Surveillance of the mental health of Germany's adults using monthly population-based survey data

Abstract

Abstract To meet new information demands in the COVID-19 pandemic, the Mental Health Surveillance at the Robert Koch Institute in Germany began using monthly survey data for high-frequency monitoring of several indicators of population mental health. Visualized time series consisting of three-month rolling estimates and smoothing curves are used to provide policymakers with regular assessments of current developments in symptoms of depression and anxiety, self-rated mental health, perceived mental health care needs, loneliness, and social support. Striking changes have taken place within the observation period - so far, particularly from mid to late 2021 and early 2022, when (further) marked declines in the mental health of adults began. For example, the percentage of the population scoring above the screening cutoff of an ultra-brief depression screener jumped from about 13 % in late 2021 to levels of 17-18 % in the first half of 2022 and then further rose to steady levels of 20 % for the second half of 2022 and the beginning of 2023. Symptoms of anxiety also increased substantially in this time, and self-rated mental health worsened. High-frequency surveillance resulted in policymakers being informed of the unfolding of these changes with relatively short delays. This presentation outlines the methods used for high-frequency monitoring within the Mental Health Surveillance and shows up-to-date results. Challenges in the interpretation of time series and in reporting will also be described. Centrally, questions about what signifies meaningful change have emerged alongside questions surrounding how the utility of high-frequency surveillance might be improved and how its utilization could be facilitated. A structured exchange with stakeholders to help address these questions is planned. A brief look at this and other next steps will wrap up the presentation.