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flexibility components of religiosity to predict racial and value-violating prejudice: A Post-Critical Belief Scale analysis
Personality and Individual Differences 54 (2013) 389–395
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Disentangling the belief in God and cognitive rigidity/flexibility components of religiosity to predict racial and value-violating prejudice: A Post-Critical Belief Scale analysis Megan Johnson Shen a,⇑, Logan A. Yelderman b, Megan C. Haggard c, Wade C. Rowatt c a b c
Mount Sinai School of Medicine, New York, NY, United States University of Nevada, Reno, Reno, NV, United States Baylor University, Waco, TX, United States
a r t i c l e
i n f o
Article history: Received 5 August 2012 Received in revised form 5 October 2012 Accepted 8 October 2012 Available online 14 November 2012 Keywords: Religiosity Prejudice Cognitive rigidity/flexibility Belief in God Post-critical beliefs
a b s t r a c t Past research indicates that being religious is associated with prejudice toward racial and value-violating out-groups. However, this past research treated religiosity as a unidimensional construct without taking into account how different components of religiosity—belief in a higher power and the rigidity/flexibility of religious beliefs—are associated with measures of prejudice. Two studies examined the relationship between these two components of religiosity, as measured by the Post-Critical Beliefs Scale, and racial (African Americans, Arabs) and value-violating prejudices (atheists, gay men). As the flexibility of religious beliefs increased (literal vs. symbolic dimension), attitudes toward racial and value-violating out-groups became more positive (Study 1). As belief in God strengthened (exclusion vs. inclusion of transcendence dimension), attitudes toward value-violating out-groups became more negative. Study 2 demonstrated that these two components of religiosity fully mediated the relationship between general religiosity and prejudice toward African Americans, Arabs, and gay men and partially mediated the relationship between religiosity and prejudice toward atheists. Results are discussed in light of reexamining the conclusion that simply being religious is associated with prejudice. Ó 2012 Published by Elsevier Ltd.
1. Introduction Because measures of religiosity have been associated with prejudice toward racial (Hall, Matz, & Wood, 2010) and value-violating (Whitley, 2009) out-groups across multiple studies, most researchers have concluded that simply being religious is associated with prejudice. One limit of this conclusion is that it assumes religiosity is a unidimensional construct. However, religiosity is a multidimensional construct with at least two components. One component of religiosity involves the degree of belief in God or a higher power (i.e., the belief in God component). A second component of religiosity involves how one holds that belief (i.e., the cognitive rigidity/flexibility component). To understand better the associations between general religiosity and prejudice, it is necessary to take into account both components. To our knowledge, no single study has assessed how the degree of belief in God and the rigidity of that belief predict prejudicial attitudes separately. Some research has examined cognitively rigid ideologies as mediators of the relationship between religiosity and ⇑ Corresponding author. Address: Mount Sinai School of Medicine, Department of Oncological Sciences, One Gustave L. Levy Place, Box 1130, NY 10029, United States. Tel.: +1 212 659 5678; fax: +1 212 849 2566. E-mail address: [email protected] (M.J. Shen). 0191-8869/$ - see front matter Ó 2012 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.paid.2012.10.008
prejudice (Brandt & Reyna, 2010; Hill, Cohen, Terrell, & Nagoshi, 2010; Johnson, Labouff, Rowatt, Patock-Peckham, & Carlisle, 2012; Johnson et al., 2011), but some ideological measures utilized—such as religious fundamentalism—entangle the belief in God and cognitive rigidity/flexibility components of religion within their items. Whether a person believes in a higher power (i.e., belief in God) and how one holds religious beliefs (i.e., cognitive rigidity/flexibility) need to be assessed separately to examine how each influences prejudices. 1.1. Religiosity, cognition, and prejudice The ways in which individuals process beliefs accounts for religiosity’s association with prejudice better than belief in God. For instance, cognitively rigid or closed-minded ideologies, such as right-wing authoritarianism (RWA) and religious fundamentalism (RF), have been shown to fully mediate the relationship between general religiosity and prejudice toward African Americans and gay men (Johnson et al., 2011). Moreover, RWA (Johnson et al., 2012), need for cognition and preference for consistency (Hill et al., 2010), and need for closure (Brandt & Reyna, 2010) have all been shown to mediate the relationship between RF and racial and value-violating prejudices. Although these studies examined the cognitive rigidity/flexibility component of religiosity, they did
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not consider both the belief in God and cognitive rigidity/flexibility components of religiosity as potential mediators of the religiosity– prejudice relationship.
racial (African American, Arab) and value-violating (gay men, atheists) prejudices.
1.2. Post-critical beliefs and prejudice
2.1. Method
The Post-Critical Beliefs Scale (PCBS; Duriez, Soenens, & Hutsebaut, 2005; Hutsebaut, 1996) allows researchers to disentangle the belief in God and cognitive rigidity/flexibility components of religiosity. The PCBS is rooted in the following two dimensions of religion posited by Wulff (1991): (1) exclusion versus inclusion of transcendence, representing the belief in God component of religion, and (2) literal versus symbolic, representing the cognitive rigidity/flexibility component of religion. Interactions between these two dimensions produce four distinct approaches to religion: (1) orthodoxy (literal, transcendent), (2) external critique (literal, non-transcendent), (3) second naiveté (symbolic, transcendent), and (4) relativism (symbolic, non-transcendent). Previous research has examined post-critical beliefs’ relationship with racial prejudice. Orthodoxy and external critique, both associated with the literal dimension of the PCBS, were positively correlated with racism (Duriez, Fontaine, & Hutsebaut, 2000; Duriez & Hutsebaut, 2000; Duriez, Luyten, Snauwaert, & Hutsebaut, 2002). Relativism, marked by symbolic beliefs, was negatively correlated with racism. Second naiveté was uncorrelated with racism. These results indicate that how one holds one’s religious beliefs (literal vs. symbolic) plays a more important role in the expression of prejudice than whether one believes in a higher power. Post-critical beliefs were examined as mediators of the relationship between age, education, church attendance, and belief salience on the one hand and racial prejudice on the other hand (Duriez & Hutsebaut, 2000). Within this model, church attendance and belief salience had no direct effects on racial prejudice but did have small indirect effects through their influence on post-critical beliefs.
2.1.1. Participants Two hundred seventy-nine Americans (73 males, 186 females, 20 missing; M age = 32.58 years, SD = 11.84) completed an online survey. Our sample consisted of: 72.0% White, 7.5% African American, 5.7% Asian/Pacific Islander, 3.9% Hispanic, 2.2% ‘‘other,’’ 1.8% Native American, and 6.8% unspecified. The sample consisted of the following self-reported religious affiliations: 29.7% ‘‘no religion,’’ 19.4% Protestant, 18.6% Catholic, 16.5% ‘‘other,’’ 5% Jewish, 2.5% Buddhist, 1.4% Hindu, and 6.8% missing.
