Abstract
Background:
Previous research has associated self-reported political conservatism to mental health stigma. Although the limitations of self-reported political attitudes are well documented, no study has evaluated this relationship from a more nuanced perspective of sociopolitical identity.
Aims:
To assess the relationship between political attitudes and mental health stigma (i.e. negative stereotypes and intended social distance), particularly from a standpoint of Right-Wing Authoritarianism (RWA) – a more specific measure of political conservatism.
Method:
A sample of 505 New York State residents completed an online survey.
Results:
The results of this study indicated significant relationships between endorsements of self-reported conservatism and RWA to negative stereotypes and social distance in relation to mental illness. Individuals with ‘High RWA’ were more likely to see individuals with mental illness as dangerous and unpredictable, and less willing to want to socially associate with individuals with mental illness. These results remained statistically significant even when controlling for other factors that consistently predict mental health stigma. Negative stereotypes also partially mediated individuals with RWA’s significant relationship to social distance.
Conclusion:
Characteristics of political conservatives and right-wing authoritarians (e.g. threat-aversion, personal responsibility) are predictive of mental health stigma. Terror Management Theory may also help to explain this phenomenon.
Keywords
Negative stereotypes about mental illness, a component of mental health stigma, include beliefs that people with mental illness are dangerous, unpredictable, responsible for their illness and cannot recover (Corrigan, Thompson, Lambert, Noel, & Campbell, 2003). Recent research indicates that stigma toward persons with mental illness remains widespread (Pescosolido, Medina, Martin, & Long, 2013), with some studies suggesting that it may be increasing (Pescosolido et al., 2010). Along with negative stereotypes often come social distancing behaviors (Martin, Pescosolido, & Tuch, 2000). Despite the theoretical connection between negative stereotypes (e.g. believing people with mental illness are dangerous) and discriminatory behaviors (e.g. avoiding living near people with mental illness), the behavioral component of stigma toward individuals with mental illness has been relatively understudied (Parcesepe & Cabassa, 2013).
While the prevalence of mental health stigma is clear, the reasons why people hold stigmatizing attitudes are less well understood. With regard to individual-level correlates of mental health stigma, research has consistently found that female gender (Corrigan & Watson, 2007), prior contact with individuals with mental illness (Corrigan, Edwards, Green, Diwan, & Penn, 2001) and greater education (Phelan & Link, 2004) are associated with less stigma, while Asian-American ethnicity is associated with more stigma and European-American ethnicity is associated with less stigma (WonPat-Borja, Yang, Link, & Phelan, 2012). Another consistent finding has been the relationship between political attitudes and mental health stigma. Self-reported conservative political ideology has been shown to be related to mental health stigma in a variety of ways, with liberal ideologies resulting in less stigmatizing attitudes. Phelan and Link (2004) found political conservatism to be significantly associated with perceived danger from individuals with mental illness. Similarly, Watson, Corrigan, and Angell (2005) found conservative attitudes to be significantly associated with attributing mental illness to bad character.
While previous research has shown a robust relationship between political attitudes and mental health stigma, measuring political attitudes in the social sciences has not been without challenge. Traditional measurements of political attitudes have relied on Likert scales and party affiliation to operationalize political ideology. However, there are potential limitations to these methods, and the consistency and reliability of such measures have been challenged (Everett, 2013). For example, political attitudes may be more complex than a given measure, and individuals may not be accurate political self-reporters (Zell & Bernstein, 2014). Furthermore, there are subsets among all political affiliates, and meaningful clusters should be tapped into and organized for future research.
