Early intervention in psychosis (EIP) services improve outcomes for young people, but approximately 30% disengage.

To test whether a new motivational engagement intervention would prolong engagement and whether it was cost-effective.

We conducted a multicentre, single-blind, parallel-group, cluster randomised controlled trial involving 20 EIP teams at five UK National Health Service (NHS) sites. Teams were randomised using permuted blocks stratified by NHS trust. Participants were all young people (aged 14–35 years) presenting with a first episode of psychosis between May 2019 and July 2020 (N = 1027). We compared the novel Early Youth Engagement (EYE-2) intervention plus standardised EIP (sEIP) with sEIP alone. The primary outcome was time to disengagement over 12–26 months. Economic outcomes were mental health costs, societal costs and socio-occupational outcomes over 12 months. Assessors were masked to treatment allocation for primary disengagement and cost-effectiveness outcomes. Analysis followed intention-to-treat principles. The trial was registered at ISRCTN51629746.

Disengagement was low at 15.9% overall in standardised stand-alone services. The adjusted hazard ratio for EYE-2 + sEIP (n = 652) versus sEIP alone (n = 375) was 1.07 (95% CI 0.76–1.49; P = 0.713). The health economic evaluation indicated lower mental healthcare costs linked to reductions in unplanned mental healthcare with no compromise of clinical outcomes, as well as some evidence for lower societal costs and more days in education, training, employment and stable accommodation in the EYE-2 group.

We found no evidence that EYE-2 increased time to disengagement, but there was some evidence for its cost-effectiveness. This is the largest study to date reporting positive engagement, health and cost outcomes in a total EIP population sample. Limitations included high loss to follow-up for secondary outcomes and low completion of societal and socio-occupational data. COVID-19 affected fidelity and implementation. Future engagement research should target engagement to those in greatest need, including in-patients and those with socio-occupational goals.

Congress directed the Secretary of Defense (DoD) to conduct a Pilot program to increase the National Disaster Medical System’s (NDMS) surge capacity, capabilities, and interoperability to support patient movement during a large-scale overseas contingency operation.

The Pilot conducted a mixed methods exploratory study, the Military-Civilian NDMS Interoperability Study (MCNIS), identifying 55 areas of solutions for NDMS innovation that align with interagency stakeholder interests. Priorities were determined via facilitated discussions, refined and validated by all five Pilot sites.

As the DoD provides essential support for the patient movement component within NDMS, the results highlighted areas for improvement between receiving patients at an airfield and moving them to NDMS definitive care partners during a large medical surge event. This includes patient tracking capabilities, transportation processes and patient placement.

In collaboration with the Departments of Health & Human Services, Homeland Security, Transportation, and Veterans Health Administration, the Pilot is addressing these areas for improvement, by executing site-specific projects that will be validated and identified for export across the system. Leaders across the Pilot site healthcare networks are working to enhance patient movement and tracking. Ultimately, the Pilot will deliver dozens of proven solutions to enhance the NDMS’s patient movement capabilities.

Scalable methods are required for population dietary monitoring. The Supermarket Transaction Records In Dietary Evaluation (STRIDE) study compares dietary estimates from supermarket transactions with an online FFQ.

Participants were recruited in four waves, accounting for seasonal dietary variation. Purchases were collected for 1 year during and 1 year prior to the study. Bland–Altman agreement and limits of agreement (LoA) were calculated for energy, sugar, fat, saturated fat, protein and sodium (absolute and relative).

This study was partnered with a large UK retailer.

Totally, 1788 participants from four UK regions were recruited from the retailer’s loyalty card customer database, according to breadth and frequency of purchases. Six hundred and eighty-six participants were included for analysis.

The analysis sample were mostly female (72 %), with a mean age of 56 years (sd 13). The ratio of purchases to intakes varied depending on amounts purchased and consumed; purchases under-estimated intakes for smaller amounts on average, but over-estimated for larger amounts. For absolute measures, the LoA across households were wide, for example, for energy intake of 2000 kcal, purchases could under- or over-estimate intake by a factor of 5; values could be between 400 kcal and 10000 kcal. LoA for relative (energy-adjusted) estimates were smaller, for example, for 14 % of total energy from saturated fat, purchase estimates may be between 7 % and 27 %.