1.3. The present studies The goals of the present studies were to examine post-critical belief dimensions as predictors of racial and value-violating prejudices and as mediators of the general religiosity–prejudice relationship. Although the cognitive rigidity/flexibility components of post-critical beliefs (literal vs. symbolic) have been strong predictors of racial prejudice (Duriez & Hutsebaut, 2000; Duriez, Hutsebaut, & Roggen, 1999), it is likely the belief in God component of post-critical beliefs (exclusion vs. inclusion of transcendence) also plays a role in predicting value-violating prejudices. Multiple measures of religiosity are consistently associated with prejudice toward gay men/lesbian women (Whitley, 2009) and these out-groups violate religious beliefs themselves. Based on past research, we formulated three main hypotheses. First, we predicted the cognitive rigidity/flexibility component of religiosity (literal vs. symbolic; higher values indicating more symbolic beliefs) would predict tolerance toward racial (African American, Arab) and value-violating (gay men, atheists) out-groups (Hypothesis 1). Second, we predicted the belief in God component of religiosity (exclusion vs. inclusion of transcendence; higher values indicating higher belief in God) would predict prejudice toward value-violating out-groups (Hypothesis 2). Finally, in Study 2 we predicted that both post-critical belief dimensions would fully mediate the relationship between general religiosity and prejudice toward racial and value-violating out-groups (Hypothesis 3). 2. Study 1 In Study 1, we examined the relationships between the belief in God and cognitive rigidity/flexibility components of religiosity and
2.2. Procedure and measures Data were collected from across the US from Amazon’s Mechanical Turk (MTurk) website, which has been shown to provide reliable and more diverse data than college samples (Behrend, Sharek, Meade, & Wiebe, 2011; Buhrmester, Kwang, & Gosling, 2011) and to be a valuable, reliable data collection tool for researchers (Mason & Suri, 2012). The survey was accessible only to American participants, and they received $0.15 in exchange for their completion of the 116-item online survey.
2.2.1. Post-Critical Beliefs Scale (PCBS) Post-critical beliefs were measured with an 18-item short form of the Post-Critical Beliefs Scale (PCBS; Duriez et al., 2005). The four PCBS subscale scores (orthodoxy, second naiveté, external critique, and relativism) were computed and used to generate scores on the belief and literalism dimensions, as follows: Exclusion vs. inclusion = (orthodoxy + second external critique relativism) Literal vs. symbolic = (relativism + second orthodoxy external critique)
naiveté naiveté
The two dimensions that resulted were highly correlated (r = .97–.98) with similar dimensions derived from Principal Component Analysis and orthogonal Procrustes rotations previously used (cf. Duriez, 2003, 2004). Higher values on the exclusion vs. inclusion dimension indicate higher levels of inclusion of transcendence. Higher values on the literal vs. symbolic dimension indicate higher levels of symbolic interpretation of religion.
2.2.2. Prejudice measures Prejudice was measured with reported levels of comfort with social proximity to atheists, gay men, Arabs, and African Americans (1 = not at all comfortable, 3 = comfortable; Bogardus, 1933). All items were reverse-scored, aggregated, and averaged so that higher scores indicated higher levels of prejudice.
2.3. Results and discussion 2.3.1. Descriptive statistics Please see Table 1 for descriptive statistics, Cronbach’s a, and intercorrelations of the various measures.1 1 Due to low internal consistency of second naiveté (Cronbach’s a = .52), the item that accounted for this low reliability was removed (‘‘The Bible is a rough guide in the search for God, and not a historical account’’). Data from the new subscale, composed of three items, were internally consistent (Cronbach’s a = .83).
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M.J. Shen et al. / Personality and Individual Differences 54 (2013) 389–395 Table 1 Zero-order correlations and descriptive statistics for PCBS and prejudice measures (Study 1). Measure
1
1. Gender (dummy-coded, 0 = female, 1 = male) 2. Race (dummy-coded, 0 = non-white, 1 = white) 3. Age 4. Socioeconomic status 5. Exclusion vs. inclusion 6. Literal vs. symbolic 7. Social distance – atheists 8. Social distance – gay men 9. Social distance – Arabs 10. Social distance – African Americans
– .05 .02 .03 .03 .03 .06 .25** .11 .22**
2
3
4
5
6
7
8
9
10
M
SD
a
.45 .45 11.84 .88 4.76 2.60 .61 .62 .63 .49
– – – – – –
–
.28 (%) .72 (%) 32.58 3.23 .35 3.17 1.43 1.46 1.53 1.33
– .11 .01 .09 .00 -.06 .08 .04 .10
– .05 .09 .17** .11 .14* .12* .08
– .04 .03 .01 .03 .05 .13*
– .24** .56** .44** .26** .05
– .02 .03 .07 .11
– .66** .62** .38**
– .45** .38**
– .64**
.90 .89 .90 .85
Note: PCBS = Post-Critical Beliefs Scale. * p < .05. ** p < .01. Single-item measure.
Table 2 Two-step regression of prejudice toward atheists on demographics and PCBS (Study 1). Predictor variables
Gender (0 = female, 1 = male) Race (0 = non-white, 1 = white) Age Socioeconomic status Exclusion vs. inclusion Literal vs. symbolic R2 F R2 change
Model 1 (base model)
Model 2 (PCBS added)
b (s.e.)/Stan. b
t
b (s.e.)/Stan. b
t
.04 (.09)/.03 .06 (.10)/ .04 .01 (.00)/.11 .00 (.05)/.00 – – .02 .90, n.s.
.47 .66 1.74 .03 – –
.01 (.07)/.01 .01 (.08)/.00 .01 (.00)/.08 .01 (.04)/ .02 .07 (.01)/.57 .03 (.01)/ .14 .31 17.67** .30**
.19 .06 1.47 .29 10.05*** 2.47*
Note: PCBS = Post-Critical Beliefs Scale. * p < .05. ** p < .01. *** p < .001.
2.3.2. Predicting prejudice with post-critical beliefs To examine if the two components of post-critical beliefs predicted prejudice, hierarchical regression analyses were run. In the first step, demographic control variables were added as predictors of prejudice. In the second step, the two dimensions of the PCBS were added as predictors. As predicted, post-critical beliefs explained a significant amount of additional variance in predicting prejudice toward atheists, gay men, and Arabs, but not in predicting prejudice toward African Americans (see Tables 2–5).2 Hypothesis 1 was partially supported. The cognitive rigidity/ flexibility component of religiosity (literal vs. symbolic) was most important in predicting tolerance toward both value-violating and racial prejudices. The literal vs. symbolic dimension was negatively associated with prejudice toward atheists (b = .14, p < .05; see Table 2), marginally negatively associated with prejudice toward gay men (b = .10, p = .09; see Table 3), and negatively associated with prejudice toward Arabs (b = .15 p < .05; see Table 4) and African Americans (b = .03, p < .05; see Table 5). Hypothesis 2 was fully supported. The belief in God component of religiosity (exclusion vs. inclusion of transcendence) was most important in predicting prejudice toward value-violating outgroups. Exclusion vs. inclusion of transcendence was positively associated with prejudice toward atheists (b = .57, p < .001; see Table 2) and gay men (b = .47, p < .001; see Table 3). The exclusion vs. inclusion of the transcendence dimension was also positively
2
Moderated regression analyses were run to examine if there was a significant interaction between inclusion and symbolism. Because this interaction was not significant in predicting any of the prejudices, it was excluded from all analyses reported.