One particular tool that has been used to assess political attitudes in a more nuanced way is Altemeyer’s (2006) Right-Wing Authoritarianism (RWA) scale, a measure of social attitudes that correlates moderately to highly to both economic and social conservatism (Altemeyer, 1996). What differentiates the RWA scale from traditional scales of conservatism is its ability to describe specific types of political affiliates (usually conservatives), particularly those with submissive, strict norm enforcing and prejudicial characteristics. RWA hinges on three components: authoritarian aggression – aggressiveness toward out-groups; authoritarian submission – a high degree of submission to authorities; and conventionalism – a belief in upholding traditional values and social norms that are set by authorities (Altemeyer, 2006). RWA also correlates highly with religious fundamentalism (Johnson et al., 2011), beliefs about group cohesion (Shaffer & Duckitt, 2013) and beliefs that the world is dangerous (Duckitt, 2006). RWA is largely built on the premise that the world is dangerous (Altemeyer, 1988, p. 147). Such fears culminate into authoritarian aggression and may reflect outward actions and behaviors toward certain groups in society (e.g. Fodor, 2006).
Research indicates that RWA predicts negative attitudes toward marginalized groups in society, including lesbian, gay, bisexual and transgender (LGBT) individuals (Haddock & Zanna, 1998); Middle Eastern groups (Duckitt & Sibley, 2007); and persons living with HIV/AIDS (Von Collani et al., 2010). Although few studies have looked at the relationship between RWA and mental health stigma, the existing research suggests that RWA is associated with greater stigma. Fodor, Wick, Hartsen, and Preve (2008), for example, found that individuals with High RWA recommended harsher sentencing and showed less empathy toward a hypothetical person with schizophrenia than other participants. In a similar study, Fodor (2006) found that individuals with High RWA gave lower evaluations and expressed less comfort with a hypothetical job candidate with schizophrenia in comparison with a ‘Low RWA’ group. Duckitt and Sibley (2007) found a significant negative association between RWA and self-reported warmth toward ‘psychiatric patients’.
Despite evidence that political conservatism and RWA are predictive of mental health stigma, theoretical explanations for this relationship have been seldom proposed. We posit that a variation of Terror Management Theory (TMT; Greenberg, Simon, Pyszcynski, Solomon, & Chatel, 1990) may explain the connection. This theory holds that increases in ‘mortality salience’, or awareness of death, lead individuals to cling strongly to worldviews and personal values. Research has demonstrated that conservative and RWA worldviews are associated with psychological processes for managing fear and uncertainty (Hibbing, Smith, & Alford, 2014; Jost, Kruglanski, Glaser, & Sulloway, 2003; Jost et al., 2007; Lilienfeld & Latzman, 2014). We hypothesize that negatively stereotyping and avoiding people with mental illness (who can be perceived as ‘alien’ or ‘other’) provide people who are high in RWA with a way to manage this fear.
The present study addressed the relative dearth of research on the relationship between political attitudes and mental health stigma by examining the association between RWA and self-reported conservatism, and both the attitudinal (negative stereotypes) and behavioral (social distance) components of mental health stigma. In addition, analyses sought to control for other factors that have been consistently found to be associated with stigma to determine whether RWA remains a robust predictor of stigma when these other factors are accounted for. We hypothesized that, consistent with TMT, RWA would be associated with both negative stereotypes and future social distance and that these relationships would remain statistically significant even when controlling for other variables that consistently predict mental health stigma. Finally, we hypothesized that, consistent with the view that negative stereotypes lead to social avoidance, the endorsement of negative stereotypes would partially mediate the relationship between RWA and future social distance.
Method
Participants
Participants were 505 New York State (NYS) residents, including college students from a large, urban college in New York City, and general community members from Amazon.com’s Mechanical Turk (MTurk) program. College student participants received course credit, while MTurk participants received US$2.00 for completing the survey. To be eligible, potential respondents had to be from NYS (verified through Internet protocol (IP) address and self-report) and be able to speak English well enough to complete the survey.
Procedure
Institutional Review Board (IRB) approval was obtained prior to data collection, and all participants provided informed consent. After providing consent, participants were informed that ‘mental illness’ may refer to diagnoses such as schizophrenia, bipolar disorder, major depressive disorder, posttraumatic stress disorder (PTSD) and panic disorder, and then were presented with a series of scales. The online survey software anonymously recorded all results.
