Search

Objectives The Estonian National Mental Health Study (EMHS) was conducted in 2021–2022 to provide population-wide data on mental health in the context of COVID-19 pandemic. The main objective of this paper is to describe the rationale, design, and methods of the EMHS and to evaluate the survey response. Methods Regionally representative stratified random sample of 20,000 persons aged 15 years and older was drawn from the Estonian Population Register for the study. Persons aged 18 years and older at the time of the sampling were enrolled into three survey waves where they were invited to complete an online or postal questionnaire about mental well-being and disorders, and behavioral, cognitive, and other risk factors. Persons younger than 18 years of age were invited to fill an anonymous online questionnaire starting from wave 2. To complement and validate survey data, data on socio-demographic, health-related, and environmental variables were collected from six national administrative databases and registries. Additionally, a subsample was enrolled into a validation study using ecological momentary assessment. Results In total, 5636 adults participated in the survey wave 1, 3751 in wave 2, and 4744 in wave 3. Adjusted response rates were 30.6%, 21.1%, and 27.6%, respectively. Women and older age groups were more likely to respond. Throughout the three survey waves, a considerable share of adult respondents screened positive for depression (27.6%, 25.1%, and 25.6% in waves 1, 2, and 3, respectively). Women and young adults aged 18 to 29 years had the highest prevalence of depression symptoms. Conclusions The registry-linked longitudinal EMHS dataset comprises a rich and trustworthy data source to allow in-depth analysis of mental health outcomes and their correlates among the Estonian population. The study serves as an evidence base for planning mental health policies and prevention measures for possible future crises.

It is not known to what extent the automatic encoding and change detection of peripherally presented facial emotion is altered in dysphoria. The negative bias in automatic face processing in particular has rarely been studied. We used magnetoencephalography (MEG) to record automatic brain responses to happy and sad faces in dysphoric (Beck’s Depression Inventory ≥ 13) and control participants. Stimuli were presented in a passive oddball condition, which allowed potential negative bias in dysphoria at different stages of face processing (M100, M170, and M300) and alterations of change detection (visual mismatch negativity, vMMN) to be investigated. The magnetic counterpart of the vMMN was elicited at all stages of face processing, indexing automatic deviance detection in facial emotions. The M170 amplitude was modulated by emotion, response amplitudes being larger for sad faces than happy faces. Group differences were found for the M300, and they were indexed by two different interaction effects. At the left occipital region of interest, the dysphoric group had larger amplitudes for sad than happy deviant faces, reflecting negative bias in deviance detection, which was not found in the control group. On the other hand, the dysphoric group showed no vMMN to changes in facial emotions, while the vMMN was observed in the control group at the right occipital region of interest. Our results indicate that there is a negative bias in automatic visual deviance detection, but also a general change detection deficit in dysphoria.