associated with prejudice toward Arabs (b = .26, p < .001; see Table 4). This association may have occurred due to individuals inaccurately equating ‘‘Arabs’’ with ‘‘Muslims,’’ in which case they might be viewed as a value-violating out-group. Future research is needed to examine this hypothesis. All other predictors of the varying prejudices are reported in Tables 2–5. 3. Study 2 In Study 2, we tested the hypothesis that post-critical beliefs would fully mediate the relationship between general religiosity and racial and value-violating prejudices (Hypothesis 3). 3.1. Method 3.1.1. Participants Two hundred ninety Americans (109 males, 149 females, 32 missing; mean age = 34.68 years, SD = 12.98) completed an online survey. The sample was comprised of the following ethnicities: 71.4% White, 8.3% Asian/Pacific Islander, 5.2% African American, 2.1% Hispanic, 1.4% ‘‘other,’’ 1.4% Native American, and 10.3% missing. The sample was comprised of the following self-reported religious affiliations: 27.6% ‘‘no religion,’’ 21% Protestant, 17.2% ‘‘other,’’ 16.9% Catholic, 2.8% Jewish, 2.4% Hindu, 1.4% Buddhist, 0.3% Muslim, and 10.3% unspecified. 3.2. Procedure and measures An online survey was administered to individuals from across the US using Amazon’s Mechanical Turk (MTurk) website. As in
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M.J. Shen et al. / Personality and Individual Differences 54 (2013) 389–395 Table 3 Two-step regression of prejudice toward gay men on demographics and PCBS (Study 1). Predictor variables
Model 1 (base model) b (s.e.)/Stan. b
Gender (0 = female, 1 = male) Race (0 = non-white, 1 = white) Age Socioeconomic status Exclusion vs. inclusion Literal vs. symbolic R2 F R2 change
Model 2 (PCBS added) t
b (s.e.)/Stan. b 3.56*** 1.63 2.37* .25 – –
.29 (.08)/.21 .09 (.08)/ .06 .01 (.00)/.12 .00 (.04)/.00 .06 (.01)/.47 .02 (.01)/ .10 .29 15.97** .21**
b (s.e.)/Stan. b
t
b (s.e.)/Stan. b
.11 .07 .01 .03 – – .03 1.78
1.19 .68 2.02* .72 – –
.09 (.09)/.06 .10 (.09)/.07 .01 (.00)/.13 .03 (.04)/.04 .05 (.01)/.26 .04 (.02)/ .15 .10 4.39** .07**
.31 (.09)/.22 .15 (.09)/ .10 .01 (.00)/.15 .01 (.05)/.02 – – .08 5.40***
t 3.79*** 1.05 2.14* .01 8.25*** 1.69
Note: PCBS = Post-Critical Beliefs Scale. p < .10. * p < .05. ** p < .01. *** p < .001.
Table 4 Two-step regression of prejudice toward Arabs on demographics and PCBS (Study 1). Predictor variables
Gender (0 = female, 1 = male) Race (0 = non-white, 1 = white) Age Socioeconomic status Exclusion vs. inclusion Literal vs. symbolic R2 F R2 change
Model 1 (base model)
(.09)/.08 (.10)/.04 (.00)/.13 (.05)/.05
Model 2 (PCBS added) t 1.02 1.08 2.05* .64 4.11*** 2.27*
Note: PCBS = Post-Critical Beliefs Scale. * p < .05. ** p < .01. *** p < .001.
Table 5 Two-step regression of prejudice toward African Americans on demographics and PCBS (Study 1). Predictor variables
Gender (0 = female, 1 = male) Race (0 = non-white, 1 = white) Age Socioeconomic status Exclusion vs. inclusion Literal vs. symbolic R2 F R2 change
Model 1 (base model)
Model 2 (PCBS added)
b (s.e.)/Stan. b
t
b (s.e.)/Stan. b
.21 (.07)/.19 .12 (.08)/.10 .00 (.00)/.07 .07 (.04)/.13 – – .07 4.40**
2.99** 1.55 1.09 2.06* – –
.20 (.07)/.18 .13 (.08)/.11 .00 (.00)/.08 .07 (.04)/.13 .01 (.01)/.08 .03 (.01)/ .13 .09 3.75** .02, n.s.
t 2.89** 1.67 1.30 2.08* 1.21 2.03*
Note: PCBS = Post-Critical Beliefs Scale. p < .10. * p < .05. ** p < .01.
Study 1, only American participants could access the survey and they received $0.15 in exchange for their completion of the 124item survey. 3.2.1. Religiosity Religiosity was measured as a latent variable with three indicators: intrinsic religiosity, religious behaviors, and general religiosity (see Fig. 1). Intrinsic religious orientation was measured using the Religious Orientation Scale (Allport & Ross, 1967), which measures religion inherently important to individuals. Religious behaviors were measured by standardizing, aggregating, and averaging
responses to questions about three indicators of religious behaviors: (1) religious service attendance, (2) reading of sacred texts, and (3) prayer/meditation (cf. Rowatt, LaBouff, Johnson, Froese, & Tsang, 2009). Finally, a single-item measure was used to assess general religiosity (i.e., ‘‘To what extent do you consider yourself a religious person?’’; 1 = not at all, 7 = very much).
3.2.2. Post-Critical Beliefs Scale (PCBS) Post-critical beliefs were measured with the same 18-item short form of the Post-Critical Beliefs Scale (PCBS; Duriez et al.,
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------- Direct paths Mediated paths .286*
Intrinsic Religiosity
Religious Behaviors
Prejudice toward atheists
General Religiosity
.350**
Exclusion vs. Inclusion .952***
.927***
.271*
Prejudice toward gay men
.918*** .877*** -.136* -.133*
Religiosity .282***
Prejudice toward Arabs
Literal vs. Symbolic
-.187**
-.169**
Prejudice toward African Americans
Fig. 1. Model depicting mediation effects of post-critical beliefs on religiosity and prejudice toward atheists, gay men, Arabs and African Americans. Standardized coefficients are shown. Please note: Selected Fit Indexes: v2 (12, N = 290) = 27.74, p < .001 [CFI = 0.991, TLI/NNFI = 0.974, RMSEA = 0.067 (CI90: .034, .100)]. Non-significant paths for indirect effects were not drawn. ⁄p < .05, ⁄⁄p < .01, ⁄⁄⁄p < .001.