Measures
Demographics
Demographic information was obtained relating to gender, race/ethnicity, age, location (zip code), education level, contact with mental illness (i.e. being personally diagnosed with mental illness or having a family member with a diagnosis) and self-reported political affiliation (i.e. liberal, moderate or conservative). Due to homogeneity in the sample, self-reported political affiliation was dichotomized so that 1 = conservatives and 0 = liberals and moderates. This relative homogeneity was evident between liberals and moderates from scores on the various measures of stigma used in this study. Similarly, based on past research and initial analyses (e.g. amount of variance explained, homogeneity of scores on stigma measures and no significant mean differences between minority race/ethnic groups), race/ethnicity was dichotomized so that 1 = Whites and 0 = all other races/ethnicities. Specific race and ethnicity differences (dichotomized, so that a particular minority race/ethnic group = 1, all other races/ethnicities = 0) are discussed in the Results. Gender was coded so that 0 = male and 1 = female, and contact (prior contact with mental illness = 1, no contact = 0) included individuals reporting having a personal diagnosis or a family member with a diagnosis. Education was split into three groups (dummy coding of these variables did not lead to significant predictions or variance changes in our regression models). Demographic characteristics of the sample are shown in Table 1.
Sample characteristics (N = 505).
Percent indicates the valid percent, not accounting for missing values; not all questions had 505 respondents.
‘Conservatism’ denotes self-reported political conservatism (n = 65 in total sample).
p < .05, **p < .01, ***p < .001.
Social Desirability Scale
The 11-item version of the scale was used for the current study (α = .65) (Crowne & Marlowe, 1960). The purpose of this scale is to distinguish between honest responses and those deemed to be socially desirable. Questions on this scale include true items such as, ‘I sometimes feel resentful when I don’t get my way’. In this study, higher mean scores were indicative of higher social desirability.
Attitudes toward Mental Illness and Its Treatment Scale
Based on a factor analysis by Kobau, DiIorio, Chapman, and Delvecchio (2010), two separate subscales that comprise the Attitudes toward Mental Illness and Its Treatment Scale (AMIS) were assessed – the AMIS 1 (3-item negative stereotypes subscale on danger, unpredictability, and believing a person with mental illness is ‘hard to talk with’; α = .62) and the AMIS 2 (4-item recovery and outcomes subscale on treatment, general recovery, working successfully, and leading normal lives; α = .67). Items were rated using a 1–5 point Likert scale, with higher scores overall indicating a higher amount of stigmatizing attitudes.
Reported and Intended Behaviors Scale
The Reported and Intended Behaviors Scale (RIBS) includes inquiries relating to future interactions with individuals who have a mental illness (Evans-Lacko et al., 2011). The four questions focus on future interactions using a 5-point Likert scale, ranging from 1 (agree strongly) to 5 (disagree strongly). The items demonstrated moderate internal consistency in our sample (α = .83). See Appendix 1 for all stigma-related measure (AMIS 1, AMIS 2, RIBS) questions, means and standard deviations.
RWA scale
The RWA scale is a 20-item measure of authoritarian and conservative values and beliefs (Altemeyer, 2006). Respondents rate each given statement on a 9-point scale from −4 to +4, indicating the degree to which they disagree (more negative) or agree (more positive). For statements in which participants may both agree and disagree with different aspects of said statement, they are asked to score these separately and combine their response scores (e.g. −4 for one part of the question and +1 for another part of the question equals a score of −3).
Following previous research methods (e.g. Altemeyer, 1996; Fodor et al., 2008), an interquartile split was used so that individuals were put into ‘Low RWA’ (bottom 25th percentile of mean scorers) and ‘High RWA’ (top 25th percentile of scorers) categories for further analyses. The RWA scale has been shown to have high internal consistency and a moderate to high test–retest validity. Consistent with previous literature, the 19-item RWA measure in this study had excellent internal consistency (α = .93). Note that 1 item was mistakenly left off the survey due to an input error (‘Our country needs free thinkers who have the courage to defy traditional ways, even if this upsets many people’), but internal consistency remained high.
