IDEAS home Printed from https://ideas.repec.org/a/sae/clnure/v31y2022i8p1481-1490.html
   My bibliography  Save this article

Diagnostic Test Accuracy of the Beck Depression Inventory for Detecting Major Depression in Adolescents: A Systematic Review and Meta-Analysis

Author

Listed:
  • Anna Lee
  • Jinkyung Park

Abstract

Major depressive disorder in adolescents is closely linked to poor social, cognitive, and academic outcomes, including suicidality. The Beck Depression Inventory (BDI), a screening tool, is one of the most widely used instruments for detecting depression; however, its diagnostic test accuracy has not yet been thoroughly examined. This study, therefore, aimed to systematically review and perform a meta-analysis to evaluate the accuracy of the BDI for detecting depression in adolescents. In August 2020, a search was conducted in the EMBASE, MEDLINE, CINAHL, and PsycArticles databases, and following a review against predefined eligibility criteria, 22 studies were finally included. The quality of the included articles was evaluated, and a hierarchical regression model was used to calculate the pooled estimates of sensitivity and specificity; 73.0% (95% CI; 62.0%, 81.8%) and 80.3% (72.8%, 86.1%) in cutoff 16, respectively. The findings indicated the BDI is a reliable and useful tool to screen adolescents’ depression.

Suggested Citation

  • Anna Lee & Jinkyung Park, 2022. "Diagnostic Test Accuracy of the Beck Depression Inventory for Detecting Major Depression in Adolescents: A Systematic Review and Meta-Analysis," Clinical Nursing Research, , vol. 31(8), pages 1481-1490, November.
    • Handle: RePEc:sae:clnure:v:31:y:2022:i:8:p:1481-1490
    DOI: 10.1177/10547738211065105
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/10547738211065105
    Download Restriction: no
    File URL: https://libkey.io/10.1177/10547738211065105?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:clnure:v:31:y:2022:i:8:p:1481-1490. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.