Beyond binary: Exploring the merits of three depression groups in multiple sclerosis

Margaret H. Cadden, Jessica E. Meyer, Peter A. Arnett

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Objective: Depression has been traditionally explored in the context of multiple sclerosis (MS) as a binary construct (depressed, not depressed). However, given the 50% lifetime prevalence rate of depression in MS, it may be useful to consider not only currently depressed versus nondepressed patients, but to evaluate groups that better characterize the complexity of MS depression. The objective of the current study was to examine demographic, cognitive, illness, and psychosocial variables thought to associate with depression in MS across 3 groups: currently depressed, remitted depression, and never been depressed. Method: Fifty-four individuals with MS were examined. Current depression status was measured using the Beck Depression Inventory-Fast Screen (BDI-FS; Beck, Steer, & Brown, 2000). Past depression was evaluated using the Structured Clinical Interview for DSM-IV Disorders (SCID-IV; First, Spitzer, Gibbon, & Williams, 1998) and a semistructured psychosocial interview. Results: The results of the current study show that evaluating depression in 3 groups is useful for exploring risk, protective, and compensatory factors of depression in MS. A consistent grouping pattern (e.g., the remitted depression group always functioning the same as the never been depressed group) was not found among the variables examined; rather, several different patterns were observed. Several of these patterns revealed differences between the remitted depression and never been depressed groups; these differences would not have been observed had these 2 groups been combined into a "not currently depressed" group. Conclusions: These different patterns yield important information about the complex relationships of depression in MS that may be obscured when depression is viewed as a binary construct.

Original languageEnglish (US)
Pages (from-to)328-336
Number of pages9
JournalNeuropsychology
Volume31
Issue number3
DOIs
StatePublished - Mar 1 2017

All Science Journal Classification (ASJC) codes

  • Neuropsychology and Physiological Psychology

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