Data analyses
Bivariate correlations were computed among all variables (see Table 2), including differences by sample (not shown). Data analyses for hypothesis 1 involved an examination of these bivariate correlations, as well as analyses of variance (ANOVAs) to assess group differences on the stigma measures. Our second hypothesis was examined through the use of simultaneous regressions, with AMIS 1, AMIS 2 and RIBS as dependent variables in separate models. Finally, hypothesis 3 was examined through the use of multiple regressions to examine partial mediation. Initial checks were completed to test that assumptions were met for parametric statistical analyses. Individuals completing the survey in less than 5 minutes were removed from analyses.
Correlations for total sample (N = 505).
AMIS: Attitudes toward Mental Illness and Its Treatment Scale; RIBS: Reported and Intended Behaviors Scale; RWA: Right-Wing Authoritarianism.
‘Conservatism’ denotes self-reported political conservatism (n = 65 in total sample).
p < .05, **p < .01, ***p < .001.
Mean imputation was used for four variables: RIBS (original n for respondents completing all questions = 499), both AMIS subscales (ns = 479) and RWA (n = 329). The large amount of non-completed responses in the RWA was believed to be due to a movable scale that was used in the online survey. Respondents who did not manually move the scale (or click on it) from its original position on ‘0’ were counted as not responding, even if 0 (a neutral response) was their desired response. Hence, the researchers in this study manually checked the RWA results for all individuals answering 10 items or more (i.e. more than half of the items answered). Twenty-one such cases were identified and labeled as ‘missing’, resulting in a new n of 484 for RWA.
Results
Based on the correlation coefficients of the total sample (Table 2), results indicated significant relationships among all major variables, except the AMIS 2 recovery and outcomes subscale and conservatism (not significant in any sample). As shown in Table 2, there was also a medium to strong, positive relationship between the two stigma measures – RIBS and AMIS negative stereotype subscale 1. This supports previous research linking cognitive processes to future discriminatory behavior (e.g. Corrigan, 2000; Tajfel, 1969). Also, as can be seen in Table 2, consistent with previous research, RWA and conservatism had a moderate positive, significant relationship (Altemeyer, 2006) (this was present in both samples, but was somewhat more pronounced in the college sample).
Analyses were also conducted to assess whether social desirability had a significant impact on participant responding. In the total sample (Table 2), results indicated significant correlations between social desirability and AMIS 1 (negative stereotypes) (p = .004), and social desirability and RWA (p = .002). Thus, two partial correlations were also imputed. The first partial correlation explored the relationship between AMIS 1 and RWA, controlling for social desirability. There was a small, positive, partial correlation between AMIS 1 and RWA, controlling for social desirability, r = .17, n = 481, p < .0005, with a similar zero-order correlation (r = .15). The second partial correlation explored the relationship between RWA and RIBS, controlling for social desirability. There was a medium, positive, partial correlation between RWA and RIBS, controlling for social desirability, r = .33, n = 481, p < .0005, with a similar zero-order correlation (r = .32). Both findings suggested that despite the statistically significant relationship between RWA and social desirability, controlling for socially desirable responding had very little impact on the relationship between RWA and both stigma variables.
Supporting our first hypothesis, both RWA and self-reported political conservatism had positive, significant relationships with the AMIS 1 negative stereotypes subscale (see Table 2). This indicates that higher RWA scores, as well as self-reported conservatism, were related to more endorsement of negative stereotypes; albeit, both of these relationships were relatively weak. As for the AMIS 2 treatment and recovery subscale, only RWA was negatively, significantly related (this relationship was not statistically significant when restricting analyses to the college sample). Hence, higher RWA scores were related to less endorsement of positive mental health recovery and outcomes. The hypothesized relationship between self-reported political affiliation and AMIS 2 was non-significant and thus not supported in any of the groupings. Also, consistent with hypothesis 1, there was a medium, positive relationship between the RWA scale and RIBS subscale on future and intended behaviors, indicating that higher scores on the RWA were associated with higher endorsement of intended discrimination. RWA explained about 9% of the variance in participant’s scores on the RIBS among the whole sample. As expected, there was also a significant, positive relationship between conservatism and RIBS.