2005) used in Study 1. Exclusion vs. inclusion and literal vs. symbolic dimensions were created as in Study 1.3 3.2.3. Prejudice measures The same social distance scales (Bogardus, 1933) utilized in Study 1 to measure prejudice were utilized in this study. 3.3. Analytic procedure A base model was fit using MPlus (v. 5.20; Muthén & Muthén, 2012) testing PCBS dimensions as mediators of prejudice (see Fig. 1). The residuals of the mediators were allowed to correlate with each other. Full information maximum likelihood (FIML) estimation was used to handle missing data. Model fit was evaluated by examining the following four estimates: (1) the chi-square (v2) goodness-of-fit, (2) the root mean square error of approximation (RMSEA; Browne & Cudeck, 1993), (3) the Tucker Lewis Index (TLI), also known as the Non-Normed Fit Index (NNFI), and (4) the Comparative Fit Index (CFI; Bentler, 1990). In the present analysis, MacKinnon, Lockwood, and Williams (2004) method for statistical mediation was utilized. This technique has been found to produce unbiased mediation estimates (Cheung & Lau, 2008). 3.4. Results and discussion See Table 6 for Cronbach’s a, descriptive statistics, and correlations between all variables. The path model is reported in Fig. 1 with all significant paths present in the base model that was tested. 3.4.1. Overall model fit The model chi-square was significant [v2 (12) = 27.740, p < .01]; however, the chi-square statistic has been shown to be sensitive to sample size and not a satisfactory indicator of model fit (Fan, Thompson, & Wang, 1999). According to other measures of fit, the hypothesized model appears to fit the data well. The RMSEA value, compensating for the effects of model complexity, was 3 Data obtained from the second naiveté (Cronbach’s a = .37) subscale had low internal consistency, so we removed the same item as in Study 1which accounted for this low reliability. Data from the new subscale, composed of three items, were internally consistent (Cronbach’s a = .84).
.067 (CI90: .034, .100), indicating acceptable fit of less than .08 (Browne & Cudeck, 1993). The value of the TLI/NNFI was .974 and the value of the CFI was .991, which both meet the standards of good fit (i.e., .95 or higher; Hu & Bentler, 1999). Fig. 1 shows the beta weights of the tested model. 3.4.2. Mediation effects In the present model, we tested two-path mediation. Each lower and upper bound value for the 95% Confidence Intervals (CIs) around each indirect effect failing to contain zero indicates support for the mediation hypothesis. Exclusion vs. inclusion mediated the effect of general religiosity on prejudice toward atheists (mediated effect = .307; CI: .109, .504) and prejudice toward gay men (mediated effect = .237; CI: .021, .453). The literal vs. symbolic dimension mediated the effect of general religiosity on prejudice toward atheists (mediated effect = .038; Confidence Interval [CI]: .076, .001), prejudice toward Arabs (mediated effect = .053; CI: .096, .010), and prejudice toward African Americans (mediated effect = .048; CI: .085, .010). These results partially support Hypothesis 3. Post-critical beliefs fully mediated the relationship between general religiosity and prejudice toward gay men, Arabs, and African Americans and partially mediated the relationship between general religiosity and prejudice toward atheists. Full mediation between religiosity and prejudice toward atheists may not have occurred because atheists are the least likely group to be socially accepted among a variety of other religious and ethnic minority groups (Edgell, Gerteis, & Hartmann, 2006). 4. General discussion Whereas previous research has indicated that the way in which individuals hold religious beliefs (cognitive rigidity/flexibility) plays an important role in mediating the relationship between general religiosity and prejudice (Brandt & Reyna, 2010; Hill et al., 2010; Johnson et al., 2011, 2012), the present studies demonstrated that both the belief in God and cognitive rigidity/flexibility components play unique roles in predicting prejudices. Together, these studies replicate and extend previous research indicating that the cognitive rigidity/flexibility component (literal vs. symbolic) of religiosity is most strongly associated with prejudice or
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Table 6 Zero-order correlations and descriptive statistics for religiosity, PCBS, and prejudice measures (Study 2). Measure
1
1. 2. 3. 4. 5. 6. 7. 8. 9.
–
Intrinsic religiosity Religious behaviors Religiosity Exclusion vs. inclusion Literal vs. symbolic Social distance – atheists Social distance – gay men Social distance – Arabs Social distance – African Americans
2 .88** .87** .86** .30** .53** .37** .10 .04
– .88** .80** .23** .51** .37** .09 .06
3
4
5
6
7
8
9
M
SD
–
4.65 .00 3.47 .18 3.05 1.48 1.56 1.54 1.32
2.46 .89 2.12 5.12 2.55 .60 .59 .62 .46
– .79** .27** .52** .37** .13* .03
– .30** .56** .41** .14** .07
– .05 .01 .13* .17**
– .68** .49** .34**
– .50** .46**
– .61**
a .95 .87 – – – .88 .85 .91 .85
Note: PCBS = Post-Critical Beliefs Scale. * p < .05. ** p < .01. Single-item measure.
tolerance toward racial out-groups (Duriez & Hutsebaut, 2000; Duriez et al., 1999). Namely, the cognitive rigidity/flexibility component (literal vs. symbolic) is most strongly associated with tolerance toward racial as well as value-violating out-groups and the belief in God component (exclusion vs. inclusion of transcendence) is most strongly associated with prejudice toward value-violating out-groups. By examining both the belief in God and cognitive rigidity/flexibility components of religiosity’s distinct roles in predicting racial and value-violating prejudices, the present studies tested a more developed mediation-path model than previous studies (Johnson et al., 2011). Some limitations exist in the present studies. First, although the present studies demonstrate that the way in which individuals process religious content is an important predictor of tolerance, we do not know if the cognitive rigidity/flexibility component of religiosity is a larger mediator of the religiosity–prejudice relationship than cognitively rigid ideologies. Further examination between cognitively rigid ideologies and cognitive processes (measured by PCBS) is necessary. Second, it is unclear why the belief in God component of religiosity predicts prejudice toward Arabs (Study 1). As noted, it may be because individuals associate ‘‘Muslim’’ with ‘‘Arab,’’ leading them to view Arabs as a value-violating out-group. Future research could examine post-critical belief dimensions as mediators of the relationship between general religiosity and prejudice toward Arabs and Muslims to examine if the model works the same for both types of prejudices. Finally, the present study examines the relationship between general religiosity, post-critical beliefs, and prejudices among a variety of religious affiliations (Protestant, Catholic, no religion). It would be helpful to examine these relationships among each religious group separately to see if there are differences in how the model works. Despite these limitations, the present studies demonstrate it is neither the belief in God nor the way in which one processes those beliefs that singularly predicts prejudice. Rather, which component of religiosity predicts prejudice depends on the type of prejudice being examined. The results of this study are the first to provide a more comprehensive model of the religiosity–prejudice relationship by demonstrating the role that the two components of religiosity—belief in God and cognitive rigidity/flexibility—play in predicting two unique types of prejudice: racial and value-violating.
