Psychometric evaluation and optimization of the self-rated Montgomery-Åsberg Depression Rating Scale

The 9-item self-rated Montgomery-Åsberg Depression Rating Scale (MADRS-S) is commonly used for depression assessment worldwide, but its psychometric properties have not been thoroughly evaluated among psychiatric patients.

To 1) evaluate the psychometric properties of the original MADRS-S and 2) derive new improved versions of MADRS-S by excluding problematic items.

We included 1286 individuals (M_age = 37.8, 66 % women) diagnosed with major depressive disorder at the largest outpatient internet psychiatry unit in Sweden. Psychometric properties were evaluated and optimized using factor analysis and item response theory methods.

Exploratory and confirmatory factor analysis showed a one-factor or a bi-factor structure with a general factor suggesting essential one-dimensionality (common variance explained = 84 %). MADRS-S showed acceptable reliability (Molenaar-Sijtsma index [MS] = 0.77, Omega Hierarchical [OmegaH] = 0.81) but weak scalability (H = 0.31). Removing the two worst-performing items, sleep and appetite, created the MADRS-S-7 with improved scalability (H = 0.39) and reliability (MS = 0.79, OmegaH = 0.80). A further reduction formed the three-item MADRS-S-3 including only hallmark depression symptoms - mood, initiative, and emotional involvement -that demonstrated the strongest scalability (H = 0.53) and acceptable reliability (MS = 0.75, OmegaH = 0.74).

The original MADRS-S show essential one-dimensionality and acceptable reliability but poor scalability and some low-performing items. The new MADRS-S-7 retains most of the conceptual scope with superior psychometric properties. Furthermore, the novel MADRS-S-3 is the optimal choice when focusing on core depression symptoms, with minimized rating burden for patients and maximized ability to rank respondents on the latent variable by their summed score. The present findings warrant external validation across different psychiatric contexts.