Our first hypothesis was further examined through one-way between-groups ANOVAs. Several separate ANOVAs were conducted to examine the relationship between political attitudes (self-reported and RWA) and AMIS 1, AMIS 2 and RIBS measures of stigma. In Table 3, results are displayed from three ANOVAs conducted to examine political attitudes, with AMIS 1, AMIS 2 and RIBS as the dependent variables. When exploring self-reported political conservatism, a statistically significant main effect was revealed for AMIS 1 and RIBS. No significant main effect was found for AMIS 2. Using Tukey post hoc analyses for the AMIS 1 analysis, post hoc comparisons indicated significant mean differences between conservatives and moderates (p = .016), and conservatives and liberals (p = .008). No significant differences were found between liberals and moderates. Using Tukey analyses for the RIBS analysis, post hoc comparisons indicated significant mean differences between conservatives and moderates (p = .008), and marginally significant differences between conservatives and liberals (p = .091). No significant differences were found between liberals and moderates. Since uneven groups were used in this comparison, additional post hoc tests were used to verify this relationship. Hochberg G2 test and Games–Howell test (used for unequal groups), respectively, also supported these significant differences. Overall, as hypothesized, conservatives scored statistically significantly higher on both the AMIS 1 and RIBS stigma measures (the hypothesis related for AMIS 2 was not supported). The effect size (calculated using eta squared) for both was close to .02, a small effect (Cohen, 1988).
Means and standard deviations (SDs) for responses to Mental Health Stigma Scales.
AMIS: Attitudes toward Mental Illness and Its Treatment Scale; RIBS: Reported and Intended Behaviors Scale; ns: not significant; M: mean.
p values indicate main effects. For the whole sample, total average score was 3.15 on AMIS 1 (SD = .741), 3.94 on AMIS 2 (SD = .597), and 2.28 on RIBS (SD = .873). Scale ranged from 1 (strongly disagree) to 5 (strongly agree) for AMIS 1 and 2, and 1 (strongly agree) to 5 (strongly disagree) for RIBS. A response of 3 represented neutral on all scales.
‘Conservatism’ denotes self-reported political conservatism (n = 65 in total sample).
p < .05, **p < .01, ***p < .001.
In Table 4, results are displayed from three ANOVAs conducted to examine RWA, with AMIS 1, AMIS 2 and RIBS as the dependent variables. When exploring RWA (ranked into four categories by score), a statistically significant main effect was revealed for AMIS, AMIS 2 and RIBS. A Tukey post hoc for AMIS 1 revealed significant differences between the Low and High RWA groups (p = .006); a Tukey post hoc for AMIS 2 also revealed significant differences between the Low and High RWA groups (p = .009); and a Tukey post hoc for RIBS revealed significant differences between the Low and High RWA groups (p < .001). Overall, as hypothesized, higher RWA scores led to more endorsements of stigma on all measures, relative to lower RWA scores. This relationship was on a gradient, whereby stigma endorsement gradually increased as RWA scores increased. The effect sizes (calculated using eta squared) for AMIS 1 and AMIS 2 were close to .03, a small effect, while the effect size for RIBS was close to .10, a medium to large effect.
Means and standard deviations (SDs) for responses to Mental Health Stigma Scales.
AMIS: Attitudes toward Mental Illness and Its Treatment Scale; RIBS: Reported and Intended Behaviors Scale.
See Table 3. Low–middle RWA indicates the 25% of scorers above ‘Low RWA’, while high–middle indicates the 25% of scorers directly below ‘High RWA’.