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M.J. Shen et al. / Personality and Individual Differences 54 (2013) 389–395 Johnson, M. K., Rowatt, W. C., Barnard-Brak, L. M., Patock-Peckham, J. A., LaBouff, J. P., & Carlisle, R. D. (2011). A mediational analysis of the role of right-wing authoritarianism and religious fundamentalism in the religiosity–prejudice link. Personality and Individual Differences, 50(6), 851–856. http://dx.doi.org/ 10.1016/j.paid.2011.01.010. MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39(1), 99–128. http://dx.doi.org/10.1207/ s15327906mbr3901_4. Mason, W., & Suri, S. (2012). Conducting behavioral research on Amazon’s Mechanical Turk. Behavior Research Methods, 44(1), 1–23. http://dx.doi.org/ 10.3758/s13428-011-0124-6.
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Disentangling the belief in God and cognitive rigidity/flexibility components of religiosity to predict racial and value-violating prejudice: A Post-Critical Belief Scale analysis Megan Johnson Shen a,⇑, Logan A. Yelderman b, Megan C. Haggard c, Wade C. Rowatt c a b c
Mount Sinai School of Medicine, New York, NY, United States University of Nevada, Reno, Reno, NV, United States Baylor University, Waco, TX, United States
a r t i c l e
i n f o
Article history: Received 5 August 2012 Received in revised form 5 October 2012 Accepted 8 October 2012 Available online 14 November 2012 Keywords: Religiosity Prejudice Cognitive rigidity/flexibility Belief in God Post-critical beliefs
a b s t r a c t Past research indicates that being religious is associated with prejudice toward racial and value-violating out-groups. However, this past research treated religiosity as a unidimensional construct without taking into account how different components of religiosity—belief in a higher power and the rigidity/flexibility of religious beliefs—are associated with measures of prejudice. Two studies examined the relationship between these two components of religiosity, as measured by the Post-Critical Beliefs Scale, and racial (African Americans, Arabs) and value-violating prejudices (atheists, gay men). As the flexibility of religious beliefs increased (literal vs. symbolic dimension), attitudes toward racial and value-violating out-groups became more positive (Study 1). As belief in God strengthened (exclusion vs. inclusion of transcendence dimension), attitudes toward value-violating out-groups became more negative. Study 2 demonstrated that these two components of religiosity fully mediated the relationship between general religiosity and prejudice toward African Americans, Arabs, and gay men and partially mediated the relationship between religiosity and prejudice toward atheists. Results are discussed in light of reexamining the conclusion that simply being religious is associated with prejudice. Ó 2012 Published by Elsevier Ltd.
1. Introduction Because measures of religiosity have been associated with prejudice toward racial (Hall, Matz, & Wood, 2010) and value-violating (Whitley, 2009) out-groups across multiple studies, most researchers have concluded that simply being religious is associated with prejudice. One limit of this conclusion is that it assumes religiosity is a unidimensional construct. However, religiosity is a multidimensional construct with at least two components. One component of religiosity involves the degree of belief in God or a higher power (i.e., the belief in God component). A second component of religiosity involves how one holds that belief (i.e., the cognitive rigidity/flexibility component). To understand better the associations between general religiosity and prejudice, it is necessary to take into account both components. To our knowledge, no single study has assessed how the degree of belief in God and the rigidity of that belief predict prejudicial attitudes separately. Some research has examined cognitively rigid ideologies as mediators of the relationship between religiosity and ⇑ Corresponding author. Address: Mount Sinai School of Medicine, Department of Oncological Sciences, One Gustave L. Levy Place, Box 1130, NY 10029, United States. Tel.: +1 212 659 5678; fax: +1 212 849 2566. E-mail address: [email protected] (M.J. Shen). 0191-8869/$ - see front matter Ó 2012 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.paid.2012.10.008
prejudice (Brandt & Reyna, 2010; Hill, Cohen, Terrell, & Nagoshi, 2010; Johnson, Labouff, Rowatt, Patock-Peckham, & Carlisle, 2012; Johnson et al., 2011), but some ideological measures utilized—such as religious fundamentalism—entangle the belief in God and cognitive rigidity/flexibility components of religion within their items. Whether a person believes in a higher power (i.e., belief in God) and how one holds religious beliefs (i.e., cognitive rigidity/flexibility) need to be assessed separately to examine how each influences prejudices. 1.1. Religiosity, cognition, and prejudice The ways in which individuals process beliefs accounts for religiosity’s association with prejudice better than belief in God. For instance, cognitively rigid or closed-minded ideologies, such as right-wing authoritarianism (RWA) and religious fundamentalism (RF), have been shown to fully mediate the relationship between general religiosity and prejudice toward African Americans and gay men (Johnson et al., 2011). Moreover, RWA (Johnson et al., 2012), need for cognition and preference for consistency (Hill et al., 2010), and need for closure (Brandt & Reyna, 2010) have all been shown to mediate the relationship between RF and racial and value-violating prejudices. Although these studies examined the cognitive rigidity/flexibility component of religiosity, they did
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not consider both the belief in God and cognitive rigidity/flexibility components of religiosity as potential mediators of the religiosity– prejudice relationship.
racial (African American, Arab) and value-violating (gay men, atheists) prejudices.
1.2. Post-critical beliefs and prejudice
2.1. Method
The Post-Critical Beliefs Scale (PCBS; Duriez, Soenens, & Hutsebaut, 2005; Hutsebaut, 1996) allows researchers to disentangle the belief in God and cognitive rigidity/flexibility components of religiosity. The PCBS is rooted in the following two dimensions of religion posited by Wulff (1991): (1) exclusion versus inclusion of transcendence, representing the belief in God component of religion, and (2) literal versus symbolic, representing the cognitive rigidity/flexibility component of religion. Interactions between these two dimensions produce four distinct approaches to religion: (1) orthodoxy (literal, transcendent), (2) external critique (literal, non-transcendent), (3) second naiveté (symbolic, transcendent), and (4) relativism (symbolic, non-transcendent). Previous research has examined post-critical beliefs’ relationship with racial prejudice. Orthodoxy and external critique, both associated with the literal dimension of the PCBS, were positively correlated with racism (Duriez, Fontaine, & Hutsebaut, 2000; Duriez & Hutsebaut, 2000; Duriez, Luyten, Snauwaert, & Hutsebaut, 2002). Relativism, marked by symbolic beliefs, was negatively correlated with racism. Second naiveté was uncorrelated with racism. These results indicate that how one holds one’s religious beliefs (literal vs. symbolic) plays a more important role in the expression of prejudice than whether one believes in a higher power. Post-critical beliefs were examined as mediators of the relationship between age, education, church attendance, and belief salience on the one hand and racial prejudice on the other hand (Duriez & Hutsebaut, 2000). Within this model, church attendance and belief salience had no direct effects on racial prejudice but did have small indirect effects through their influence on post-critical beliefs.
2.1.1. Participants Two hundred seventy-nine Americans (73 males, 186 females, 20 missing; M age = 32.58 years, SD = 11.84) completed an online survey. Our sample consisted of: 72.0% White, 7.5% African American, 5.7% Asian/Pacific Islander, 3.9% Hispanic, 2.2% ‘‘other,’’ 1.8% Native American, and 6.8% unspecified. The sample consisted of the following self-reported religious affiliations: 29.7% ‘‘no religion,’’ 19.4% Protestant, 18.6% Catholic, 16.5% ‘‘other,’’ 5% Jewish, 2.5% Buddhist, 1.4% Hindu, and 6.8% missing.
