Fig. 3.

Elbow test for k-means analysis and k-means clustering results (A: visual inspection of the plot demonstrates that the optimal number of clusters is 3 in the elbow test. B: The k-means clustering results show a high degree of similarity with regard to clustering designations. As the clusters were generated on 8 axes (one for each anxiety subcategory), these axes were condensed into two distilled axes (dimensionality reduction), represented here by “Dim1” and “Dim 2” to represent the greatest concordance between the data)