To explore our second hypothesis, several simultaneous regressions were used to investigate whether conservatism and RWA remained significant predictors of the three stigma measures when controlling for other factors (see Tables 5 and 6). The use of social desirability as an independent variable was not significant in any of the models and is thus not shown.
Conservatism as a predictor of mental health stigma.
AMIS: Attitudes toward Mental Illness and Its Treatment Scale; RIBS: Reported and Intended Behaviors Scale; β: beta standardized coefficient; T: t-statistic
Three separate regression models represented. R-squared for AMIS 1 (.05), AMIS 2 (.04), and RIBS (.09).
p < .08; **p < .05; ***p < .01.
Right-Wing Authoritarianism (RWA) as a predictor of mental health stigma.
AMIS: Attitudes toward Mental Illness and Its Treatment Scale; RIBS: Reported and Intended Behaviors Scale; β: beta standardized coefficient; T: t-statistic
Three separate regression models represented. R-squared for AMIS 1 (.05), AMIS 2 (.05), RIBS (.15).
p < .08; **p < .05; ***p ⩽ .01.
The first set of regressions (Table 5) explored the predictive contribution of self-reported conservatism, race/ethnicity, contact, gender, age and education. Conservatism was the second strongest predictor in the AMIS 1 model (behind gender) and the third strongest predictor in the RIBS model (behind contact and race/ethnicity). Contact was seen as the most robust, consistent predictor in all of these models. White race/ethnicity was a significant predictor in the RIBS and AMIS 2 models. Gender was only significant in the AMIS 1 model. Overall, conservative political attitudes predicted endorsement of both negative stereotypes and social distance, even when controlling for other variables. Arguably, the strongest predictor of stigma in these models was contact: Individuals reporting having a personal diagnosis or a family member with a diagnosis were less likely to endorse any stigma, across all measures. Additionally, participants from specific racial and ethnic minority groups predicted negative recovery attitudes (i.e. Hispanic/Latino(a) ethnicity) and social distance endorsement (i.e. Asian-American ethnicity). White respondents had the lowest endorsement of stigma for recovery attitudes and social distance endorsement (compared to minority groups). Male gender predicted more negative stereotype endorsement in these self-reported political attitude models.
Next, the same procedure was used but with RWA substituted as a predictor variable for self-reported conservatism (Table 6). All models were again significant: AMIS 1, AMIS 2 and RIBS. RWA was the strongest predictor of stigma in the AMIS 1 and RIBS models, and the second strongest predictor in the AMIS 2 model. Overall, right-wing authoritarian attitudes predicted a wide range of stigma (i.e. negative stereotypes, negative recovery attitudes (p = .063), and social distance), even when controlling for other factors. Again, contact was also a significant inverse predictor for social distance. Similar to the models in Table 5, participants from specific racial and ethnic minority groups predicted negative recovery attitudes (i.e. Hispanic/Latino(a) ethnicity) and social distance endorsement (i.e. Asian-American ethnicity). White respondents had the lowest endorsement of stigma for recovery attitudes and social distance endorsement (compared to minority groups). Finally, male gender predicted more negative stereotype endorsement.
Our third hypothesis, that negative stereotypes would mediate the relationship between RWA and social distance, was then explored through mediation analysis (see Figure 1). As hypothesized, the relationship between RWA and social distance (RIBS) was partially mediated by negative stereotypes (AMIS 1). A Sobel test was also conducted, supporting the finding of partial mediation (p < .0001). As Figure 1 illustrates, the standardized regression coefficient between RWA and RIBS decreased by .05 when controlling for AMIS. The other conditions were also met for mediation: RWA was a significant predictor of RIBS and AMIS, and AMIS was a significant predictor of RIBS. When considering the mediated effect, for every 1 standard deviation (SD) increase in RWA, a .064 increase in RIBS is predicted through the mediating variable of AMIS. In terms of explained variance for these models, RWA individually explained over 10% of the variance in RIBS, while RWA and AMIS 1 together explained 23% of the variance in RIBS.
