The needs of young people attending mental healthcare can be complex and often span multiple domains (e.g., social, emotional and physical health factors). These factors often complicate treatment approaches and contribute to poorer outcomes in youth mental health. We aimed to identify how these factors interact over time by modelling the temporal dependencies between these transdiagnostic social, emotional and physical health factors among young people presenting for youth mental healthcare.

Dynamic Bayesian networks were used to examine the relationship between mental health factors across multiple domains (social and occupational function, self-harm and suicidality, alcohol and substance use, physical health and psychiatric syndromes) in a longitudinal cohort of 2663 young people accessing youth mental health services. Two networks were developed: (1) ‘initial network’, that shows the conditional dependencies between factors at first presentation, and a (2) ‘transition network’, how factors are dependent longitudinally.

The ‘initial network’ identified that childhood disorders tend to precede adolescent depression which itself was associated with three distinct pathways or illness trajectories; (1) anxiety disorder; (2) bipolar disorder, manic-like experiences, circadian disturbances and psychosis-like experiences; (3) self-harm and suicidality to alcohol and substance use or functioning. The ‘transition network’ identified that over time social and occupational function had the largest effect on self-harm and suicidality, with direct effects on ideation (relative risk [RR], 1.79; CI, 1.59–1.99) and self-harm (RR, 1.32; CI, 1.22–1.41), and an indirect effect on attempts (RR, 2.10; CI, 1.69–2.50). Suicide ideation had a direct effect on future suicide attempts (RR, 4.37; CI, 3.28–5.43) and self-harm (RR, 2.78; CI, 2.55–3.01). Alcohol and substance use, physical health and psychiatric syndromes (e.g., depression and anxiety, at-risk mental states) were independent domains whereby all direct effects remained within each domain over time.

This study identified probable temporal dependencies between domains, which has causal interpretations, and therefore can provide insight into their differential role over the course of illness. This work identified social, emotional and physical health factors that may be important early intervention and prevention targets. Improving social and occupational function may be a critical target due to its impacts longitudinally on self-harm and suicidality. The conditional independence of alcohol and substance use supports the need for specific interventions to target these comorbidities.

Subthreshold/attenuated syndromes are established precursors of full-threshold mood and psychotic disorders. Less is known about the individual symptoms that may precede the development of subthreshold syndromes and associated social/functional outcomes among emerging adults.

We modeled two dynamic Bayesian networks (DBN) to investigate associations among self-rated phenomenology and personal/lifestyle factors (role impairment, low social support, and alcohol and substance use) across the 19Up and 25Up waves of the Brisbane Longitudinal Twin Study. We examined whether symptoms and personal/lifestyle factors at 19Up were associated with (a) themselves or different items at 25Up, and (b) onset of a depression-like, hypo-manic-like, or psychotic-like subthreshold syndrome (STS) at 25Up.

The first DBN identified 11 items that when endorsed at 19Up were more likely to be reendorsed at 25Up (e.g., hypersomnia, impaired concentration, impaired sleep quality) and seven items that when endorsed at 19Up were associated with different items being endorsed at 25Up (e.g., earlier fatigue and later role impairment; earlier anergia and later somatic pain). In the second DBN, no arcs met our a priori threshold for inclusion. In an exploratory model with no threshold, >20 items at 19Up were associated with progression to an STS at 25Up (with lower statistical confidence); the top five arcs were: feeling threatened by others and a later psychotic-like STS; increased activity and a later hypo-manic-like STS; and anergia, impaired sleep quality, and/or hypersomnia and a later depression-like STS.

These probabilistic models identify symptoms and personal/lifestyle factors that might prove useful targets for indicated preventative strategies.

