A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication.

To develop and evaluate a model that could predict the risk of TRS in routine clinical practice.

We used data from two UK-based FEP cohorts (GAP and AESOP-10) to develop and internally validate a prognostic model that supports identification of patients at high-risk of TRS soon after FEP diagnosis. Using sociodemographic and clinical predictors, a model for predicting risk of TRS was developed based on penalised logistic regression, with missing data handled using multiple imputation. Internal validation was undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. Interviews and focus groups with clinicians were conducted to establish clinically relevant risk thresholds and understand the acceptability and perceived utility of the model.

We included seven factors in the prediction model that are predominantly assessed in clinical practice in patients with FEP. The model predicted treatment resistance among the 1081 patients with reasonable accuracy; the model's C-statistic was 0.727 (95% CI 0.723–0.732) prior to shrinkage and 0.687 after adjustment for optimism. Calibration was good (expected/observed ratio: 0.999; calibration-in-the-large: 0.000584) after adjustment for optimism.

We developed and internally validated a prediction model with reasonably good predictive metrics. Clinicians, patients and carers were involved in the development process. External validation of the tool is needed followed by co-design methodology to support implementation in early intervention services.

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.

Childhood trauma and adversity are common across societies and have strong associations with physical and psychiatric morbidity throughout the life-course. One possible mechanism through which childhood trauma may predispose individuals to poor psychiatric outcomes is via associations with brain structure. This study aimed to elucidate the associations between childhood trauma and brain structure across two large, independent community cohorts.

The two samples comprised (i) a subsample of Generation Scotland (n=1,024); and (ii) individuals from UK Biobank (n=27,202). This comprised n=28,226 for mega-analysis. MRI scans were processed using Free Surfer, providing cortical, subcortical, and global brain metrics. Regression models were used to determine associations between childhood trauma measures and brain metrics and psychiatric phenotypes.

Childhood trauma associated with lifetime depression across cohorts (OR 1.06 GS, 1.23 UKB), and related to early onset and recurrent course within both samples. There was evidence for associations between childhood trauma and structural brain metrics. This included reduced global brain volume, and reduced cortical surface area with highest effects in the frontal (β=−0.0385, SE=0.0048, p(FDR)=5.43x10−15) and parietal lobes (β=−0.0387, SE=0.005, p(FDR)=1.56x10−14). At a regional level the ventral diencephalon (VDc) displayed significant associations with childhood trauma measures across both cohorts and at mega-analysis (β=−0.0232, SE=0.0039, p(FDR)=2.91x10−8). There were also associations with reduced hippocampus, thalamus, and nucleus accumbens volumes.

Associations between childhood trauma and reduced global and regional brain volumes were found, across two independent UK cohorts, and at mega-analysis. This provides robust evidence for a lasting effect of childhood adversity on brain structure.

Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls.

Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses).

For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent.

This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals.

The transition from military service to civilian life is a high-risk period for suicide attempts (SAs). Although stressful life events (SLEs) faced by transitioning soldiers are thought to be implicated, systematic prospective evidence is lacking.

Participants in the Army Study to Assess Risk and Resilience in Servicemembers (STARRS) completed baseline self-report surveys while on active duty in 2011–2014. Two self-report follow-up Longitudinal Surveys (LS1: 2016–2018; LS2: 2018–2019) were subsequently administered to probability subsamples of these baseline respondents. As detailed in a previous report, a SA risk index based on survey, administrative, and geospatial data collected before separation/deactivation identified 15% of the LS respondents who had separated/deactivated as being high-risk for self-reported post-separation/deactivation SAs. The current report presents an investigation of the extent to which self-reported SLEs occurring in the 12 months before each LS survey might have mediated/modified the association between this SA risk index and post-separation/deactivation SAs.

The 15% of respondents identified as high-risk had a significantly elevated prevalence of some post-separation/deactivation SLEs. In addition, the associations of some SLEs with SAs were significantly stronger among predicted high-risk than lower-risk respondents. Demographic rate decomposition showed that 59.5% (s.e. = 10.2) of the overall association between the predicted high-risk index and subsequent SAs was linked to these SLEs.

It might be possible to prevent a substantial proportion of post-separation/deactivation SAs by providing high-risk soldiers with targeted preventive interventions for exposure/vulnerability to commonly occurring SLEs.

As an accelerated cognitive decline frequently heralds onset of severe neuropathological disorders, understanding the source of individual differences in withstanding the onslaught of cognitive ageing may highlight how best cognitive abilities may be retained into advanced age.

Using a population representative sample of 5088 adults aged •50 years from the English Longitudinal Study of Ageing, we investigated relationships of polygenic predisposition to general cognition with a rate of change in cognition during a 10-year follow-up period. Polygenic predisposition was measured with polygenic scores for general cognition (GC-PGS). Cognition was measured employing tests for verbal memory and semantic fluency.