Standardized regression coefficients (betas (β)) for the relationship between RWA and social distance as mediated by negative stereotypes. The standardized regression coefficient between RWA and RIBS controlling for negative stereotypes is in parentheses.
Discussion
Our first hypothesis, that self-reported conservatives and High RWA individuals would endorse the most stigma, was partially supported. There are several reasons for why mental health stigma occurs, but political attitudes seem to be an important part of the stigma dynamic. The link between self-reported conservatism and negative stereotype endorsement was replicated (Gonzales, Chan, & Yanos, in press) and extended to RWA. Particular endorsement of social distance by individuals with RWA suggests that these individuals may have a visceral reaction to persons with mental illness that may be better assessed on scales like the RIBS, rather than cognitive–attitudinal scales.
Our second hypothesis, that these relationships would remain significant even when controlling for other factors, was also partially supported. Across the measures of stigma in this study, RWA proved to be a stable and robust predictor of stigmatizing attitudes and future behaviors toward individuals with mental illness. In the regression models, previous contact with mental illness was one of the strongest predictors for recovery attitudes and social distance; however, conservatism was a stronger predictor of negative stereotypes than contact. While self-reported political affiliation, to some extent, may dictate one’s future behavior toward individuals with mental illness, these findings suggest that having a personal mental health diagnosis or a family member with a diagnosis can supersede these attitudes. Moreover, being a male, of younger age, and of a minority racial or ethnic group – also significant predictors in these models – may additionally complicate any direct relationship of conservatism to stigma.
Finally, our third hypothesis (that negative stereotypes would partially mediate the relationship between political attitudes and social distance) was also supported. Previous research (Evans-Lacko et al., 2011) has shown that even though commonly used cognitive-based scales of stigma may measure both attitudes and behaviors, the two constructs are not disaggregated as separate from each other. This hypothesis aided in the disentanglement of these phenomena. While RWA is significantly related to RIBS, endorsements of negative stereotypes accounted for a substantial proportion of this relationship. Previous research has supported links between threats and negative attitudes as mediators of potential future stigmatizing behavior (Corrigan et al., 2001). As stated previously, it was believed that persons with mental illness activated hostility in individuals with RWA. This hostility was ostensibly activated because of a personal threat (e.g. perceived harm to self; Duckitt, 2006). Thus, persons with RWA did not want to socially associate with persons with mental illness (RIBS) and also endorsed negative stereotypes (AMIS 1), providing some evidence for threat activation leading to stigma. While it is presumed that negative stereotypes precede social distancing, it is possible that social distancing causes negative stereotype endorsement, in order for persons with RWA to justify their social distance. Overall, wide endorsement of stigma by individuals with RWA, as well as conservatives’ general endorsement of stigma, points to a possible conclusion that these groups harbor hostility toward individuals with mental illness. This is consistent with our theoretical extension of TMT discussed above: that conservatives and individuals with RWA see individuals with mental illness as a threatening feature of the environment that should be avoided.
It should be emphasized that the data are correlational and it is possible that the direction of the relationship operates in the opposite direction in reality (i.e. avoidance of people with mental illness leads one to endorse more RWA views and identify as politically conservative). However, this interpretation runs counter to the idea that political views are often central to one’s worldview and rooted in early development (Block & Block, 2006). Similarly, it is also possible that both RWA views and mental health stigma are related to some other, unmeasured variable.
Despite the documented relationship between RWA attitudes and stigma, it should be noted that these attitudes and behaviors are not always fixed, and may be malleable and flexible, depending on contextual, situational or other personal factors (Hibbing et al., 2014; Shaffer & Duckitt, 2013). Moreover, RWA and support for stigma are not always ‘automatic and reflexive’ and ‘can be trumped’ (Altemeyer, 2006, p. 16). In line with Altemeyer’s (2006) terming of ‘visible minorities’ (p. 242), contact is paramount to reduce stigma, particularly for individuals high on RWA and endorsing conservative beliefs. The more positive interactions and portrayals of mental illness one is exposed to, the less chance of stigma. Previous research has shown that the relationship between RWA and stigma can decrease over time, especially if leaders and authority figures become less inclined to express prejudice openly (Chong, 1994). For example, the relationship between RWA and ethnic/racial prejudice has decreased over time (Childs, 2011), suggesting that the views of authority figures and social norms, along with other social contextual factors, can change attitudes of people high in RWA. Therefore, changing widespread social norms can lead to a change in social behavior and interactions.