1.3. The present studies The goals of the present studies were to examine post-critical belief dimensions as predictors of racial and value-violating prejudices and as mediators of the general religiosity–prejudice relationship. Although the cognitive rigidity/flexibility components of post-critical beliefs (literal vs. symbolic) have been strong predictors of racial prejudice (Duriez & Hutsebaut, 2000; Duriez, Hutsebaut, & Roggen, 1999), it is likely the belief in God component of post-critical beliefs (exclusion vs. inclusion of transcendence) also plays a role in predicting value-violating prejudices. Multiple measures of religiosity are consistently associated with prejudice toward gay men/lesbian women (Whitley, 2009) and these out-groups violate religious beliefs themselves. Based on past research, we formulated three main hypotheses. First, we predicted the cognitive rigidity/flexibility component of religiosity (literal vs. symbolic; higher values indicating more symbolic beliefs) would predict tolerance toward racial (African American, Arab) and value-violating (gay men, atheists) out-groups (Hypothesis 1). Second, we predicted the belief in God component of religiosity (exclusion vs. inclusion of transcendence; higher values indicating higher belief in God) would predict prejudice toward value-violating out-groups (Hypothesis 2). Finally, in Study 2 we predicted that both post-critical belief dimensions would fully mediate the relationship between general religiosity and prejudice toward racial and value-violating out-groups (Hypothesis 3). 2. Study 1 In Study 1, we examined the relationships between the belief in God and cognitive rigidity/flexibility components of religiosity and
2.2. Procedure and measures Data were collected from across the US from Amazon’s Mechanical Turk (MTurk) website, which has been shown to provide reliable and more diverse data than college samples (Behrend, Sharek, Meade, & Wiebe, 2011; Buhrmester, Kwang, & Gosling, 2011) and to be a valuable, reliable data collection tool for researchers (Mason & Suri, 2012). The survey was accessible only to American participants, and they received $0.15 in exchange for their completion of the 116-item online survey.
2.2.1. Post-Critical Beliefs Scale (PCBS) Post-critical beliefs were measured with an 18-item short form of the Post-Critical Beliefs Scale (PCBS; Duriez et al., 2005). The four PCBS subscale scores (orthodoxy, second naiveté, external critique, and relativism) were computed and used to generate scores on the belief and literalism dimensions, as follows: Exclusion vs. inclusion = (orthodoxy + second external critique relativism) Literal vs. symbolic = (relativism + second orthodoxy external critique)
naiveté naiveté
The two dimensions that resulted were highly correlated (r = .97–.98) with similar dimensions derived from Principal Component Analysis and orthogonal Procrustes rotations previously used (cf. Duriez, 2003, 2004). Higher values on the exclusion vs. inclusion dimension indicate higher levels of inclusion of transcendence. Higher values on the literal vs. symbolic dimension indicate higher levels of symbolic interpretation of religion.
2.2.2. Prejudice measures Prejudice was measured with reported levels of comfort with social proximity to atheists, gay men, Arabs, and African Americans (1 = not at all comfortable, 3 = comfortable; Bogardus, 1933). All items were reverse-scored, aggregated, and averaged so that higher scores indicated higher levels of prejudice.
2.3. Results and discussion 2.3.1. Descriptive statistics Please see Table 1 for descriptive statistics, Cronbach’s a, and intercorrelations of the various measures.1 1 Due to low internal consistency of second naiveté (Cronbach’s a = .52), the item that accounted for this low reliability was removed (‘‘The Bible is a rough guide in the search for God, and not a historical account’’). Data from the new subscale, composed of three items, were internally consistent (Cronbach’s a = .83).
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M.J. Shen et al. / Personality and Individual Differences 54 (2013) 389–395 Table 1 Zero-order correlations and descriptive statistics for PCBS and prejudice measures (Study 1). Measure
1
1. Gender (dummy-coded, 0 = female, 1 = male) 2. Race (dummy-coded, 0 = non-white, 1 = white) 3. Age 4. Socioeconomic status 5. Exclusion vs. inclusion 6. Literal vs. symbolic 7. Social distance – atheists 8. Social distance – gay men 9. Social distance – Arabs 10. Social distance – African Americans
– .05 .02 .03 .03 .03 .06 .25** .11 .22**
2
3
4
5
6
7
8
9
10
M
SD
a
.45 .45 11.84 .88 4.76 2.60 .61 .62 .63 .49
– – – – – –
–
.28 (%) .72 (%) 32.58 3.23 .35 3.17 1.43 1.46 1.53 1.33
– .11 .01 .09 .00 -.06 .08 .04 .10
– .05 .09 .17** .11 .14* .12* .08
– .04 .03 .01 .03 .05 .13*
– .24** .56** .44** .26** .05
– .02 .03 .07 .11
– .66** .62** .38**
– .45** .38**
– .64**
.90 .89 .90 .85
Note: PCBS = Post-Critical Beliefs Scale. * p < .05. ** p < .01. Single-item measure.
Table 2 Two-step regression of prejudice toward atheists on demographics and PCBS (Study 1). Predictor variables
Gender (0 = female, 1 = male) Race (0 = non-white, 1 = white) Age Socioeconomic status Exclusion vs. inclusion Literal vs. symbolic R2 F R2 change
Model 1 (base model)
Model 2 (PCBS added)
b (s.e.)/Stan. b
t
b (s.e.)/Stan. b
t
.04 (.09)/.03 .06 (.10)/ .04 .01 (.00)/.11 .00 (.05)/.00 – – .02 .90, n.s.
.47 .66 1.74 .03 – –
.01 (.07)/.01 .01 (.08)/.00 .01 (.00)/.08 .01 (.04)/ .02 .07 (.01)/.57 .03 (.01)/ .14 .31 17.67** .30**
.19 .06 1.47 .29 10.05*** 2.47*
Note: PCBS = Post-Critical Beliefs Scale. * p < .05. ** p < .01. *** p < .001.
