Coercive measures such as involuntary psychiatric admission are considered a last resort in the treatment of people with psychiatric disorders. So far, numerous factors have been identified that influence their use. However, the link between a pandemic – in particular, restrictions such as lockdowns – and the use of involuntary psychiatric admission is unclear.

To examine the association between COVID-19 lockdowns and involuntary psychiatric admissions in Austria.

This retrospective exploratory study assessed all involuntary psychiatric admissions and use of mechanical restraint in Austria, except for the federal state of Vorarlberg, between 1 January 2018 and 31 December 2020. Descriptive statistics and regression models were used.

During the 3-year study period, 40 012 individuals (45.9% females, mean age 51.3 years) had 66 124 involuntary psychiatric admissions for an average of 10.9 days. Mechanical restraint was used during 33.9% of these admissions. In weeks of nationwide COVID-19 lockdowns (2020 v. 2018/2019), involuntary psychiatric admissions were significantly fewer (odds ratio = 0.93, P = 0.0001) but longer (11.6 (s.d.: 16) v. 10.9 (s.d.: 15.8) days). The likelihood of involuntary admission during lockdowns was associated with year (2020 v. 2018–2019; adjusted odds ratio = 0.92; P = 0.0002) but not with sex (P = 0.814), age (P = 0.310), use of mechanical restraint (P = 0.653) or type of ward (P = 0.843).

Restrictions such as lockdowns affect coercive measures and resulted in fewer but longer involuntary psychiatric admissions during weeks of lockdown in Austria. These results strengthen previous findings that showed the dependence of coercive measures on external factors, highlighting the need to further clarify causality and desired prevention effects when using coercive measures.

Magnetic resonance imaging (MRI) studies on major depressive disorder (MDD) have predominantly found short-term electroconvulsive therapy (ECT)-related gray matter volume (GMV) increases, but research on the long-term stability of such changes is missing. Our aim was to investigate long-term GMV changes over a 2-year period after ECT administration and their associations with clinical outcome.

In this nonrandomized longitudinal study, patients with MDD undergoing ECT (n = 17) are assessed three times by structural MRI: Before ECT (t0), after ECT (t1) and 2 years later (t2). A healthy (n = 21) and MDD non-ECT (n = 33) control group are also measured three times within an equivalent time interval. A 3(group) × 3(time) ANOVA on whole-brain level and correlation analyses with clinical outcome variables is performed.

Analyses yield a significant group × time interaction (pFWE < 0.001) resulting from significant volume increases from t0 to t1 and decreases from t1 to t2 in the ECT group, e.g., in limbic areas. There are no effects of time in both control groups. Volume increases from t0 to t1 correlate with immediate and delayed symptom increase, while volume decreases from t1 to t2 correlate with long-term depressive outcome (all p ⩽ 0.049).

Volume increases induced by ECT appear to be a transient phenomenon as volume strongly decreased 2 years after ECT. Short-term volume increases are associated with less symptom improvement suggesting that the antidepressant effect of ECT is not due to volume changes. Larger volume decreases are associated with poorer long-term outcome highlighting the interplay between disease progression and structural changes.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Childhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age.

Within the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer.

CM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions.

Severity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.

The present study aimed to identify dietary patterns, compare dietary patterns regarding nutrient profile and investigate the association between dietary patterns and body composition in a population in western Austria.

In a cross-sectional study, eating habits, anthropometric measurements and body composition were assessed. Food intake was collected by two non-consecutive 24 h recalls. Factor analysis (principal component analysis) with complementary cluster analysis was applied to identify dietary patterns. Associations of dietary patterns with body composition and nutrient profile were examined by the t test, one-way ANOVA and ANCOVA with Bonferroni’s correction. The χ2 test was used for categorical variables.

Tyrol, western Austria, 2014–2015.

Adults (n 463) aged 18–64 years.

Three dietary patterns were derived, labelled as the ‘health-conscious’, the ‘western’ and the ‘traditional’ dietary pattern. After adjustment for confounding variables, individuals following the traditional and western patterns were more likely to be overweight/obese (P <0·001) and to have a higher body fat percentage (P <0·05). Individuals following the traditional dietary pattern consumed significantly more SFA and less PUFA and dietary fibre (P <0·001) than those in the other groups.

Individuals who mostly eat in a traditional way should be encouraged to increase their consumption of vegetables, fruits, whole grains and healthy fats. It is important to know local eating habits not only for planning individual nutritional therapy, but also for well-directed public health actions.