Edinburgh Research Explorer

Depression prevalence using the HADS-D compared to SCID major depression classification: An individual participant data meta-analysis

Research output: Contribution to journalArticle

  • Eliana Brehaut
  • Dipika Neupane
  • Brooke Levis
  • Yin Wu
  • Ying Sun
  • Ankur Krishnan
  • Chen He
  • Parash Mani Bhandari
  • Zelalem Negeri
  • Kira E. Riehm
  • Danielle B. Rice
  • Marleine Azar
  • Xin Wei Yan
  • Mahrukh Imran
  • Matthew J. Chiovitti
  • Nazanin Saadat
  • Pim Cuijpers
  • John P.A. Ioannidis
  • Sarah Markham
  • Scott B. Patten
  • Roy C. Ziegelstein
  • Melissa Henry
  • Zahinoor Ismail
  • Carmen G. Loiselle
  • Nicholas D. Mitchell
  • Marcello Tonelli
  • Jill T. Boruff
  • Lorie A. Kloda
  • Anna Beraldi
  • Anna P.B.M. Braeken
  • Gregory Carter
  • Kerrie Clover
  • Ronán M. Conroy
  • Daniel Cukor
  • Carlos E. da Rocha e Silva
  • Jennifer De Souza
  • Marina G. Downing
  • Anthony Feinstein
  • Panagiotis P. Ferentinos
  • Felix H. Fischer
  • Alastair J. Flint
  • Maiko Fujimori
  • Pamela Gallagher
  • Simone Goebel
  • Nathalie Jetté
  • Miguel Julião
  • Monika Keller
  • Marie Kjærgaard
  • Anthony W. Love
  • Bernd Löwe
  • Rocio Martin-Santos
  • Ioannis Michopoulos
  • Ricard Navines
  • Ahmet Öztürk
  • Luis Pintor
  • Jennie L. Ponsford
  • Roberto Sánchez-González
  • Marcelo L. Schwarzbold
  • Sébastien Simard
  • Susanne Singer
  • Ka-Yee Tung
  • Alyna Turner
  • Mark Walterfang
  • Jennifer White
  • Andrea Benedetti
  • Brett D. Thombs

Related Edinburgh Organisations

Original languageEnglish
JournalJournal of Psychosomatic Research
Volume139
Early online date23 Sep 2020
DOIs
Publication statusE-pub ahead of print - 23 Sep 2020

Abstract

ObjectivesValidated diagnostic interviews are required to classify depression status and estimate prevalence of disorder, but screening tools are often used instead. We used individual participant data meta-analysis to compare prevalence based on standard Hospital Anxiety and Depression Scale – depression subscale (HADS-D) cutoffs of ≥8 and ≥11 versus Structured Clinical Interview for DSM (SCID) major depression and determined if an alternative HADS-D cutoff could more accurately estimate prevalence.
MethodsWe searched Medline, Medline In-Process & Other Non-Indexed Citations via Ovid, PsycINFO, and Web of Science (inception-July 11, 2016) for studies comparing HADS-D scores to SCID major depression status. Pooled prevalence and pooled differences in prevalence for HADS-D cutoffs versus SCID major depression were estimated.
Results6005 participants (689 SCID major depression cases) from 41 primary studies were included. Pooled prevalence was 24.5% (95% Confidence Interval (CI): 20.5%, 29.0%) for HADS-D ≥8, 10.7% (95% CI: 8.3%, 13.8%) for HADS-D ≥11, and 11.6% (95% CI: 9.2%, 14.6%) for SCID major depression. HADS-D ≥11 was closest to SCID major depression prevalence, but the 95% prediction interval for the difference that could be expected for HADS-D ≥11 versus SCID in a new study was −21.1% to 19.5%.
ConclusionsHADS-D ≥8 substantially overestimates depression prevalence. Of all possible cutoff thresholds, HADS-D ≥11 was closest to the SCID, but there was substantial heterogeneity in the difference between HADS-D ≥11 and SCID-based estimates. HADS-D should not be used as a substitute for a validated diagnostic interview.

    Research areas

  • depression, Hospital Anxiety and Depression Scale, individual participant data, meta-analysis, screening tools

ID: 173676269