant predictor of universal health care attitudes, even when controlling for political ideology. Future research could focus on better partialing out the difference between conservatism and racism as predictors of universal health care attitudes.
Implications
The present findings have important implications for equality in the U.S. Despite much progress following the Civil Rights movement, Blacks still remain at a substantial disadvantage in many realms, particularly economically (Sears et al., 2000). Given these extant inequalities, it is important to determine ways to reduce these racial gaps. Contention persists regarding the proper role of the U.S. government in dealing with inequality issues (Sears et al., 2000). Given that the poverty rate of Blacks (27.4% in 2010) is so much higher than that of Whites (9.9% in 2010; DeNavas-Walt et al., 2011), and the racial health care disparities described above, the role of the U.S. government in helping reduce these racial inequalities ought to be carefully considered.
Although some of this inequality may be due to differences in poverty rates, it does not negate the fact that race plays an important role in determining the quality of and access to health care that individuals receive (Lillie-Blanton, Brodie, Rowland, Altman, & McIntosh, 2000). As such, universal health care policies may play an important role in reducing racial health disparities in the United States. Alternatively, opposition to universal health care could be helping to maintain these disparities. This is why “symbolic racism may be, politically, the most potent vehicle for racial prejudice today” (Kinder & Sears, 1981, p. 416).
Due to the potential role of subtle racial prejudice in predicting universal health care attitudes, racial bias ought to be examined and targeted as a potential mechanism of political change in future research. Because the framing of information can be utilized to increase or decrease the degree to which racial cues influence political attitudes (Kinder & Sanders, 1996), it is an important area of intervention for policymakers. The present analyses did not directly support the hypothesis that framing of whether an individual free rides or does not could reduce the effects of race, but rather suggested that free riding itself was a powerful predictor of a lack of support for universal health care (without an interaction with race). As such, future research could examine alternative framing approaches to determine how to frame political messages about universal health care in a way that promotes endorsement of it, regardless of the race of the individual receiving it. Perhaps by educating voters about the needs of the populations served by specific universal health care policies, policymakers may be able to increase support by reducing the role racial cues play in influencing or informing attitudes toward universal health care. This, in turn, could ultimately help produce support for policies that address specific racial gaps in access to health care. However, based on our current findings, more research is required to understand the most effective ways to reduce the influence of racial bias on policy support.
Limitations and Directions for Future Research
Limitations in the present research afford opportunities for future investigations. First, although we examined the connections between subtle racial prejudice and support of universal health care through attitudinal measures, we did not examine the underlying processes that drive this connection. Possible mediators, as discussed earlier, may be attitudes toward President Obama or beliefs that African Americans benefit most from universal health care. Future research could combine past research indicating that attitudes toward Obama predict universal health care attitudes and the current theoretical framework of symbolic racism to examine both attitudes toward Obama as well as the belief that universal health care benefits minorities as two potential mediators of the relationship between racial prejudice and attitudes toward universal health care.
Second, another area for future research not addressed in the present studies is examining if subtle racial prejudice predicts behavior related to universal health care attitudes (e.g., voting or financial support of specific universal health care policies). Future elections may provide opportunities to address these questions. In the present study, we also used McConahay's (1986) measure of racism, which has traditionally been used to measure symbolic racism. However, more recent research often utilizes Henry and Sears (2009) measure of symbolic racism, which might lead to different results due to its assessment of a more indirect measure of racism that is more common in today’s U.S. society (versus the McConahay’s measure which is a more direct measure of racism). Future studies should examine how this more recently developed measure of racism might differentially predict attitudes toward universal health care.
Third, although we examined the relationship between subtle racial prejudice and universal health care attitudes, our current samples were limited to examining racial attitudes toward Blacks. Subtle prejudice toward other racial and ethnic groups, such as Hispanics and Latinos, might also predict lack of support for universal health care. In fact, because Latinos often represent a group that faces issues with immigration and illegal citizenship, prejudice towards this group may be an even more powerful predictor of lack of support for universal health care. Future research should examine these other areas of prejudice to determine if these results generalize.
Fourth, Study 3 indicated that providing free riding information did not reduce the effect of race on attitudes toward universal health care. As such, it would be advantageous to examine other modes of reducing the influence of racial prejudice on universal health care attitudes. For instance, intergroup contact has been shown to reduce racial prejudice (Pettigrew, 1998). Future research could examine how intergroup contact might reduce racial prejudice, potentially improving support for universal health care.
Fifth, although we examined one potential source of influence on U.S. citizens’ lack of support for universal health care, namely subtle racial attitudes, there are several other potential sources of influence as well that ought to be examined and considered. For instance, individuals’ ideas about the role of government in regulating individuals’ healthcare may be a strong predictor of attitudes toward universal health care. Political ideology, however, is a good proxy measure for this attitude and was included in the present studies. Additionally, the condition of the market economy, the availability of health care services in one’s area, and other market-level factors may influence attitudes as well. Finally, additional attitudes such as social dominance orientation (Pratto et al., 1994) and system justification (Kay & Jost, 2003), which have been shown to predict support of racial prejudice may also play a role in predicting universal health care attitudes.
Sixth, the samples used in the present studies included student samples at a Southwestern U.S. university and national samples collected from MTurk. Neither of these sources represents a nationally representative sample, as MTurk has been demonstrated to have some bias in the representativeness of the sample and to be more similar to samples of undergraduates than of the general U.S. population. Moreover, these samples failed to include a broad range of political orientation (e.g., Tea Party members), which may influence how strongly related racial prejudice and attitudes toward universal health care are. Thus, the present results may have limited generalizability to the broader U.S. public and broader sociopolitical contexts. To address these limitations of generalizability, recruitment procedures for getting a larger, more nationally representative sample would help discover if these results generalized more broadly to the entire U.S. public. Despite these limitations, however, it should be noted that results were consistent across both student samples and U.S. samples through MTurk, suggesting some consistency of results.
Finally, the present study may have been influenced by social desirability and the desire to control prejudice on self-report measures. As such, subtle prejudice may have been underreported. Future studies could assess internal motivation to respond without subtle prejudice (Plant & Devine, 1998) as a potential mediator of this relationship.
More generally, another direction for future research is to examine if the models seen in the present study extend to political issues other than universal health care. Racial attitudes might predict support for a multitude of other political policies, even policies less clearly framed in racial terms. President Obama’s 2013 State of the Union suggestion to dramatically increase education funding to provide government-funded preschool to all U.S. citizens evoked a new round of discussion surrounding education policy, for example. Although liberalism/conservatism is often viewed as the main contributor to these political attitudes, it is possible that racial prejudice also uniquely predicts lack of support for governmental spending on education programs. If Blacks are viewed as receiving disproportionately more benefits from improvements in educational spending than Whites as they are with welfare and food stamps (Plant & Devine, 1998), then racial prejudice also ought to predict attitudes toward governmental spending on education.
Conclusions
Our aim in the present research was to test the hypothesis that subtle racial prejudice predicts opposition to universal health care. Across three studies, utilizing correlational and experimental techniques with student and adult U.S. samples, we found partial support for the hypothesis that subtle racial prejudice is a unique predictor of opposition to universal health care. Given that much racial prejudice today takes place more subtly through opposition to policies that reduce racial inequality, examination of the relationship between subtle racial prejudice and support of these policies deserves greater scientific attention. Although the present studies provide only preliminary support for the connection between forms of racial prejudice and opposition to universal health care, results across these studies indicate a fairly consistent relationship. Much remains to be learned, however, about how intergroup attitudes influence political decisions on policies construed to reduce inequality.