Luppo Kuillman

Chapter 5 118 this, we used two essential parameters, namely ‘Tolerance’ and ‘Variance Inflation Factor’ (VIF). Considering all the Tolerances being well above 0.1 and all VIFs far below 10 (see Tables 3 and 4), we excluded the presence of multicollinearity that could have affected the outcomes (Dormann et al., 2013).  As can be seen in Table 2, both age and gender correlated with Paternalism. For this reason, we included these variables in the multiple regression in Step 1. In explaining the yielding to pressure in vignette 1 (unnecessary prescription of antibiotics), only gender remained a significant predictor of yielding to pressure (see Table 3 and 4). Interpretation of this outcome learns that male (coded as ‘1’) providers in this study are less prone to yield to pressure. This effect, however, was not the case for yielding to pressure in vignette 2.   Predictors of Yielding to pressure  Regarding hypotheses 1 and 2, we assumed that both moral deliberation and paternalism would regress positively and negatively respectively on the propensity of yielding to pressure in vignettes 1 and 2. However, only hypothesis 1 could be partly affirmed (see Table 3) in relation to yielding to pressure in vignette 1. That is, even though moral deliberation behaves as a predictor for both vignettes, for vignette 1 there is a positive relationship ( b = .244, t= 3.062, p= .003) and for vignette 2, moral deliberation turns out to be a negative statistically significant ( b = -.252, t= -3.126, p= .002) predictor.  Furthermore, we also had to reject hypotheses 3 and 4 because moral disengagement did neither moderate (cross-product: DELIB*MDS) the relationship between moral deliberation and the propensity of yielding to pressure in vignette 1 and 2, nor did it moderate (cross-product: PATER*MDS) the relationship between paternalism and the propensity of yielding to pressure.