The development, standardization, and initial validation of the Chicago Multiscale Depression Inventory

Abstract

Current self-report depression scales may overestimate depression symptoms in medical patients by including items measuring symptoms inherent to many medical conditions. They may therefore reflect a patient's medical rather than psychological state. We present the Chicago Multiscale Depression Inventory (CMDI), a factorially derived self-report depression scale that includes Mood, Evaluative, and Vegetative subscales. The CMDI and its subscales were designed to be used separately or combined; we posit that the nonvegetative CMDI subscales are the most accurate means of examining depression in medical patients. In this study we outline the development, standardization, and initial validation of the CMDI, a multistep process that required a total sample of 1,062 adults. We show the CMDI and each of its subscales to be internally consistent, reliable, and valid. Confirmatory factor analysis supports the CMDI factor structure. Finally, we report standardization scores for each of the CMDI scales, derived from an age-, race- and gender-stratified standardization sample of 420 adults.