2.3.2. Predicting prejudice with post-critical beliefs To examine if the two components of post-critical beliefs predicted prejudice, hierarchical regression analyses were run. In the first step, demographic control variables were added as predictors of prejudice. In the second step, the two dimensions of the PCBS were added as predictors. As predicted, post-critical beliefs explained a significant amount of additional variance in predicting prejudice toward atheists, gay men, and Arabs, but not in predicting prejudice toward African Americans (see Tables 2–5).2 Hypothesis 1 was partially supported. The cognitive rigidity/ flexibility component of religiosity (literal vs. symbolic) was most important in predicting tolerance toward both value-violating and racial prejudices. The literal vs. symbolic dimension was negatively associated with prejudice toward atheists (b = .14, p < .05; see Table 2), marginally negatively associated with prejudice toward gay men (b = .10, p = .09; see Table 3), and negatively associated with prejudice toward Arabs (b = .15 p < .05; see Table 4) and African Americans (b = .03, p < .05; see Table 5). Hypothesis 2 was fully supported. The belief in God component of religiosity (exclusion vs. inclusion of transcendence) was most important in predicting prejudice toward value-violating outgroups. Exclusion vs. inclusion of transcendence was positively associated with prejudice toward atheists (b = .57, p < .001; see Table 2) and gay men (b = .47, p < .001; see Table 3). The exclusion vs. inclusion of the transcendence dimension was also positively
2
Moderated regression analyses were run to examine if there was a significant interaction between inclusion and symbolism. Because this interaction was not significant in predicting any of the prejudices, it was excluded from all analyses reported.
associated with prejudice toward Arabs (b = .26, p < .001; see Table 4). This association may have occurred due to individuals inaccurately equating ‘‘Arabs’’ with ‘‘Muslims,’’ in which case they might be viewed as a value-violating out-group. Future research is needed to examine this hypothesis. All other predictors of the varying prejudices are reported in Tables 2–5. 3. Study 2 In Study 2, we tested the hypothesis that post-critical beliefs would fully mediate the relationship between general religiosity and racial and value-violating prejudices (Hypothesis 3). 3.1. Method 3.1.1. Participants Two hundred ninety Americans (109 males, 149 females, 32 missing; mean age = 34.68 years, SD = 12.98) completed an online survey. The sample was comprised of the following ethnicities: 71.4% White, 8.3% Asian/Pacific Islander, 5.2% African American, 2.1% Hispanic, 1.4% ‘‘other,’’ 1.4% Native American, and 10.3% missing. The sample was comprised of the following self-reported religious affiliations: 27.6% ‘‘no religion,’’ 21% Protestant, 17.2% ‘‘other,’’ 16.9% Catholic, 2.8% Jewish, 2.4% Hindu, 1.4% Buddhist, 0.3% Muslim, and 10.3% unspecified. 3.2. Procedure and measures An online survey was administered to individuals from across the US using Amazon’s Mechanical Turk (MTurk) website. As in
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M.J. Shen et al. / Personality and Individual Differences 54 (2013) 389–395 Table 3 Two-step regression of prejudice toward gay men on demographics and PCBS (Study 1). Predictor variables
Model 1 (base model) b (s.e.)/Stan. b
Gender (0 = female, 1 = male) Race (0 = non-white, 1 = white) Age Socioeconomic status Exclusion vs. inclusion Literal vs. symbolic R2 F R2 change
Model 2 (PCBS added) t
b (s.e.)/Stan. b 3.56*** 1.63 2.37* .25 – –
.29 (.08)/.21 .09 (.08)/ .06 .01 (.00)/.12 .00 (.04)/.00 .06 (.01)/.47 .02 (.01)/ .10 .29 15.97** .21**
b (s.e.)/Stan. b
t
b (s.e.)/Stan. b
.11 .07 .01 .03 – – .03 1.78
1.19 .68 2.02* .72 – –
.09 (.09)/.06 .10 (.09)/.07 .01 (.00)/.13 .03 (.04)/.04 .05 (.01)/.26 .04 (.02)/ .15 .10 4.39** .07**
.31 (.09)/.22 .15 (.09)/ .10 .01 (.00)/.15 .01 (.05)/.02 – – .08 5.40***
t 3.79*** 1.05 2.14* .01 8.25*** 1.69
Note: PCBS = Post-Critical Beliefs Scale. p < .10. * p < .05. ** p < .01. *** p < .001.
Table 4 Two-step regression of prejudice toward Arabs on demographics and PCBS (Study 1). Predictor variables
Gender (0 = female, 1 = male) Race (0 = non-white, 1 = white) Age Socioeconomic status Exclusion vs. inclusion Literal vs. symbolic R2 F R2 change
Model 1 (base model)
(.09)/.08 (.10)/.04 (.00)/.13 (.05)/.05
Model 2 (PCBS added) t 1.02 1.08 2.05* .64 4.11*** 2.27*
Note: PCBS = Post-Critical Beliefs Scale. * p < .05. ** p < .01. *** p < .001.
Table 5 Two-step regression of prejudice toward African Americans on demographics and PCBS (Study 1). Predictor variables
Gender (0 = female, 1 = male) Race (0 = non-white, 1 = white) Age Socioeconomic status Exclusion vs. inclusion Literal vs. symbolic R2 F R2 change
Model 1 (base model)
Model 2 (PCBS added)
b (s.e.)/Stan. b
t
b (s.e.)/Stan. b
.21 (.07)/.19 .12 (.08)/.10 .00 (.00)/.07 .07 (.04)/.13 – – .07 4.40**
2.99** 1.55 1.09 2.06* – –
.20 (.07)/.18 .13 (.08)/.11 .00 (.00)/.08 .07 (.04)/.13 .01 (.01)/.08 .03 (.01)/ .13 .09 3.75** .02, n.s.
t 2.89** 1.67 1.30 2.08* 1.21 2.03*
Note: PCBS = Post-Critical Beliefs Scale. p < .10. * p < .05. ** p < .01.
Study 1, only American participants could access the survey and they received $0.15 in exchange for their completion of the 124item survey. 3.2.1. Religiosity Religiosity was measured as a latent variable with three indicators: intrinsic religiosity, religious behaviors, and general religiosity (see Fig. 1). Intrinsic religious orientation was measured using the Religious Orientation Scale (Allport & Ross, 1967), which measures religion inherently important to individuals. Religious behaviors were measured by standardizing, aggregating, and averaging
responses to questions about three indicators of religious behaviors: (1) religious service attendance, (2) reading of sacred texts, and (3) prayer/meditation (cf. Rowatt, LaBouff, Johnson, Froese, & Tsang, 2009). Finally, a single-item measure was used to assess general religiosity (i.e., ‘‘To what extent do you consider yourself a religious person?’’; 1 = not at all, 7 = very much).
3.2.2. Post-Critical Beliefs Scale (PCBS) Post-critical beliefs were measured with the same 18-item short form of the Post-Critical Beliefs Scale (PCBS; Duriez et al.,
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------- Direct paths Mediated paths .286*
Intrinsic Religiosity
Religious Behaviors
Prejudice toward atheists
General Religiosity
.350**
Exclusion vs. Inclusion .952***
.927***
.271*
Prejudice toward gay men
.918*** .877*** -.136* -.133*
Religiosity .282***
Prejudice toward Arabs
Literal vs. Symbolic
-.187**
-.169**
Prejudice toward African Americans
Fig. 1. Model depicting mediation effects of post-critical beliefs on religiosity and prejudice toward atheists, gay men, Arabs and African Americans. Standardized coefficients are shown. Please note: Selected Fit Indexes: v2 (12, N = 290) = 27.74, p < .001 [CFI = 0.991, TLI/NNFI = 0.974, RMSEA = 0.067 (CI90: .034, .100)]. Non-significant paths for indirect effects were not drawn. ⁄p < .05, ⁄⁄p < .01, ⁄⁄⁄p < .001.
