Clinical Utility of the Inventory of Depression and Anxiety Symptoms (IDAS). (July 2019)

• Record Type: Journal Article
• Authors: Stasik-O'Brien, Sara M.; Brock, Rebecca L.; Chmielewski, Michael; Naragon-Gainey, Kristin; Koffel, Erin; McDade-Montez, Elizabeth; O'Hara, Michael W.; Watson, David
• Is Part Of: Assessment. Volume 26:Number 5(2019)
• Page Start: 944
• Page End: 960
• Publication Date: 2019-07
• Subjects: major depression -- anxiety disorders -- scale development -- cutoff scores -- Inventory of Depression and Anxiety Symptoms; Psychological tests -- Periodicals; Psychodiagnostics -- Periodicals; Personality tests -- Periodicals; 150.287
• DOI: 10.1177/1073191118790036
• Languages: English
• ISSNs: 1073-1911

Abstract

Depressive and anxiety disorders are severe and disabling conditions that result in substantial cost and global societal burden. Accurate and efficient identification is thus vital to proper diagnosis and treatment of these disorders. The Inventory of Depression and Anxiety Symptoms (IDAS) is a reliable and well-validated measure that provides dimensional assessment of both mood and anxiety disorder symptoms. The current study examined the clinical utility of the IDAS by establishing diagnostic cutoff scores and severity ranges using a large mixed sample ( N = 5, 750). Results indicated that the IDAS scales are good to excellent predictors of their associated Structured Clinical Interview for DSM-IV diagnoses. These findings were replicated using Diagnostic and Statistical Manual of Mental Disorders–Fifth edition (DSM-5) criteria assessed via the Mini-International Neuropsychiatric Interview. We provide three cutoff scores for each scale that can be used differentially depending on the goal of their use: screening, efficiency, or diagnosis confirmation. The identified severity ranges allow users to characterize individuals as mild, moderate, or severe, providing clinical information beyond diagnostic status. Finally, the 10-item IDAS Dysphoria scale and 20-item General Depression scale demonstrate strong ability to predict internalizing diagnoses and may represent an efficient way to screen for the presence of internalizing psychopathology.