Non-alcoholic fatty liver disease (NAFLD) is an increasing cause of chronic liver disease that accompanies obesity and the metabolic syndrome. Excess fructose consumption can initiate or exacerbate NAFLD in part due to a consequence of impaired hepatic fructose metabolism. Preclinical data emphasized that fructose-induced altered gut microbiome, increased gut permeability, and endotoxemia play an important role in NAFLD, but human studies are sparse. The present study aimed to determine if two weeks of excess fructose consumption significantly alters gut microbiota or permeability in humans.

We performed a pilot double-blind, cross-over, metabolic unit study in 10 subjects with obesity (body mass index [BMI] 30–40 mg/kg/m2). Each arm provided 75 grams of either fructose or glucose added to subjects’ individual diets for 14 days, substituted isocalorically for complex carbohydrates, with a 19-day wash-out period between arms. Total fructose intake provided in the fructose arm of the study totaled a mean of 20.1% of calories. Outcome measures included fecal microbiota distribution, fecal metabolites, intestinal permeability, markers of endotoxemia, and plasma metabolites.

Routine blood, uric acid, liver function, and lipid measurements were unaffected by the fructose intervention. The fecal microbiome (including Akkermansia muciniphilia), fecal metabolites, gut permeability, indices of endotoxemia, gut damage or inflammation, and plasma metabolites were essentially unchanged by either intervention.

In contrast to rodent preclinical findings, excess fructose did not cause changes in the gut microbiome, metabolome, and permeability as well as endotoxemia in humans with obesity fed fructose for 14 days in amounts known to enhance NAFLD.

Black, Asian and minority ethnicity groups may experience better health outcomes when living in areas of high own-group ethnic density – the so-called ‘ethnic density’ hypothesis. We tested this hypothesis for the treatment outcome of compulsory admission.

Data from the 2010–2011 Mental Health Minimum Dataset (N = 1 053 617) was linked to the 2011 Census and 2010 Index of Multiple Deprivation. Own-group ethnic density was calculated by dividing the number of residents per ethnic group for each lower layer super output area (LSOA) in the Census by the LSOA total population. Multilevel modelling estimated the effect of own-group ethnic density on the risk of compulsory admission by ethnic group (White British, White other, Black, Asian and mixed), accounting for patient characteristics (age and gender), area-level deprivation and population density.

Asian and White British patients experienced a reduced risk of compulsory admission when living in the areas of high own-group ethnic density [odds ratios (OR) 0.97, 95% credible interval (CI) 0.95–0.99 and 0.94, 95% CI 0.93–0.95, respectively], whereas White minority patients were at increased risk when living in neighbourhoods of higher own-group ethnic concentration (OR 1.18, 95% CI 1.11–1.26). Higher levels of own-group ethnic density were associated with an increased risk of compulsory admission for mixed-ethnicity patients, but only when deprivation and population density were excluded from the model. Neighbourhood-level concentration of own-group ethnicity for Black patients did not influence the risk of compulsory admission.

We found only minimal support for the ethnic density hypothesis for the treatment outcome of compulsory admission to under the Mental Health Act.

Despite its pivotal role in prophylaxis for bipolar-I-disorders (BD-I), variability in lithium (Li) response is poorly understood and only a third of patients show a good outcome. Converging research strands indicate that rest–activity rhythms can help characterize BD-I and might differentiate good responders (GR) and non-responders (NR).

Seventy outpatients with BD-I receiving Li prophylaxis were categorized as GR or NR according to the ratings on the retrospective assessment of response to lithium scale (Alda scale). Participants undertook 21 consecutive days of actigraphy monitoring of sleep quantity (SQ), sleep variability (SV) and circadian rhythmicity (CR).

Twenty-five individuals were categorized as GR (36%). After correcting statistical analysis to minimize false discoveries, four variables (intra-daily variability; median activity level; amplitude; and relative amplitude of activity) significantly differentiated GR from NR. The odds of being classified as a GR case were greatest for individuals showing more regular/stable CR (1.41; 95% confidence interval (CI) 1.08, 2.05; p < 0.04). Also, there was a trend for lower SV to be associated with GR (odds ratio: 0.56; 95% CI 0.31, 1.01; p < 0.06).

