Study 1a
Participants. Study 1a included 1,627 participants (836 female, 765 male, 26 other) with 72 exclusions based on failure of attention checks. The sample size was calculated to yield at least 50 participants per condition, plus ten additional participants in each condition to account for typical rates of exclusion. The average age of the participants was 36.4 (SD=13.0) years old; 90% of participants were not Hispanic or Latino, 10% were Hispanic or Latino, 74% White or European-American, 7% Black or African-American, 12% Asian or Asian-American, less than 1% Native American or Pacific Islander, 4% Multiracial, and 1.5% selected other. Combined annual income was: 22% less than $30,000; 20% between 30,000-49,999; 18% between 50,000-69,999, 19% between 70,000-99,999, and 19% 100,000+. The majority, 43%, of participants were liberal or very liberal; a similar percentage, 39%, was slightly liberal, middle-of- the-road, or slightly conservative; 12% were conservative or very conservative; 3% did not know or were not political; 1% selected libertarian; 1% selected other. Participants were from all four regions of the US: West (24%), Midwest (20%), Northeast (22%) and South (34%).
Study 1a Results. We conducted analyses of variance to investigate the influence of the “damage type” – COVID-19, seasonal flu, or car accident – on whether participants considered the protagonist responsible, contaminated, and injured, their willingness to help him, and how risky they considered helping him; as well as whether priming with binding values increased perception of Dan as responsible, contaminated, and risky to help, and decreased willingness to help.
For responsibility, we found a significant main effect of the prime (F(2,4.031) = 8.326, p = .037, partial eta2=.805), a significant main effect of damage type (F(2,4.031) = 174.036, p < .000, partial eta2= .989), and no interactions: priming binding values caused the highest responsibility ratings (M=3.82, SEM=.07), significantly higher than individualizing values (M=3.58, SEM=.06, p=.009) but not significantly higher than control (M=3.72 SEM=.07, p=.25). Ratings of Dan’s responsibility (see means in Figure 1) were highest for being infected with COVID-19, higher than responsibility ratings for the car accident (p<.000) and seasonal flu (p=.003).
For contamination, injury, riskiness, and willingness to help, we found significant main effects of damage type only (see means in Figure 1). Contamination ratings were highest in the case of COVID-19, higher than the flu (p<.000), and higher than the car accident (p<.000; F(2,4.003) = 448.00, p < .000, partial eta2= .996). Dan was rated most injured by the car accident, followed by COVID-19 (p<.000), and the flu (p<.000; F(2,4.04) = 2487.68, p < .000, partial eta2=.999). People considered helping Dan to be riskiest when he contracted COVID-19, compared to the flu, or a car accident (p<.000; F(2,4.040) = 2693.42, p < .000, partial eta2= .999). People were significantly less willing to help the COVID-19 victim compared to the flu victim and the car accident victim (p<.000; F(2,4.004) = 68.96, p = .001, partial eta2= .972).
Study 1a Summary. Result suggest that the perceived threat to health and safety from COVID-19 was elevated compared to the flu or a car accident: participants were less willing to help COVID-19 victims, and considered them riskier to help, more responsible, and more contaminated than flu and car accident victims.
Study 1b
Participants. Study 1b included 1009 participants (510 female, 494 male, 5 other) with 73 exclusions based on failure of attention checks. The majority of participants in each prime condition identified the correct word from the vignette they read (individualizing 81%; binding 66%, control 71%). The sample size was calculated to yield at least 50 participants per condition, plus ten additional participants to each condition to account typical rates of exclusion. The average age of the participants was 38.9 (SD = 13.7); 93% of participants were not Hispanic or Latino, 7% were Hispanic or Latino, 79% White or European-American, 7% Black or African-American, 10% Asian or Asian-American, less than 1% Native American or Pacific Islander, 3% Multiracial and 1% selected other. Combined annual income was: 18% less than $30,000; 20% between 30,000 - 49,999; 18% between 50,000 - 69,999, 22% between 70,000 - 99,999, and 23% 100,000+. The majority of participants, 42%, were liberal or very liberal; a similar percentage, 41%, was slightly liberal, middle-of-the-road, or slightly conservative; 13% were conservative or very conservative; 2% did not know or were not political; ~2% selected libertarian; <1% selected other. Participants were from all four regions of the US: West (22%), Midwest (23%), Northeast (19%) and South (36%).