The average baseline memory score was 11.1 (s.d. = 2.9) and executive function score was 21.5 (s.d. = 5.8). An increase in GC-PGS by one standard deviation (1-s.d.) was associated with a higher baseline verbal memory by an average 0.27 points (95% CI 0.19–0.34, p < 0.001). Similarly, 1-s.d. increase in GC-PGS was associated with a higher semantic fluency score at baseline in the entire sample (β = 0.45, 95% CI 0.27–0.64, p < 0.001). These associations were significant for women and men, and all age groups. Nonetheless, 1-s.d. increase in GC-PGS was not associated with decreases in verbal memory nor semantic fluency during follow-up in the entire sample, as well stratified models by sex and age.

Although common genetic variants associated with general cognition additively are associated with a stable surplus to cognition in adults, a polygenic predisposition to general cognition is not associated with age-related cognitive decline during a 10-year follow-up.

Recently the NHS has expanded the provision of liaison mental health services (LMHS) to ensure that every acute hospital with an emergency department in England has a liaison psychiatry service. Little work has been undertaken to explore first-hand experiences of these services. The aim of this study was to capture service users’ experiences of LMHS in both emergency departments and acute inpatient wards in the UK, with a view to adapt services to better meet the needs of its users.

This cross-sectional internet survey was initially advertised from May-July 2017 using the social media platform Facebook. Due to a paucity of male respondents, it was re-run from November 2017-February 2018, specifically targeting this demographic group. 184 people responded to the survey, of which 147 were service users and 37 were service users’ accompanying partners, friends or family members. The survey featured a structured questionnaire divided into three categories: the profile of the respondent, perceived professionalism of LMHS, and overall opinion of the service. Space was available for free-text comments in each section. Descriptive analysis of quantitative data was undertaken with R statistical software V.3.2.2. Qualitative data from free-text comments were transcribed and interpreted independently by three researchers using framework analysis; familiarisation with the data was followed by identification of a thematic framework, indexing, charting, mapping and interpretation.

Opinions of the service were mixed but predominantly negative. 31% of service users and 27% of their loved ones found their overall contact with LMHS useful. Features most frequently identified as important were the provision of a 24/7 service, assessment by a variety of healthcare professionals and national standardisation of services. Respondents indicated that the least important feature was the provision of a separate service for older people. They also expressed that a desirable LMHS would include faster assessments following referral from the parent team, clearer communication about next steps and greater knowledge of local services and third sector organisations.

Our survey identified mixed responses, however service users and their loved ones perceived LMHS more frequently as negative than positive. This may be attributed to the recent governmental drive to assess, treat and discharge 95% of all patients seen in emergency departments within four hours of initial attendance. Additionally, dissatisfied service users are more likely to volunteer their opinions. The evaluation and adaptation of LMHS should be prioritised to enhance their inherent therapeutic value and improve engagement with treatment and future psychiatric care.

We assessed long-term incidence and prevalence trends of dementia and parkinsonism across major ethnic and immigrant groups in Ontario.

Linking administrative databases, we established two cohorts (dementia 2001–2014 and parkinsonism 2001–2015) of all residents aged 20 to 100 years with incident diagnosis of dementia (N = 387,937) or parkinsonism (N = 59,617). We calculated age- and sex-standardized incidence and prevalence of dementia and parkinsonism by immigrant status and ethnic groups (Chinese, South Asian, and the General Population). We assessed incidence and prevalence trends using Poisson regression and Cochran–Armitage trend tests.

Across selected ethnic groups, dementia incidence and prevalence were higher in long-term residents than recent or longer-term immigrants from 2001 to 2014. During this period, age- and sex-standardized incidence of dementia in Chinese, South Asian, and the General Population increased, respectively, among longer-term immigrants (by 41%, 58%, and 42%) and long-term residents (28%, 7%, and 4%), and to a lesser degree among recent immigrants. The small number of cases precluded us from assessing parkinsonism incidence trends. For Chinese, South Asian, and the General Population, respectively, prevalence of dementia and parkinsonism modestly increased over time among recent immigrants but significantly increased among longer-term immigrants (dementia: 134%, 217%, and 117%; parkinsonism: 55%, 54%, and 43%) and long-term residents (dementia: 97%, 132%, and 71%; parkinsonism: 18%, 30%, and 29%). Adjustment for pre-existing conditions did not appear to explain incidence trends, except for stroke and coronary artery disease as potential drivers of dementia incidence.

Recent immigrants across major ethnic groups in Ontario had considerably lower rates of dementia and parkinsonism than long-term residents, but this difference diminished with longer-term immigrants.