To our knowledge, this is the largest actigraphy study of rest–activity rhythms and Li response. Circadian markers associated with fragmentation, variability, amount and/or amplitude of day and night-time activity best-identified GR. However, associations were modest and future research must determine whether these objectively measured parameters, singly or together, represent robust treatment response biomarkers. Actigraphy may offer an adjunct to multi-platform approaches aimed at developing personalized treatments or stratification of individuals with BD-I into treatment-relevant subgroups.

Predictors of new-onset bipolar disorder (BD) or psychotic disorder (PD) have been proposed on the basis of retrospective or prospective studies of ‘at-risk’ cohorts. Few studies have compared concurrently or longitudinally factors associated with the onset of BD or PDs in youth presenting to early intervention services. We aimed to identify clinical predictors of the onset of full-threshold (FT) BD or PD in this population.

Multi-state Markov modelling was used to assess the relationships between baseline characteristics and the likelihood of the onset of FT BD or PD in youth (aged 12–30) presenting to mental health services.

Of 2330 individuals assessed longitudinally, 4.3% (n = 100) met criteria for new-onset FT BD and 2.2% (n = 51) met criteria for a new-onset FT PD. The emergence of FT BD was associated with older age, lower social and occupational functioning, mania-like experiences (MLE), suicide attempts, reduced incidence of physical illness, childhood-onset depression, and childhood-onset anxiety. The emergence of a PD was associated with older age, male sex, psychosis-like experiences (PLE), suicide attempts, stimulant use, and childhood-onset depression.

Identifying risk factors for the onset of either BD or PDs in young people presenting to early intervention services is assisted not only by the increased focus on MLE and PLE, but also by recognising the predictive significance of poorer social function, childhood-onset anxiety and mood disorders, and suicide attempts prior to the time of entry to services. Secondary prevention may be enhanced by greater attention to those risk factors that are modifiable or shared by both illness trajectories.

Opioid use disorder is a major public health crisis, and evidence suggests ways of better serving patients who live with opioid use disorder in the emergency department (ED). A multi-disciplinary team developed a quality improvement project to implement this evidence.

The intervention was developed by an expert working group consisting of specialists and stakeholders. The group set goals of increasing prescribing of buprenorphine/naloxone and providing next day walk-in referrals to opioid use disorder treatment clinics. From May to September 2018, three Alberta ED sites and three opioid use disorder treatment clinics worked together to trial the intervention. We used administrative data to track the number of ED visits where patients were given buprenorphine/naloxone. Monthly ED prescribing rates before and after the intervention were considered and compared with eight nonintervention sites. We considered whether patients continued to fill opioid agonist treatment prescriptions at 30, 60, and 90 days after their index ED visit to measure continuity in treatment.

The intervention sites increased their prescribing of buprenorphine/naloxone during the intervention period and prescribed more buprenorphine/naloxone than the controls. Thirty-five of 47 patients (74.4%) discharged from the ED with buprenorphine/naloxone continued to fill opioid agonist treatment prescriptions 30 days and 60 days after their index ED visit. Thirty-four patients (72.3%) filled prescriptions at 90 days.

Emergency clinicians can effectively initiate patients on buprenorphine/naloxone when supports for this standardized evidence-based care are in place within their practice setting and timely follow-up in community is available.

Neurocognitive impairments robustly predict functional outcome. However, heterogeneity in neurocognition is common within diagnostic groups, and data-driven analyses reveal homogeneous neurocognitive subgroups cutting across diagnostic boundaries.

To determine whether data-driven neurocognitive subgroups of young people with emerging mental disorders are associated with 3-year functional course.

