U.S. Simulation of Lifetime Major Depressive Episode Prevalence and Recall Error.

Abstract

Simulation models can improve measurement and understanding of mental health conditions in the population. Major depressive episodes are a common and leading cause of disability but are subject to substantial recall bias in survey assessments. This study illustrates the application of a simulation model to quantify the full burden of major depressive episodes on population health in the U.S. A compartmental model of major depressive episodes that explicitly simulates individuals' under-reporting of past episodes was developed and calibrated to 2005-2017 National Surveys on Drug Use and Health data. Parameters for incidence of a first major depressive episode and the probability of under-reporting past episodes were estimated. Analysis was conducted from 2017 to 2019. The model estimated that 30.1% of women (95% range: 29.0%-32.5%) and 17.4% of men (95% range: 16.7%-18.8%) have lifetime histories of a major depressive episode after adjusting for recall error. Among all adults, 13.1% of women (95% range: 8.1%-16.5%) and 6.6% of men (95% range: 4.0%-8.3%) failed to report a past major depressive episode. Under-reporting of a major depressive episode history in adults aged >65 years was estimated to be 70%. Simulation models can address knowledge gaps in disease epidemiology and prevention and improve surveillance efforts. This model quantifies the under-reporting of major depressive episodes and provides parameter estimates for future research. After adjusting for under-reporting, 23.9% of adults have a lifetime history of major depressive episodes, which is much higher than based on self-report alone (14.0%). Far more adults would benefit from depression prevention strategies than what survey estimates suggest.