Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.

We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.

Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs.

An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.

There is growing interest in using composite individualized treatment rules (ITRs) to guide depression treatment selection, but best approaches for doing this are not widely known. We develop an ITR for depression remission based on secondary analysis of a recently published trial for second-line antidepression medication selection using a cutting-edge ensemble machine learning method.

Data come from the SUN(^_^)D trial, an open-label, assessor blinded pragmatic trial of previously-untreated patients with major depressive disorder from 48 clinics in Japan. Initial clinic-level randomization assigned patients to 50 or 100 mg/day sertraline. We focus on the 1549 patients who failed to remit within 3 weeks and were then rerandomized at the individual-level to continuation with sertraline, switching to mirtazapine, or combining mirtazapine with sertraline. The outcome was remission 9 weeks post-baseline. Predictors included socio-demographics, clinical characteristics, baseline symptoms, changes in symptoms between baseline and week 3, and week 3 side effects.

Optimized treatment was associated with significantly increased cross-validated week 9 remission rates in both samples [5.3% (2.4%), p = 0.016 50 mg/day sample; 5.1% (2.7%), p = 0.031 100 mg/day sample] compared to randomization (30.1–30.8%). Optimization was also associated with significantly increased remission in both samples compared to continuation [24.7% in both: 11.2% (3.8%), p = 0.002 50 mg/day sample; 11.7% (3.9%), p = 0.001 100 mg/day sample]. Non-significant gains were found for optimization compared to switching or combining.

An ITR can be developed to improve second-line antidepressant selection, but replication in a larger study with more comprehensive baseline predictors might produce stronger and more stable results.

One important aspect of the societal burden of mental disorders is the extent to which these problems cause disability.

To assess days out of role associated with commonly occurring mental disorders in comparison with physical disorders in Portugal.

National cross-sectional survey, with home interviews carried out with 3849 adult (aged 18+) respondents (57.3% response rate).

Twelve-month prevalence for any mental disorder was 21.8%, any physical disorder 55.1% and any disorder 63.1%, with an average of 2.3 disorders per respondent with a disorder. Close to one out of every 10 respondents (9.2%) reported at least one day totally out of role in the past month (median of 6.4 days/any). The 18 conditions accounted for 78.2% of all days out of role, with 20.2% because of mental disorders and 59.2% because of physical disorders.

Mental disorders account for a substantial proportion of all role disability in the Portuguese population. Early detection and intervention would have a positive societal effect. Owing to highly frequent comorbidity, simultaneous management of mental and physical disorder comorbidities is advised for greater effect.

Although childhood adversities are known to predict increased risk of post-traumatic stress disorder (PTSD) after traumatic experiences, it is unclear whether this association varies by childhood adversity or traumatic experience types or by age.

To examine variation in associations of childhood adversities with PTSD according to childhood adversity types, traumatic experience types and life-course stage.

Epidemiological data were analysed from the World Mental Health Surveys (n = 27017).

Four childhood adversities (physical and sexual abuse, neglect, parent psychopathology) were associated with similarly increased odds of PTSD following traumatic experiences (odds ratio (OR)=1.8), whereas the other eight childhood adversities assessed did not predict PTSD. Childhood adversity–PTSD associations did not vary across traumatic experience types, but were stronger in childhood-adolescence and early-middle adulthood than later adulthood.

Childhood adversities are differentially associated with PTSD, with the strongest associations in childhood-adolescence and early-middle adulthood. Consistency of associations across traumatic experience types suggests that childhood adversities are associated with generalised vulnerability to PTSD following traumatic experiences.

Burden-of-illness data, which are often used in setting healthcare policy-spending priorities, are unavailable for mental disorders in most countries.

To examine one central aspect of illness burden, the association of serious mental illness with earnings, in the World Health Organization (WHO) World Mental Health (WMH) Surveys.

The WMH Surveys were carried out in 10 high-income and 9 low- and middle-income countries. The associations of personal earnings with serious mental illness were estimated.

Respondents with serious mental illness earned on average a third less than median earnings, with no significant between-country differences (χ2(9) = 5.5–8.1, P = 0.52–0.79). These losses are equivalent to 0.3–0.8% of total national earnings. Reduced earnings among those with earnings and the increased probability of not earning are both important components of these associations.

These results add to a growing body of evidence that mental disorders have high societal costs. Decisions about healthcare resource allocation should take these costs into consideration.

The epidemiology of rapid-cycling bipolar disorder in the community is largely unknown.

To investigate the epidemiological characteristics of rapid-cycling and non-rapid-cycling bipolar disorder in a large cross-national community sample.

The Composite International Diagnostic Interview (CIDI version 3.0) was used to examine the prevalence, severity, comorbidity, impairment, suicidality, sociodemographics, childhood adversity and treatment of rapid-cycling and non-rapid-cycling bipolar disorder in ten countries(n = 54 257).

The 12-month prevalence of rapid-cycling bipolar disorder was 0.3%. Roughly a third and two-fifths of participants with lifetime and 12-month bipolar disorder respectively met criteria for rapid cycling. Compared with the non-rapid-cycling, rapid-cycling bipolar disorder was associated with younger age at onset, higher persistence, more severe depressive symptoms, greater impairment from depressive symptoms, more out-of-role days from mania/hypomania, more anxiety disorders and an increased likelihood of using health services. Associations regarding childhood, family and other sociodemographic correlates were less clear cut.

The community epidemiological profile of rapid-cycling bipolar disorder confirms most but not all current clinically based knowledge about the illness.

Advocates of expanded mental health treatment assert that mental disorders are as disabling as physical disorders, but little evidence supports this assertion.

To establish the disability and treatment of specific mental and physical disorders in high-income and low- and middle-income countries.

Community epidemiological surveys were administered in 15 countries through the World Health Organization World Mental Health (WMH) Survey Initiative.

Respondents in both high-income and low- and middle-income countries attributed higher disability to mental disorders than to the commonly occurring physical disorders included in the surveys. This pattern held for all disorders and also for treated disorders. Disaggregation showed that the higher disability of mental than physical disorders was limited to disability in social and personal role functioning, whereas disability in productive role functioning was generally comparable for mental and physical disorders.

Despite often higher disability, mental disorders are under-treated compared with physical disorders in both high-income and in low- and middle-income countries.