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External validation of a shortened screening tool using individual participant data meta-analysis: A case study of the Patient Health Questionnaire-Dep-4

  • the DEPRESsion Screening Data DEPRESSD PHQ Collaboration
  • New York University
  • Keele University
  • McGill University
  • Charité – Universitätsmedizin Berlin
  • Stanford University
  • University of Amsterdam
  • University of Calgary
  • Johns Hopkins University
  • King's College London
  • McGill University
  • University of York
  • Concordia University
  • University of Washington
  • Bar-Ilan University
  • Iran University of Medical Sciences
  • Technical University of Munich
  • University of Manitoba
  • University of KwaZulu-Natal
  • Hospital Mesra Bukit Padang
  • Universidade de São Paulo
  • Prince of Wales Hospital Hong Kong
  • Universiti Kebangsaan Malaysia
  • University of Zimbabwe
  • University of Toronto
  • Universidad de Buenos Aires
  • Utrecht University
  • Generalitat de Catalunya
  • University of Cape Town
  • Monash University
  • Singapore Institute of Mental Health
  • Harvard University
  • University of Technology Sydney
  • London School of Hygiene and Tropical Medicine
  • Duke University

Research output: Contribution to journalArticlepeer-review

Abstract

Shortened versions of self-reported questionnaires may be used to reduce respondent burden. When shortened screening tools are used, it is desirable to maintain equivalent diagnostic accuracy to full-length forms. This manuscript presents a case study that illustrates how external data and individual participant data meta-analysis can be used to assess the equivalence in diagnostic accuracy between a shortened and full-length form. This case study compares the Patient Health Questionnaire-9 (PHQ-9) and a 4-item shortened version (PHQ-Dep-4) that was previously developed using optimal test assembly methods. Using a large database of 75 primary studies (34,698 participants, 3,392 major depression cases), we evaluated whether the PHQ-Dep-4 cutoff of ≥ 4 maintained equivalent diagnostic accuracy to a PHQ-9 cutoff of ≥ 10. Using this external validation dataset, a PHQ-Dep-4 cutoff of ≥ 4 maximized the sum of sensitivity and specificity, with a sensitivity of 0.88 (95% CI 0.81, 0.93), 0.68 (95% CI 0.56, 0.78), and 0.80 (95% CI 0.73, 0.85) for the semi-structured, fully structured, and MINI reference standard categories, respectively, and a specificity of 0.79 (95% CI 0.74, 0.83), 0.85 (95% CI 0.78, 0.90), and 0.83 (95% CI 0.80, 0.86) for the semi-structured, fully structured, and MINI reference standard categories, respectively. While equivalence with a PHQ-9 cutoff of ≥ 10 was not established, we found the sensitivity of the PHQ-Dep-4 to be non-inferior to that of the PHQ-9, and the specificity of the PHQ-Dep-4 to be marginally smaller than the PHQ-9.

Original languageEnglish
Pages (from-to)300-311
Number of pages12
JournalMethods
Volume204
DOIs
StatePublished - Aug 2022

Keywords

  • Equivalence testing
  • Optimal test assembly
  • Self-report questionnaire
  • Sensitivity
  • Specificity

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