Dropout from healthcare interventions can negatively affect patients and healthcare providers through impaired trust in the healthcare system and ineffective use of resources. Research on this topic is still largely missing on refugees and asylum seekers. The current study aimed to characterize predictors for dropout in the Mental Health in Refugees and Asylum Seekers (MEHIRA) study, one of the largest multicentered controlled trials investigating the effectiveness and cost-effectiveness of a nationwide stepped and collaborative care model.

Predictors were multiply imputed and selected for descriptive modelling using backward elimination. The final variable set was entered into logistic regression.

The overall dropout rate was 41,7%. Dropout was higher in participants in group therapy (p = 0.001; OR = 10.7), with larger satisfaction with social relationships (p = 0.017; OR = 1.87), with difficulties in maintaining personal relationships (p = 0.005; OR = 4.27), and with higher depressive symptoms (p = 0.029; OR = 1.05). Participants living in refugee accommodation (p = 0.040; OR = 0.45), with a change in social status (p = 0.008; OR = 0.67) and with conduct (p = 0.020; OR = 0.24) and emotional problems (p = 0.013; OR = 0.31) were significantly less likely to drop out of treatment.

Overall, the outcomes of this study suggest that predictors assessing social relationships, social status, and living conditions should be considered as topics of psychological treatment to increase adherence and as predictors for future research studies (including treatment type).

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.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

After parasuicide there is a high risk of reattempts. However, it seems that patients who survived severe suicidal trauma recover well. Therefore, the outcome of patients with severe multiple blunt trauma as a result of a suicide attempt was investigated with respect to psychiatric and somatic health, quality of life (QOL) and suicide reattempt rates.

Patients who underwent a suicide attempt were isolated from a prospectively collected sample of trauma patients from a level I University Trauma Centre. Follow-up examination was performed 6.1 ± 3 years after the trauma. A physical and psychiatric examination was performed, using established psychiatric scales.

Twelve percent of severely injured patients were identified as suicide attempters (male/female: 37/28, mean age 38 ± 18 years, mean Injury Severity Score (ISS) 40 ± 15 points). A psychiatric diagnosis was present in 90% at the time of the suicide attempt. Twenty-one patients died during the hospital stay (32%) and six subjects died thereafter, none due to suicide. Thirty-five individuals were eligible for examination. None of them had reattempted suicide. Seventeen (48%) had good outcomes reflected by absent or ambulatory psychiatric treatment, employment, normal psychiatric findings and good psychosocial ability. An indeterminate outcome was determined in 24%. Predictive variables for an adverse outcome (10 patients, 28%) were found to be a diagnosis of schizophrenia, continued psychiatric treatment and being without employment.

Despite the seriousness of the suicide attempt, survivors recovered well in about half the cases with no further suicide attempt in any patient. An early psychiatric consultation already on the Intensive Care Unit (ICU) is recommended.

Empathy is a basic human ability, and patients with schizophrenia show dysfunctional empathic abilities on the behavioural and neural level.

These dysfunctions may precede the onset of illness; thus, it seems mandatory to examine the empathic abilities in individuals at clinical high risk for psychosis.

Using functional magnetic resonance imaging, we measured 15 individuals at clinical high risk of psychosis (CHR group) and compared their empathy performance with 15 healthy volunteers and 15 patients with schizophrenia.

Behavioural data analysis indicated no significant deficit in the CHR group. Functional data analysis revealed hyperactivation in a frontotemporoparietal network including the amygdala in the CHR group compared with the other two groups.

Despite normal behavioural performance, the CHR group activated the neural empathy network differently and specifically showed hyperactivation in regions critical for emotion processing. This could suggest a compensatory mechanism reflecting emotional hypersensitivity or dysfunctional emotion regulation. Further investigations should clarify the role of these neural alterations for development and exacerbation of psychosis.

Individuals with schizophrenia and people with depression both show abnormal behavioural and neural responses when perceiving and responding to emotional stimuli, but pathology-specific differences and commonalities remain mostly unclear.

To directly compare empathic responses to dynamic multimodal emotional stimuli in a group with schizophrenia and a group with depression, and to investigate their neural correlates using functional magnetic resonance imaging (fMRI).

The schizophrenia group (n = 20), the depression group (n = 24) and a control group (n = 24) were presented with portrait-shot video clips expressing emotion through three possible communication channels: facial expression, prosody and content. Participants rated their own and the actor's emotional state as an index of empathy.

Although no group differences were found in empathy ratings, characteristic differences emerged in the fMRI activation patterns. The schizophrenia group demonstrated aberrant activation patterns during the neutral speech content condition in regions implicated in multimodal integration and formation of semantic constructs. Those in the depression group were most affected during conditions with trimodal emotional and trimodal neutral stimuli, in key regions of the mentalising network.

Our findings reveal characteristic differences in patients with schizophrenia compared with those with depression in their cortical responses to dynamic affective stimuli. These differences indicate that impairments in responding to emotional stimuli may be caused by pathology-specific problems in social cognition.