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. 2023 Mar 6;13:100279. doi: 10.1016/j.jvacx.2023.100279

Table 6.

Multiple logistic regressions predicting profile membership.

Rationals
Ambivalents
Pessimists
Invincibles
Borderliners
B OR B OR B OR B OR B OR
Gender (female & non-binary) 0.42† 1.52 0.09 1.10 0.40 1.49 −0.41 0.66 −0.33† 0.72
Race
Asian/PI 0.02 1.02 0.20 1.23 −1.43 0.24 0.26 1.30 0.08 1.08
Black/AA 0.11 1.11 0.06 1.06 −0.55 0.58 0.15 1.16 0.17 1.19
Hispanic/Latino −0.33 0.72 0.31 1.36 0.10 1.11 0.00 1.00 −0.15 0.86
Other 0.60 1.83 −0.34 0.71 0.32 1.38 0.22 1.25 −0.60 0.55
Political orientation −0.13* 0.87 −0.02 0.98 −0.06 0.94 0.23** 1.27 0.05 1.05
Purity −0.26** 0.77 0.35*** 1.42 0.32*** 1.38 0.17† 1.19 −0.54*** 0.59
Fairness −0.21** 0.81 0.34*** 1.40 −0.36** 0.70 −0.70*** 0.50 0.53*** 1.69

Note. Asian/PI = Asian or Pacific Islander; Black/AA = Black or African American. Regression coefficients are unstandardized. Reference group for gender is male; reference group for race is White. For each regression model, the dependent variable is membership in the column profile versus membership in all other profiles (i.e., membership in column profile = 1, non-membership in column profile = 0). *** p <.001 ** p <.01 * p <.05 † p <.10.