Caveat: There are many different ways to perform a factor analysis, and we are not experts in the area, so the following should be regarded as a suggestive illustration rather than as a serious scientific analysis. Furthermore, factor analysis results are strongly dependent on the choice of questions for the survey.
To obtain this component matrix we used one variable for each of the thirty questions (for non-binary question we chose the variable with strongest correlations to other questions). To extract the components, we used the principal components method, stopping when eigenvalue < 1. We performed a Varimax rotation with Kaiser normalization, which converged in 8 rotations. In the attached component matrix we list only loadings with an absolute value greater than 0.25.
The interpretation of the factors is a subjective matter, but one could naturally suggest that the first four factors are strongly connected to: