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Background
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.
Methods
Predictors were multiply imputed and selected for descriptive modelling using backward elimination. The final variable set was entered into logistic regression.
Results
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.
Conclusion
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).
Background
Polygenic scores (PGSs) hold the potential to identify patients who respond favorably to specific psychiatric treatments. However, their biological interpretation remains unclear. In this study, we developed pathway-specific PGSs (PSPGSs) for lithium response and assessed their association with clinical lithium response in patients with bipolar disorder.
Methods
Using sets of genes involved in pathways affected by lithium, we developed 9 PSPGSs and evaluated their associations with lithium response in the International Consortium on Lithium Genetics (ConLi+Gen) (N = 2367), with validation in combined PsyCourse (Pathomechanisms and Signatures in the Longitudinal Course of Psychosis) (N = 105) and BipoLife (N = 102) cohorts. The association between each PSPGS and lithium response—defined both as a continuous ALDA score and a categorical outcome (good vs. poor responses)—was evaluated using regression models, with adjustment for confounders. The cutoff for a significant association was p < .05 after multiple testing correction.
Results
The PGSs for acetylcholine, GABA (gamma-aminobutyric acid), and mitochondria were associated with response to lithium in both categorical and continuous outcomes. However, the PGSs for calcium channel, circadian rhythm, and GSK (glycogen synthase kinase) were associated only with the continuous outcome. Each score explained 0.29% to 1.91% of the variance in the categorical and 0.30% to 1.54% of the variance in the continuous outcomes. A multivariate model combining PSPGSs that showed significant associations in the univariate analysis (combined PSPGS) increased the percentage of variance explained (R2) to 3.71% and 3.18% for the categorical and continuous outcomes, respectively. Associations for PGSs for GABA and circadian rhythm were replicated. Patients with the highest genetic loading (10th decile) for acetylcholine variants were 3.03 times more likely (95% CI, 1.95 to 4.69) to show a good lithium response (categorical outcome) than patients with the lowest genetic loading (1st decile).
Conclusions
PSPGSs achieved predictive performance comparable to the conventional genome-wide PGSs, with the added advantage of biological interpretability using a smaller list of genetic variants.
