The assessment of depression in people with multiple sclerosis: a systematic review of psychometric validation studies

Daniel Hind, Daphne Kaklamanou*, Dan Beever, Rosie Webster, Ellen Lee, Michael Barkham, Cindy Cooper

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Background: The prevalence of depression in people with multiple sclerosis (PwMS) is high; however, symptoms common to both conditions makes measurement difficult. There is no high quality overview of validation studies to guide the choice of depression inventory for this population.

Methods: A systematic review of studies validating the use of generic depression inventories in people with MS was conducted using MEDLINE and PsycINFO. Studies validating the use of depression inventories in PwMS and published in English were included; validation studies of tests for cognitive function and general mental health were excluded. Eligible studies were then quality assessed using the COSMIN checklist and findings synthesised narratively by instrument and validity domain.

Results: Twenty-one studies (N=5,991 PwMS) evaluating 12 instruments were included in the review. Risk of bias varied greatly between instrument and validity domain.

Conclusions: The review of validation studies was constrained by poor quality reporting and outcome reporting bias. Well-conducted evaluations of some instruments are unavailable for some validity domains. This systematic review provides an evidence base for trade-offs in the selection of an instrument for assessing self-reported symptoms of depression in research or clinical practice involving people with MS. We make detailed and specific recommendations for where further research is needed. Trial Registration: PROSPERO CRD42014010597

Original languageEnglish
Article number278
Number of pages18
JournalBMC Psychiatry
Volume16
Issue number1
DOIs
Publication statusPublished - 4 Aug 2016

Keywords

  • Chronic Disease
  • Depression
  • Multiple Sclerosis
  • Psychometrics
  • Reproducibility of Results

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