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

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    Author
    He, C; Levis, B; Riehm, KE; Saadat, N; Levis, AW; Azar, M; Rice, DB; Krishnan, A; Wu, Y; Sun, Y; ...
    Date
    2020-01-01
    Source Title
    Psychotherapy and Psychosomatics
    Publisher
    KARGER
    University of Melbourne Author/s
    Butterworth, Peter; Stafford, Lesley; Turner, Alyna
    Affiliation
    Psychiatry
    Melbourne School of Psychological Sciences
    Melbourne Institute of Applied Economic and Social Research
    Metadata
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    Document Type
    Journal Article
    Citations
    He, C., Levis, B., Riehm, K. E., Saadat, N., Levis, A. W., Azar, M., Rice, D. B., Krishnan, A., Wu, Y., Sun, Y., Imran, M., Boruff, J., Cuijpers, P., Gilbody, S., Ioannidis, J. P. A., Kloda, L. A., McMillan, D., Patten, S. B., Shrier, I. ,... Benedetti, A. (2020). The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression: An Individual Participant Data Meta-Analysis. PSYCHOTHERAPY AND PSYCHOSOMATICS, 89 (1), pp.25-37. https://doi.org/10.1159/000502294.
    Access Status
    Access this item via the Open Access location
    URI
    http://hdl.handle.net/11343/253949
    DOI
    10.1159/000502294
    Open Access URL
    https://www.karger.com/Article/Pdf/502294
    Abstract
    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.

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