2005) used in Study 1. Exclusion vs. inclusion and literal vs. symbolic dimensions were created as in Study 1.3 3.2.3. Prejudice measures The same social distance scales (Bogardus, 1933) utilized in Study 1 to measure prejudice were utilized in this study. 3.3. Analytic procedure A base model was fit using MPlus (v. 5.20; Muthén & Muthén, 2012) testing PCBS dimensions as mediators of prejudice (see Fig. 1). The residuals of the mediators were allowed to correlate with each other. Full information maximum likelihood (FIML) estimation was used to handle missing data. Model fit was evaluated by examining the following four estimates: (1) the chi-square (v2) goodness-of-fit, (2) the root mean square error of approximation (RMSEA; Browne & Cudeck, 1993), (3) the Tucker Lewis Index (TLI), also known as the Non-Normed Fit Index (NNFI), and (4) the Comparative Fit Index (CFI; Bentler, 1990). In the present analysis, MacKinnon, Lockwood, and Williams (2004) method for statistical mediation was utilized. This technique has been found to produce unbiased mediation estimates (Cheung & Lau, 2008). 3.4. Results and discussion See Table 6 for Cronbach’s a, descriptive statistics, and correlations between all variables. The path model is reported in Fig. 1 with all significant paths present in the base model that was tested. 3.4.1. Overall model fit The model chi-square was significant [v2 (12) = 27.740, p < .01]; however, the chi-square statistic has been shown to be sensitive to sample size and not a satisfactory indicator of model fit (Fan, Thompson, & Wang, 1999). According to other measures of fit, the hypothesized model appears to fit the data well. The RMSEA value, compensating for the effects of model complexity, was 3 Data obtained from the second naiveté (Cronbach’s a = .37) subscale had low internal consistency, so we removed the same item as in Study 1which accounted for this low reliability. Data from the new subscale, composed of three items, were internally consistent (Cronbach’s a = .84).
.067 (CI90: .034, .100), indicating acceptable fit of less than .08 (Browne & Cudeck, 1993). The value of the TLI/NNFI was .974 and the value of the CFI was .991, which both meet the standards of good fit (i.e., .95 or higher; Hu & Bentler, 1999). Fig. 1 shows the beta weights of the tested model. 3.4.2. Mediation effects In the present model, we tested two-path mediation. Each lower and upper bound value for the 95% Confidence Intervals (CIs) around each indirect effect failing to contain zero indicates support for the mediation hypothesis. Exclusion vs. inclusion mediated the effect of general religiosity on prejudice toward atheists (mediated effect = .307; CI: .109, .504) and prejudice toward gay men (mediated effect = .237; CI: .021, .453). The literal vs. symbolic dimension mediated the effect of general religiosity on prejudice toward atheists (mediated effect = .038; Confidence Interval [CI]: .076, .001), prejudice toward Arabs (mediated effect = .053; CI: .096, .010), and prejudice toward African Americans (mediated effect = .048; CI: .085, .010). These results partially support Hypothesis 3. Post-critical beliefs fully mediated the relationship between general religiosity and prejudice toward gay men, Arabs, and African Americans and partially mediated the relationship between general religiosity and prejudice toward atheists. Full mediation between religiosity and prejudice toward atheists may not have occurred because atheists are the least likely group to be socially accepted among a variety of other religious and ethnic minority groups (Edgell, Gerteis, & Hartmann, 2006). 4. General discussion Whereas previous research has indicated that the way in which individuals hold religious beliefs (cognitive rigidity/flexibility) plays an important role in mediating the relationship between general religiosity and prejudice (Brandt & Reyna, 2010; Hill et al., 2010; Johnson et al., 2011, 2012), the present studies demonstrated that both the belief in God and cognitive rigidity/flexibility components play unique roles in predicting prejudices. Together, these studies replicate and extend previous research indicating that the cognitive rigidity/flexibility component (literal vs. symbolic) of religiosity is most strongly associated with prejudice or
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Table 6 Zero-order correlations and descriptive statistics for religiosity, PCBS, and prejudice measures (Study 2). Measure
1
1. 2. 3. 4. 5. 6. 7. 8. 9.
–
Intrinsic religiosity Religious behaviors Religiosity Exclusion vs. inclusion Literal vs. symbolic Social distance – atheists Social distance – gay men Social distance – Arabs Social distance – African Americans
2 .88** .87** .86** .30** .53** .37** .10 .04
– .88** .80** .23** .51** .37** .09 .06
3
4
5
6
7
8
9
M
SD
–
4.65 .00 3.47 .18 3.05 1.48 1.56 1.54 1.32
2.46 .89 2.12 5.12 2.55 .60 .59 .62 .46
– .79** .27** .52** .37** .13* .03
– .30** .56** .41** .14** .07
– .05 .01 .13* .17**
– .68** .49** .34**
– .50** .46**
– .61**
a .95 .87 – – – .88 .85 .91 .85
Note: PCBS = Post-Critical Beliefs Scale. * p < .05. ** p < .01. Single-item measure.
tolerance toward racial out-groups (Duriez & Hutsebaut, 2000; Duriez et al., 1999). Namely, the cognitive rigidity/flexibility component (literal vs. symbolic) is most strongly associated with tolerance toward racial as well as value-violating out-groups and the belief in God component (exclusion vs. inclusion of transcendence) is most strongly associated with prejudice toward value-violating out-groups. By examining both the belief in God and cognitive rigidity/flexibility components of religiosity’s distinct roles in predicting racial and value-violating prejudices, the present studies tested a more developed mediation-path model than previous studies (Johnson et al., 2011). Some limitations exist in the present studies. First, although the present studies demonstrate that the way in which individuals process religious content is an important predictor of tolerance, we do not know if the cognitive rigidity/flexibility component of religiosity is a larger mediator of the religiosity–prejudice relationship than cognitively rigid ideologies. Further examination between cognitively rigid ideologies and cognitive processes (measured by PCBS) is necessary. Second, it is unclear why the belief in God component of religiosity predicts prejudice toward Arabs (Study 1). As noted, it may be because individuals associate ‘‘Muslim’’ with ‘‘Arab,’’ leading them to view Arabs as a value-violating out-group. Future research could examine post-critical belief dimensions as mediators of the relationship between general religiosity and prejudice toward Arabs and Muslims to examine if the model works the same for both types of prejudices. Finally, the present study examines the relationship between general religiosity, post-critical beliefs, and prejudices among a variety of religious affiliations (Protestant, Catholic, no religion). It would be helpful to examine these relationships among each religious group separately to see if there are differences in how the model works. Despite these limitations, the present studies demonstrate it is neither the belief in God nor the way in which one processes those beliefs that singularly predicts prejudice. Rather, which component of religiosity predicts prejudice depends on the type of prejudice being examined. The results of this study are the first to provide a more comprehensive model of the religiosity–prejudice relationship by demonstrating the role that the two components of religiosity—belief in God and cognitive rigidity/flexibility—play in predicting two unique types of prejudice: racial and value-violating.
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