Our findings should be interpreted with some limitations in mind. First, the data are from only NYS residents, and respondents primarily identified as liberals and moderates. Although the self-reported conservative group was small – and given the aforementioned literature on the limitations of self-report – our High RWA group seemed to serve as an adequate proxy. Finally, our sample was not representative of NYS residents (i.e. convenience, non-probability sample) and included both college students from a single institution and community members frequenting an online crowdsourcing website. Future research should employ more nationally (and locally) representative samples. An additional limitation may also be the broad definition of ‘mental illness’. While it was defined for participants, past studies have shown differences in stigma depending on diagnosis (Martin et al., 2000).
Future research may extend upon our findings to identify which aspects of right-wing groups most clearly relate to stigma (e.g. fear and threat-aversion, terror management activation, personal responsibility, traditional values, rigidity in beliefs, authoritarianism). This may also help to guide anti-stigma intervention efforts. As a reflection of one’s values and worldviews, political ideologies and political attitudes may induce the development of stigmatizing attitudes and behaviors toward certain groups. On a micro-level, political attitudes can result in stigmatizing interactions and behaviors toward individuals with mental illness in the community (Segal, Baumohl, & Moyles, 1980). On a macro-level, political attitudes can result in the formation of discriminatory laws and policies toward individuals with mental illness (Corrigan & Watson, 2003; Link & Phelan, 2001). Since individuals high on RWA are more likely to submit to authorities, areas with a highly dominating and prejudicial leader, along with many High RWA inhabitants, could spell out acceptance of stigma. As researchers begin to understand more fully how stigma develops, initiatives and research can begin to look at creating target-based methods to reduce mental health stigma in society and mitigate the occurrence of individual-community stigma and structural stigma related to political attitudes.
Footnotes
Appendix
Stigma measure items, means and standard deviations (SDs).
| Attitudes toward Mental Illness: Negative Stereotypes (AMIS 1) | Mean | SD |
|---|---|---|
| I believe a person with mental illness is a danger to others. | 2.97 | 1.03 |
| I believe a person with mental illness is unpredictable. | 3.67 | .91 |
| I believe a person with mental illness is hard to talk with. | 2.80 | .99 |
| Attitudes toward Mental Illness: Recovery (AMIS 2) | Mean | SD |
| I believe a person with mental illness would improve if given treatment and support. | 4.29 | .75 |
| I believe a person with mental illness can eventually recover. | 3.55 | .96 |
| I believe a person with mental illness can be as successful at work as others. | 3.83 | .89 |
| Treatment can help people with mental illness lead normal lives. | 4.10 | .76 |
| Reported and Intended Behavior Scale (RIBS) | Mean | SD |
| In the future, I would be willing to live with someone with a mental health problem. | 3.00 | 1.14 |
| In the future, I would be willing to work with someone with a mental health problem. | 2.17 | 1.07 |
| In the future, I would be willing to live nearby to someone with a mental health problem. | 2.24 | 1.09 |
| In the future, I would be willing to continue a relationship with a friend who developed a mental health problem. | 1.72 | 1.02 |
Total sample mean and SD for AMIS 1 (3.15, .74), AMIS 2, (3.94, .60) and RIBS (2.28, .87). AMIS scales ranged from 1 (strongly disagree) to 5 (strongly agree), where 3 indicates neither agreement nor disagreement. RIBS scale ranged from 1 (strongly agree) to 5 (strongly disagree), where 3 indicates a neutral response.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.