The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis

Chen He, Brooke Levis, Kira E. Riehm, Nazanin Saadat, Alexander W. Levis, Marleine Azar, Danielle B. Rice, Ankur Krishnan, Yin Wu, Ying Sun, Mahrukh Imran, Jill Boruff, Pim Cuijpers, Simon Gilbody, John P.A. Ioannidis, Lorie A. Kloda, Dean McMillan, Scott B. Patten, Ian Shrier, Roy C. ZiegelsteinDickens H. Akena, Bruce Arroll, Liat Ayalon, Hamid R. Baradaran, Murray Baron, Anna Beraldi, Charles H. Bombardier, Peter Butterworth, Gregory Carter, Marcos Hortes Nisihara Chagas, Juliana C.N. Chan, Rushina Cholera, Kerrie Clover, Yeates Conwell, Janneke M. De Man-Van Ginkel, Jesse R. Fann, Felix H. Fischer, Daniel Fung, Bizu Gelaye, Felicity Goodyear-Smith, Catherine G. Greeno, Brian J. Hall, Patricia A. Harrison, Martin Härter, Ulrich Hegerl, Leanne Hides, Stevan E. Hobfoll, Marie Hudson, Thomas N. Hyphantis, Masatoshi Inagaki, Khalida Ismail, Nathalie Jetté, Mohammad E. Khamseh, Kim M. Kiely, Yunxin Kwan, Femke Lamers, Shen Ing Liu, Manote Lotrakul, Sonia R. Loureiro, Bernd Löwe, Laura Marsh, Anthony McGuire, Sherina Mohd-Sidik, Tiago N. Munhoz, Kumiko Muramatsu, Flávia L. Osório, Vikram Patel, Brian W. Pence, Philippe Persoons, Angelo Picardi, Katrin Reuter, Alasdair G. Rooney, Iná S. Da Silva Dos Santos, Juwita Shaaban, Abbey Sidebottom, Adam Simning, Lesley Stafford, Sharon Sung, Pei Lin Lynnette Tan, Alyna Turner, Henk C.P.M. Van Weert, Jennifer White, Mary A. Whooley, Kirsty Winkley, Mitsuhiko Yamada, Brett D. Thombs, Andrea Benedetti

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


Background: Screening for major depression with the Patient Health Questionnaire-9 (PHQ-9) can be done using a cutoff or the PHQ-9 diagnostic algorithm. Many primary studies publish results for only one approach, and previous meta-analyses of the algorithm approach included only a subset of primary studies that collected data and could have published results. Objective: To use an individual participant data meta-analysis to evaluate the accuracy of two PHQ-9 diagnostic algorithms for detecting major depression and compare accuracy between the algorithms and the standard PHQ-9 cutoff score of ≥10. Methods: Medline, Medline In-Process and Other Non-Indexed Citations, PsycINFO, Web of Science (January 1, 2000, to February 7, 2015). Eligible studies that classified current major depression status using a validated diagnostic interview. Results: Data were included for 54 of 72 identified eligible studies (n participants = 16,688, n cases = 2,091). Among studies that used a semi-structured interview, pooled sensitivity and specificity (95% confidence interval) were 0.57 (0.49, 0.64) and 0.95 (0.94, 0.97) for the original algorithm and 0.61 (0.54, 0.68) and 0.95 (0.93, 0.96) for a modified algorithm. Algorithm sensitivity was 0.22-0.24 lower compared to fully structured interviews and 0.06-0.07 lower compared to the Mini International Neuropsychiatric Interview. Specificity was similar across reference standards. For PHQ-9 cutoff of ≥10 compared to semi-structured interviews, sensitivity and specificity (95% confidence interval) were 0.88 (0.82-0.92) and 0.86 (0.82-0.88). Conclusions: The cutoff score approach appears to be a better option than a PHQ-9 algorithm for detecting major depression.

Original languageEnglish (US)
Pages (from-to)25-37
Number of pages13
JournalPsychotherapy and psychosomatics
Issue number1
StatePublished - Jan 1 2020
Externally publishedYes


  • Depression
  • Diagnostic accuracy
  • Meta-analysis
  • Patient Health Questionnaire-9
  • Screening

ASJC Scopus subject areas

  • Clinical Psychology
  • Applied Psychology
  • Psychiatry and Mental health


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