Model-based cluster analysis was applied to neurocognitive test scores across nine domains from 629 young people accessing mental health clinics. Cluster groups were compared on demographic, clinical and substance-use measures. Mixed-effects models explored associations between cluster-group membership and socio-occupational functioning (using the Social and Occupational Functioning Assessment Scale) over 3 years, adjusted for gender, premorbid IQ, level of education, depressive, positive, negative and manic symptoms, and diagnosis of a primary psychotic disorder.

Cluster analysis of neurocognitive test scores derived three subgroups described as ‘normal range’ (n = 243, 38.6%), ‘intermediate impairment’ (n = 252, 40.1%), and ‘global impairment’ (n = 134, 21.3%). The major mental disorder categories (depressive, anxiety, bipolar, psychotic and other) were represented in each neurocognitive subgroup. The global impairment subgroup had lower functioning for 3 years of follow-up; however, neither the global impairment (B = 0.26, 95% CI −0.67 to 1.20; P = 0.581) or intermediate impairment (B = 0.46, 95% CI −0.26 to 1.19; P = 0.211) subgroups differed from the normal range subgroup in their rate of change in functioning over time.

Neurocognitive impairment may follow a continuum of severity across the major syndrome-based mental disorders, with data-driven neurocognitive subgroups predictive of functional course. Of note, the global impairment subgroup had longstanding functional impairment despite continuing engagement with clinical services.

J.S. and G.M. are members of mMARCH, (Motor Activity Research Consortium for Health), which is led by Dr Kathleen Merikangas, National Institute for Mental Health. J.S. reports being a visiting professor at Diderot University, the Norwegian University of Science and Technology, Swinburne University of Technology and The University of Sydney; receiving grant funding from the UK Medical Research Council and from the UK Research for Patient Benefit programme; and receiving a personal fee from Janssen-Cilag for a non-promotional talk on sleep problems.

To compare rates of admission for different types of severe mental illness between ethnic groups, and to test the hypothesis that larger and more clustered ethnic groups will have lower admission rates. This was a descriptive study of routinely collected data from the National Health Service in England.

There was an eightfold difference in admission rates between ethnic groups for schizophreniform and mania admissions, and a fivefold variation in depression admissions. On average, Black and minority ethnic (BME) groups had higher rates of admission for schizophreniform and mania admissions but not for depression. This increased rate was greatest in the teenage years and early adulthood. Larger ethnic group size was associated with lower admission rates. However, greater clustering was associated with higher admission rates.

Our findings support the hypothesis that larger ethnic groups have lower rates of admission. This was a between-group comparison rather than within each group. Our findings do not support the hypothesis that more clustered groups have lower rates of admission. In fact, they suggest the opposite: groups with low clustering had lower admission rates. The BME population in the UK is increasing in size and becoming less clustered. Our results suggest that both of these factors should ameliorate the overrepresentation of BME groups among psychiatric in-patients. However, this overrepresentation continues, and our results suggest a possible explanation, namely, changes in the delivery of mental health services, particularly the marked reduction in admissions for depression.

None.

Transition from at-risk state to full syndromal mental disorders is underexplored for unipolar and bipolar disorders compared with psychosis.

Prospective, trans-diagnostic study of rates and predictors of early transition from sub-threshold to full syndromal mental disorder.

One-year outcome of 243 consenting youth aged 15–25 years with a sub-syndromal presentation of a potentially severe mental disorder. Survival analysis and odds ratio (OR) for predictors of transition identified from baseline clinical and demographic ratings.

About 17% (n=36) experienced transition to a major mental disorder. Independent of syndromal diagnosis, transition was significantly more likely in individuals who were NEET (not in education, employment or training), in females and in those with more negative psychological symptoms (e.g. social withdrawal).

NEET status and negative symptoms are modifiable predictors of illness trajectory across diagnostic categories and are not specific to transition to psychosis.

• Gain awareness of some limitations of current approaches to psychiatric diagnosis

• Review the basic principles of clinical staging models used in general medicine

• Understand current research on the use of staging models in psychiatry, and attempts to apply these models to bipolar disorders