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.

Despite multiple ethical issues and little evidence of their efficacy, compulsory admission and treatment are still common psychiatric practice. Therefore, we aimed to assess potential differences in treatment and outcome between voluntarily and compulsorily admitted patients.

We extracted clinical data from inpatients treated in an academic hospital in Zurich, Switzerland between January 1, 2013 and December 31, 2019. Observation time started upon the first admission and ended after a one-year follow-up after the last discharge. Several sociodemographic and clinical characteristics, including Health of the Nation Outcome Scales (HoNOS) scores, were retrospectively obtained. We then identified risk factors of compulsory admission using logistic regression in order to perform a widely balanced propensity score matching. Altogether, we compared 4,570 compulsorily and 4,570 voluntarily admitted propensity score-matched patients. Multiple differences between these groups concerning received treatment, coercive measures, clinical parameters, and service use outcomes were detected.

Upon discharge, compulsorily admitted patients reached a similar HoNOS sum score in a significantly shorter duration of treatment. They were more often admitted for crisis interventions, were prescribed less pharmacologic treatment, and received fewer therapies. During the follow-up, voluntarily admitted patients were readmitted more often, while the time to readmission did not differ.

Under narrowly set circumstances, compulsory admissions might be helpful to avert and relieve exacerbations of severe psychiatric disorders.

Despite increased research interest in smartphone mental health applications (MHapps), few studies have examined user engagement and its determinants. MoodMission is a MHapp that targets low mood and anxiety via evidence-based techniques including behavioural activation (BA).

The present study aimed to investigate (i) whether BA interventions delivered with visual psychoeducation had greater engagement than BA interventions delivered with solely written psychoeducation, (ii) whether BA interventions targeting mastery would have greater engagement than those targeting pleasure, and (iii) the relationship between level of engagement and MHapp benefit.

Participants downloaded MoodMission and completed activities and within-app evaluations over a 30-day period. Data from 238 MoodMission users were analysed via multi-level modelling and linear regression.

The average number of app-based activities completed was 5.46 and the average self-reported engagement level was in the low to moderate range. As hypothesized, higher levels of engagement significantly predicted more positive activity appraisal.

The results suggest that BA technique beliefs are involved in MHapp engagement and future research examining user appraisals of techniques is warranted.

The influence of baseline severity has been examined for antidepressant medications but has not been studied properly for cognitive–behavioural therapy (CBT) in comparison with pill placebo.

To synthesise evidence regarding the influence of initial severity on efficacy of CBT from all randomised controlled trials (RCTs) in which CBT, in face-to-face individual or group format, was compared with pill-placebo control in adults with major depression.

A systematic review and an individual-participant data meta-analysis using mixed models that included trial effects as random effects. We used multiple imputation to handle missing data.

We identified five RCTs, and we were given access to individual-level data (n = 509) for all five. The analyses revealed that the difference in changes in Hamilton Rating Scale for Depression between CBT and pill placebo was not influenced by baseline severity (interaction P = 0.43). Removing the non-significant interaction term from the model, the difference between CBT and pill placebo was a standardised mean difference of –0.22 (95% CI –0.42 to –0.02, P = 0.03, I 2 = 0%).

Patients suffering from major depression can expect as much benefit from CBT across the wide range of baseline severity. This finding can help inform individualised treatment decisions by patients and their clinicians.