Impact of misclassification error in the estimation of maternal major depression disorder prevalence in home visitation programs

Abstract

The objective of this study was to measure the bias introduced by misclassification error when estimating the prevalence of MDD among mothers in two community-based studies. Baseline data were collected from mothers participating in two home visitation study sites in South Central United States between 2010 and 2014. The operational definition of MDD was a Center of Epidemiological Studies-Depression - Short Form (CESD-SF) score of 10 or higher. Misclassification error was adjusted for using CESD-SF sensitivity and specificity priors that were either antepartum or postpartum specific or non-specific. Bias was measured as the difference between the observed and misclassification error-adjusted prevalence estimates using a Binomial Bayesian Latent Class model. The proportion of mothers in the antepartum and postpartum periods confounded the level of bias in estimating MDD prevalence. When using antepartum and postpartum specific sensitivity and specificity of the CESD-SF, misclassification error led to nearly no bias in prevalence estimates. In contrast, ignoring differences in CESD-SF sensitivity and specificity between these periods showed considerable MDD prevalence bias. The use of period of assessment (antepartum versus postpartum) specific case-finding instrument diagnostic performance values is critical to the valid estimation of MDD prevalence among mothers. Studies using other case-finding instruments are needed to support this conclusion.

Keywords: Bias; CESD; Confounding; Maternal major depression disorder; Misclassification error.