Cleaving depressive diseases from depressive disorders and non-clinical states

OBJECTIVE: We sought to determine whether putative depressive diseases could be differentiated categorically from clinical depressive disorders and non-clinical mood states. METHOD: We interviewed volunteers who reported or denied any lifetime depressive mood state and analyzed data from the former group reporting on their 'most severe' depressive episode. We employed latent class analysis (LCA) to determine whether a two-class solution was supported and the contribution of individual variables to class allocations. RESULTS: All variables were significant predictors of class allocation. LCA-assigned Class I participants reported more depressive symptoms, had more distressing episodes and more lasting consequences, were more likely to view their depression as 'like a disease', and as being both disproportionately more severe and persistent in relation to any antecedent stressor. Validation involved comparison of LCA assignment with DSM-IV diagnosis for their most severe depressive episode. Of those assigned to Class I, 89% had a DSM diagnosis of melancholic, psychotic or bipolar depression. Class II had all those failing to meet criteria for a depressive episode and the majority of those with a non-melancholic depressive condition. CONCLUSION: Despite not including individual depressive symptoms, study variables strongly differentiated putative depressive diseases from a composite of clinical depressive conditions and subclinical depressive states.