title: Summary diagnostic validity of commonly used maternal major depression disorder case finding instruments in the United States: A meta-analysis.
abstract: Major Depression Disorder (MDD) is common among mothers of young children. However, its detection remains low in primary-care and community-based settings in part due to the uncertainty regarding the validity of existing case-finding instruments. We conducted meta-analyses to estimate the diagnostic validity of commonly used maternal MDD case finding instruments in the United States.
  
  
  
  We systematically searched three electronic bibliographic databases PubMed, PsycINFO, and EMBASE from 1994 to 2015 to identify relevant published literature. Study eligibility and quality were evaluated using the Standards for the Reporting of Diagnostic Accuracy studies and Quality Assessment of Diagnostic Accuracy Studies guidelines, respectively. Pooled sensitivity and specificity of case-finding instruments were generated using Bayesian hierarchical summary receiver operating models.
  
  
  
  Overall, 1130 articles were retrieved and 74 articles were selected for full-text review. Twelve articles examining six maternal MDD case-finding instruments met the eligibility criteria and were included in our meta-analyses. Pooled sensitivity and specificity estimates were highest for the BDI-II (91%; 95% Bayesian Credible Interval (BCI): 68%; 99% and 89%; 95% BCI: 62%; 98% respectively) and EPDS10 (74%; 95% BCI: 46%; 91% and 97%; 95% BCI: 84%; 99% respectively) during the antepartum and postpartum periods respectively.
  
  
  
  No meta-regression was conducted to examine the impact of study-level characteristics on the results.
  
  
  
  Diagnostic performance varied among instruments and between peripartum periods. These findings suggest the need for a judicious selection of maternal MDD case-finding instruments depending on the study population and target periods of assessment.
authors: Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States. Electronic address: hamieuga@gmail.com.
authors: Arthur H
authors: AH
authors: Owora
authors: Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States. Electronic address: Helene-Carabin@ouhsc.edu.
authors: Hélène
authors: H
authors: Carabin
authors: Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States. Electronic address: Jessica-Reese@ouhsc.edu.
authors: Jessica
authors: J
authors: Reese
authors: Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States. Electronic address: Tabitha-Garwe@ouhsc.edu.
authors: Tabitha
authors: T
authors: Garwe
mesh_terms: D001499:Bayes Theorem; D003865:Major Depressive Disorder / Q000175:diagnosis*; D006801:Humans; D009035:Mothers / Q000523:psychology*; D058725:Peripartum Period / Q000523:psychology; D011569:Psychiatric Status Rating Scales / Q000706:statistics & numerical data*; D014481:United States
keywords: Bayesian meta-analysis; Case-finding instrument; Diagnostic performance; Major depression disorder; Misclassification error