Study 1b Results. We conducted identical analyses as in Study 1a. Again (see Figure 1), there were significant main effects of damage type on all outcome variables: responsibility (F(2,1000) = 64.75, p < .001, partial eta2= .97), contamination (F(2,1000) = 339.76, p < .001, partial eta2= .994), injury (F(2,1000) = 281.46, p < .001, partial eta2=.993), willingness to help (F(2,1000) = 126.0, p < .000, partial eta2= .98), and risk (F(2,1000) = 177.12, p < .001, partial eta2= .989), there was a significant effect of damage type, only. As in Study 1a, these results indicated that ratings of contamination and perceived risk of helping were highest for COVID-19, followed by the flu and the car accident. Ratings of injury were highest for the car accident, followed by COVID-19, and the flu. Ratings of responsibility were highest in the case of COVID- 19, followed by the car accident and the flu. Finally, willingness to help was highest for the car accident victim, followed by the flu, and COVID-19.
Study 1b Summary. Relative to the flu and car accident victim, participants were again less willing to help the COVID-19 victim, who was considered significantly riskier to help, more contaminated, and more responsible.
Study 1c
In Study 1c, we replaced the “warrior” primes from Studies 1a-b with another set of primes for binding and individualizing values that have been found to be effective in prior research (Mooijman et al., 2018). These primes involved reading a short passage about morality by a purported “morality scholar,” arguing that either the well-being of the group (binding values condition) or the well-being of individuals (individualizing values condition) is central to morality. Participants then wrote a brief response essay discussing their perspective on the scholar’s ideas about morality. In the control condition, participants did not read or write a passage.
Study 1c Participants. Study 1c included 1026 participants (422 female, 593 male, 11 other) plus 54 exclusions based on failure of attention checks. The sample size was calculated as in Study 1b. The average age of the participants was 37.7 (SD = 14.7); 90% of participants were not Hispanic or Latino, 10% were Hispanic or Latino, 75% White or European-American, 10% Black or African-American, 8% Asian or Asian-American, 1% Native American or Pacific Islander, 4% Multiracial, and 2% selected other. Combined annual income was: 25% less than $30,000; 20% between 30,000-49,999; 17% between 50,000-69,999, 20% between 70,000- 99,999, and 19% 100,000+. The majority of participants, 45%, were liberal or very liberal; a similar percentage, 37%, was slightly liberal, middle-of-the-road, or slightly conservative; 12% were conservative or very conservative; 3% did not know or were not political; 1% selected libertarian; 2% other. Participants were from all four regions of the US: West (24%), Midwest (21%), Northeast (21%) and South (34%).
Study 1c Results. Analyses were identical to Studies 1a-b. We again found significant main effects for damage type on all the outcome variables: responsibility (F(2,1016) = 20.75, p = .008, partial eta2= .91), contamination (F(2,1016) = 186.4, p < .001, partial eta2= .989), injury (F(2,1016) = 177.95, p < .001, partial eta2=.989), willingness to help (F(2,1016) = 32.38, p < .000, partial eta2= .94), and risk (F(2,1016) = 122.17, p < .001, partial eta2= .984). As in Studies 1a-b, these results indicated (see Figure 1) ratings of contamination and risk were highest for COVID-19, followed by the flu, and the car accident; ratings of injury were highest for the car accident, followed by COVID-19, and the flu; ratings of responsibility were highest for COVID-19, followed by the car accident, and the flu; willingness to help was highest for the car accident victim, followed by the flu, and COVID-19.
Study 1c Summary. Once again, people were less willing to help the COVID-19 victim, who was considered significantly riskier to help, more contaminated, and more responsible than a flu or car accident victim.
Study 2
Binding values reflect group-level moral concerns; as such, Study 2 aimed to shed light on whether binding values would affect judgments of communities (groups) differently than they affected judgments of individuals. We investigated whether perceived risk and willingness to help a community, rather than an individual victim, would vary with moral values and damage type.
Study 2 Participants. Study 2 included 571 participants (317 female, 218 male, 4 other) with 23 exclusions based on failure of attention checks. The sample size was calculated to yield at least 50 participants per condition, plus ten additional participants in each condition to account for typical rates of exclusion. The average age of the participants was 35.7 (SD = 12.2); 92% of participants were not Hispanic or Latino, 8% were Hispanic or Latino, 79% White or European-American, 8% Black or African-American, 7% Asian or Asian-American, less than <1% Native American or Pacific Islander, 4% Multiracial and 1.3% selected other. Combined annual income was: 19% less than $30,000; 20% between 30,000-49,999; 20% between 50,000-69,999, 21% between 70,000-99,999, and 19% 100,000+. The majority of participants, 43%, were liberal or very liberal; a similar percentage, 39% was slightly liberal, middle-of-the- road, or slightly conservative (39%); 13% were conservative or very conservative; 2% did not know or were not political; <1% selected libertarian, <1% selected other. Participants were from all four regions of the US: West (18%), Midwest (23%), Northeast (24%) and South (35%).