Agreement between purchases and intake was highly variable, strongest for smaller loyal households and for relative values. For some customers, relative nutrient purchases are a reasonable proxy for dietary composition indicating utility in population-level dietary research.

1. To evaluate demand, capacity and flow of an integrated community learning disability service in a peri- and post-COVID-19 pandemic setting. 2. To improve flow of a community learning disability service. 3. To improve staff and service user satisfaction by engaging them and identifying common priorities.

We collected demand and capacity data of all disciplines in a community learning disability service for 2021–2022.

We carried out focus groups with service users and their carers (N = 5) and surveyed them with a questionnaire consisting of 6 quantitative and 2 qualitative questions (N = 63), investigating the impact of waiting times on service user experience.

We surveyed staff from all disciplines (N = 20) with a questionnaire consisting of 3 qualitative questions, to identify their views on waiting times and areas to optimise.

We performed thematic analysis on all qualitative responses. We analysed quantitative data with descriptive statistics.

From 2021–22, the number of accepted referrals to individual disciplines increased: for example referrals to psychiatry increased by 51.6% and referrals to OT increased by 32%.

With regard to flow, the ratio of discharges to accepted referrals in the psychiatry discipline decreased from 1.5:1 to 0.6:1.

A significant proportion of service users reported waiting months (31%) or years (16%) to be seen by the learning disability team. 28% of service users reported additional problems while waiting to be seen. 31% were unaware whether they were on a waiting list or not. Quantitative data showed average waiting times for psychiatry services did not change from 2021–2022 (23.1 and 23.3 days respectively).

Thematic analysis from service users’ responses revealed an anxiety about needs not being met; a feeling of problems deteriorating while waiting; and communication issues.

Staff responses revealed desires to intervene sooner to prevent unnecessary deteriorations; and to increase team working between disciplines.

Quantitative data analysis suggests a greatly increased demand for our service following the COVID-19 pandemic.

Our thematic analysis identifies concern of deterioration secondary to prolonged waiting times. It also highlights that communication could be improved.

As a result of this mixed-methods approach, the following change ideas were generated and are now being tested:

1. 1. Improve communication with patients on waiting lists by testing an accessible customisable letter.

2. 2. Organise more joint assessments and reviews of service users with multiple disciplines.

3. 3. Short-term allocation of more urgent casework via a new integrated health and social care duty system.

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.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding of Earth's sensitivity to carbon dioxide, finds that permafrost thaw could release more carbon emissions than expected and that the uptake of carbon in tropical ecosystems is weakening. Adverse impacts on human society include increasing water shortages and impacts on mental health. Options for solutions emerge from rethinking economic models, rights-based litigation, strengthened governance systems and a new social contract. The disruption caused by COVID-19 could be seized as an opportunity for positive change, directing economic stimulus towards sustainable investments.

A synthesis is made of ten fields within climate science where there have been significant advances since mid-2019, through an expert elicitation process with broad disciplinary scope. Findings include: (1) a better understanding of equilibrium climate sensitivity; (2) abrupt thaw as an accelerator of carbon release from permafrost; (3) changes to global and regional land carbon sinks; (4) impacts of climate change on water crises, including equity perspectives; (5) adverse effects on mental health from climate change; (6) immediate effects on climate of the COVID-19 pandemic and requirements for recovery packages to deliver on the Paris Agreement; (7) suggested long-term changes to governance and a social contract to address climate change, learning from the current pandemic, (8) updated positive cost–benefit ratio and new perspectives on the potential for green growth in the short- and long-term perspective; (9) urban electrification as a strategy to move towards low-carbon energy systems and (10) rights-based litigation as an increasingly important method to address climate change, with recent clarifications on the legal standing and representation of future generations.

Stronger permafrost thaw, COVID-19 effects and growing mental health impacts among highlights of latest climate science.

Traditional dietary assessment methods in research can be challenging, with participant burden to complete an interview, diary, 24 h recall or questionnaire and researcher burden to code the food record to obtain a nutrient breakdown. Self-reported assessment methods are subject to recall and social desirability biases, in addition to selection bias from the nature of volunteering to take part in a research study. Supermarket loyalty card transaction records, linked to back of pack nutrient information, present a novel opportunity to use objective records of food purchases to assess diet at a household level. With a large sample size and multiple transactions, it is possible to review variation in food purchases over time and across different geographical areas.

