top of page

Vicarious Sadism


Statistical Tests of Mean (Ave.) Differences Among Execution Actors

Regarding the vicarious sadism belief system that enjoys news about executions and supports public executions, all four groups reported means in the 'disagree' range. However, the level of disagreement varied widely among the four groups. Executioners posted the highest average scores of 2.92. Hard Abstract Supporters reported the second highest average (mean=2.29). Abolitionists reported the third highest levels of average agreement at 1.71. Consistent with their high scores on the disdain belief system, Soft Abstract Supporters reported the lowest level of agreement (mean=1.62) with vicarious sadism. The test of the four groups indicated statistically significant differences in means. The effect size is large; eta squared for this test is .25.

For the three groups that support executions, differences in means were statistically significant. This is largely due to Soft Abstract Supporters of executions reporting much lower vicarious sadism scores than the other two pro-execution groups. The effect size is large; eta squared for this test is .25. When Soft Abstract Supporters and Hard Abstract Supporters were tested separately, the relationship was statistically significant. The effect size (eta squared) is .15. This might be described as above medium effect size, where eta squared=.09 is medium and eta squared=.25 is large.

Researchers also tested the difference between Abolitionists and Soft Abstract Supporters. The differences in means is not statistically significant. The effect size is small. Eta squared for this test is .004.



*Every person in the study had an average "score" for this belief system. That score ranged from 1.00 (strongly disagree) to 5.0 (strongly agree), where 3.0 is neither agree/disagree. Analysis of Variance (ANOVA) tests differences in average scores across groups. Inherently, ANOVA is a more powerful statistic than the Chi-Square. As with the Chi-Square, a Sig. less than .05 indicates that differences in averages are significant. Further, ANOVA provides an estimate of effect size (eta squared). With non-probability samples, effect size is a more meaningful measure of the influence of underlying belief systems on roles (intended actions) that people play as execution actors.

bottom of page