Depression in multiple sclerosis: The utility of common self-report instruments and development of a disease-specific measure

Lauren B. Strober, Peter A. Arnett

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49 Scopus citations


The ultimate objective of the present investigation was to improve the detection of depression in multiple sclerosis (MS) by comparing common self-report depression measures to a new, modified measure, which takes into account the contribution that symptoms of MS may have on individuals reports. There has been a longstanding concern regarding the accurate assessment of depression in MS, particularly with regard to the overlap of MS symptomatology and neurovegetative depression symptoms on self-report questionnaires, which may lead to an overdiagnosis of depression in MS. To address these difficulties, we previously proposed a "trunk and branch" of depression in MS. This model allows for the delineation of what symptoms are most reflective of depression in MS. By identifying these symptoms, it was possible to develop a modified Beck Depression Inventory (BDI) in which only the items found to be most related to depression in MS are included in the new measure, the MS Specific BDI (MS-BDI). We compared this measure to common self-report instruments (Beck Depression Inventory-Second Edition, BDI-II; Beck Depression Inventory-Fast Screen, BDI-FS; Chicago Multiscale Depression Inventory, CMDI). Results suggest that cutoffs of 4 on the BDI-FS and 23 on the CMDI Mood subscale are most useful when screening for depression in MS, with a sensitivity for both of 100%, while a cutoff of 19 on the BDI-II, a cutoff of 22 on the CMDI Evaluative scale, and a cutoff of 8 on the MS-BDI had high specificities, suggesting they can be used as to assist in diagnosing depression in MS.

Original languageEnglish (US)
Pages (from-to)722-732
Number of pages11
JournalJournal of Clinical and Experimental Neuropsychology
Issue number7
StatePublished - Aug 9 2015

All Science Journal Classification (ASJC) codes

  • Clinical Psychology
  • Neurology
  • Clinical Neurology


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