Study 2 Results. We used analyses of variance to investigate whether participants would be less willing to help (donate to or volunteer in) an unnamed community affected by COVID-19, and how they perceived the risk of helping, when binding values were made salient, versus individualizing values or control (no prime). As in the previous studies, we varied damage type such that the community was affected by COVID-19, HIV/AIDS, or a severe storm. We also examined whether effects differed on the targets of donations and volunteering (soup kitchen, homeless shelter, medical facilities).
Consistent with the previous studies, we found a significant main effect of damage type for volunteering (F(2,531) = 7.62, p < .001, partial eta2= .028): participants were less willing to volunteer in the case of a community affected by COVID-19, compared to HIV/AIDS or a severe storm (p’s<.005; see means in Figure 2). There was no effect of the moral values primes. For donation, no effects were significant. For riskiness, we again found a significant main effect of damage type (F(2,531) = 85.1, p < .001, partial eta2= .24): people considered volunteering riskiest in a community affected by COVID-19, compared to HIV/AIDS or a severe storm (p’s<.000, see Figure 2). Finally, merging across volunteering and donating, there was a significant effect of helping location (F(2,1062) = 44.00, p < .001, partial eta2= .08): people preferred to help a soup kitchen, followed by a homeless shelter, and then medical facilities.
Study 2 Summary. Consistent with the previous studies examining an individual victim, participants were less willing to help a community of COVID-19 victims, relative to HIV/AIDS and storm victims, and considered helping the COVID-19 victims to be riskier.
All studies: Stable moral values, politics, and demographics analyses
We examined whether people’s stable moral values (binding values and individualizing values) predicted attitudes about victims, along with politics, gender, education, and income (politics from 1-7: very liberal to very conservative, gender: male (0) and female (1), income in increments from 1-7: under $30K to $100K and over per year, and education from 1-6: some high school, high school, some university/college, university/college, graduate degree, doctoral or professional degree (e.g., M.D., J.D., etc.). We conducted a series of regression analyses on our outcome variables by damage condition (COVID-19, flu, car accident). We entered moral values (binding values, individualizing values) in step one, and politics, education, gender, and income in step two, to predict (a) responsibility, (b) contamination, (c) injury, (d) perceived risk, and (e) willingness to help. The results for all studies are presented in Table 1, where standardized Beta coefficients and significance levels, R2 change values and significance levels, and averaged R2 change values are indicated; significant (p<.05) values indicated in bold.
As visible in Table 1, the results of the regression analyses indicate that moral values played a role in people’s judgments of both COVID-19 and non-COVID-19 victims; however, moral values consistently played a stronger role in judgments about victims of non-COVID-19 damage. Specifically, binding or individualizing values significantly predicting judgments in cases of non-COVID-19 victims 45% of the time (38/84 tests) and COVID-19 victims 21% of the time (9/42 tests). Averaging R2 change across all studies to estimate the variability accounted for by the predictors (Johnson & LeBreton, 2004; see Table 1), for non-COVID-19 victims, total R2 change accounted for by binding and individualizing values was: responsibility 1.9%, contamination 3.7%, injury 1.7%, risk 4.7%, and willingness to help 4.7%. For COVID-19 victims, total R2 change accounted for by binding and individualizing values was: responsibility 0.9%; contamination 2.9%, injury 2.1%, risk 1.8%, and willingness to help 1.6%.
Table 1.
Results of regression analyses of judgments of responsibility, contamination, injury, riskiness of helping, and willingness to help for COVID-19 and non-COVID-19 victims in Studies 1a-c and 2.
Note. Beta values represent coefficients with all variables modeled, in a two-step model with binding and individualizing values entered in step one, and demographics (politics, education, gender, and income) entered in step two. The top value in the R2 change columns represents the binding and individualizing values variables, the bottom value represents the change from the addition of the four variables: politics, education, gender, and income. Variance Inflation Factors were computed for each of the models reported in Table 1 and are consistently below 2.00, within acceptable range. For Study 2: Willingness to Help, the first column represents volunteering, the second column represents donation. Significant (p<.05) beta values and R2 change values indicated in bold.