Comparison of the screening ability between the 32-item Hypomania Checklist (HCL-32) and the Mood Disorder Questionnaire (MDQ) for bipolar disorder: A meta-analysis and systematic review

Psychiatry Res. 2019 Mar:273:461-466. doi: 10.1016/j.psychres.2019.01.061. Epub 2019 Jan 18.

Abstract

The frequent misdiagnosis of bipolar disorder (BD) is associated with detrimental consequences and inappropriate treatments. The 32-item Hypomania Checklist (HCL-32) and the Mood Disorder Questionnaire (MDQ) are widely used self-report screening instruments for BD. This is a systematic review and meta-analysis to compare the psychometric properties of the HCL-32 and the MDQ based on the same patient samples. Two reviewers systematically and independently searched PubMed, PsycINFO, EMBASE, Web of Science, and Cochrane Library databases. Studies using the HCL-32 and MDQ concurrently and reporting their psychometric properties were included. Eleven studies that met the entry criteria were included in the systematic review, and 9 studies with relevant data were included in the meta-analysis. Using study-defined cutoffs, summary sensitivities were 82% (95% CI: 72%-89%) and 80% (95% CI: 71%-86%), while specificities were 57% (95% CI: 48%-66%) and 70% (95% CI: 59%-71%) for the HCL-32 and the MDQ respectively. Both the HCL-32 and the MDQ have acceptable psychometric properties to identify BD and appear to be useful screening tools for BD.

Keywords: Bipolar disorder; CRD42018109267; HCL-32; MDQ; Meta-analysis; Screening.

Publication types

  • Comparative Study
  • Meta-Analysis
  • Research Support, Non-U.S. Gov't
  • Systematic Review

MeSH terms

  • Adult
  • Bipolar Disorder / diagnosis*
  • Checklist / statistics & numerical data*
  • Diagnostic Errors
  • Female
  • Humans
  • Male
  • Mass Screening / methods
  • Mass Screening / statistics & numerical data*
  • Psychometrics / methods
  • Psychometrics / statistics & numerical data*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Surveys and Questionnaires / statistics & numerical data*