Revisiting the factor structure of the EURO-D, a depressive symptomatology scale: An exploratory graph analysis in 26...

Despite the widely use and multiple validations of the EURO-D scale, its factor structure is still under debate. Exploratory Graph Analysis (EGA), a novel network psychometric method, offers a promising approach to examining dimensionality.

45,390 participants (mean age = 71.27, 57.4% women) from 26 European countries. The sample was randomly split into a derivation sample (n = 22,823) and a cross-validation sample (n = 22,567). EGA was applied to the derivation sample to determine the structure of the EURO-D scale, utilizing two estimation methods: Graphical Least Absolute Shrinkage and Selection Operator (GLASSO) and Triangulated Maximally Filtered Graph (TMFG). The identified factor structures were then tested via Confirmatory Factor Analysis (CFA) in the cross-validation sample for model fit.

EGA consistently revealed a two-factor structure with minor differences in the placement of suicidality and fatigue items across estimation methods. CFA results confirmed an adequate model fit for both solutions.

This study combines exploratory (EGA) and confirmatory (CFA) approaches, supporting a two-factor structure for the EU-RO-D scale with alternative placements for fatigue and suicidality items. Results are discussed in contrast to previous studies reporting two and three-factor solutions with different assignments of these items.