The internal consistency of the initial 24 items was estimated through the Cronbach’s alpha coefficient measured over sample 1. First, we checked the conditions for a stable factor structure in the data through the Kaiser–Meyer–Olkin measure and we checked for overall significance in the correlations within the items’ correlation matrix by means of a Bartlett’s test of sphericity. An EFA with principal component analysis (i.e., to allow for finding linear combinations of the variables with the greatest variance) was employed to extract the latent dimensions of the original questionnaire, where an orthogonal Varimax rotation (i.e., to minimize the number of variables with high loading on each factor, and to simplify the interpretation of the factor solution) was selected. We retained those items with factor loadings greater than 0.5 and with a minimum difference in factor loading on the remaining factors of 0.2 [39], items that would compose the final scale. Determining the number of factors of the final solution in the exploratory sample was guided by parallel analysis with 500 randomly correlated matrices [40]. With parallel analysis a random generated set of Eigenvalues is compared to the empirically derived Eigenvalues.

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