*2.6. Factor Analysis*

Factor analysis was used to simplify the information given by a correlation matrix to make it more easily interpretable [23]. To check for the appropriate conditions to perform a factor analysis we have used 2 methods: the Kaiser–Meyer–Olkin test and the Bartlett sphericity test. The first ranges from 0 to 1, with a value lower than 0.5 indicating that it is inappropriate to do the analysis. A significant result of the Bartlett sphericity test (*p* < 0.05) indicates that it is pertinent to make a factor analysis. To check for the number of different dimensions of the questionnaire, 3 different criteria were used: (1) Kaiser rule which selects the number of factors with a value greater than 1; (2) the percentage of explained variance which is determined by the accumulated percentage of variation extracted in each factor (varimax rotation with Kaiser's normalization was used to simplify the number of dimensions); (3) a scree plot which graphically represents the number of factors or dimensions extracted, we retained the factors or components to the left of the inflection point on the graph [23].

The statistical programs STATA version 15/SE and SPSS v23 (SPSS Inc., Chicago, IL, USA) were used for these statistical analyses. Results were considered significant with *p* < 0.05.