This study uses supermarket loyalty card transactions for one retailer's customers in Leeds, for 12 months during 2016. Fruit and vegetable purchases for customers who appear to shop regularly for a ‘complete’ shop, buying from at least 7 of 11 Living Cost and Food Survey categories, were calculated. Using total weight of fruits and vegetables purchased over one year, average portions (80g) per day, per household were generated. Descriptive statistics of fruit and vegetable purchases by age, gender and Index of Multiple Deprivation of the loyalty card holder were generated. Using Geographical Information Systems, maps of neighbourhood purchases per month of the year were created to visualise variations.

The loyalty card holder transaction records represent 6.4% of the total Leeds population. On average, households in Leeds purchase 3.5 portions of fruit and vegetables per day, per household. Affluent and rural areas purchase more fruit and vegetables than average with 22% purchasing more than 5 portions/day. Conversely poor urban areas purchase less, with 18% purchasing less than 1 portion/day. Highest purchases are in the winter months, with lowest in the summer holidays. Loyalty cards registered to females purchased 0.4 portions per day more than male counterparts. The over 65 years purchased 1.5 portions per day more than the 17–24 year olds. A clear deprivation gradient is observed, with the most deprived purchasing 1.5 portions less per day than the least deprived.

Loyalty card transaction data offer an exciting opportunity for measuring variation in fruit and vegetable purchases. Variation is observed by age, gender, deprivation, geographically across a city and throughout the seasons. These insights can inform both policymakers and retailers regarding areas for fruit and vegetable promotion.

Supermarket transaction data, generated from loyalty cards, offers a novel source of food purchase information. Data are available for large sample sizes, over sustained periods of time, allowing for habitual purchasing patterns to be generated. In the UK, recommended dietary patterns to achieve a healthy diet are pictorially illustrated using the Eatwell Guide. Foods include: Fruit and vegetables; starchy products including potatoes, bread, pasta, rice; dairy or dairy alternatives; proteins such as beans, pulses, fish, eggs and meat; oils and spreads; and advice to limit foods high in salt, fat and sugar. Through mapping of foods purchased to the categories of the Eatwell Guide it is possible to review population performance against these national recommendations.

All loyalty card transaction records for purchases made in a UK supermarket chain, by residents of Yorkshire and the Humber during 2016 were included in this research. Customers who purchased foods from 7 or 11 Living Cost and Food Survey (LCFS) categories on ten or more occasions throughout the year were included in the sample, as these customers were considered to be purchasing the majority of their foods from the supermarket. All foods purchased were mapped to the Eatwell Guide food groups via the LCFS categories.

Households purchased: 25% of their total spend on fruits and vegetables, compared with 39% recommended; 13% on starchy products compared to 37% recommended; 23% of protein rich foods compared with 12% recommended; 12% dairy and alternatives compared to 8%; oils and spreads 2% compared to 1% recommended; and 25% foods that should be limited compared to 3% (recommended, but not pictorially illustrated on the plate).

Supermarket transaction data is a novel source of food purchase information which can be used to illustrate dietary behaviours in the UK population. However, it represents foods purchased, not consumed and is at a household level, not individual. Food purchases outside the home are not included. That said, it is arguably an objective measure for dietary assessment. From this study, it is clear to see that food purchases do not match the recommendations. Purchases of high sugar, high fat and high salt snacks constitute a significant proportion of spending, when they should in fact be limited. Protein rich products are also over-represented. Fruit and vegetables and starchy products are under-represented. This insight can benefit both retailers and policy makers for understanding the food purchase behaviours of our society.

Major depressive disorder and neuroticism (Neu) share a large genetic basis. We sought to determine whether this shared basis could be decomposed to identify genetic factors that are specific to depression.

We analysed summary statistics from genome-wide association studies (GWAS) of depression (from the Psychiatric Genomics Consortium, 23andMe and UK Biobank) and compared them with GWAS of Neu (from UK Biobank). First, we used a pairwise GWAS analysis to classify variants as associated with only depression, with only Neu or with both. Second, we estimated partial genetic correlations to test whether the depression's genetic link with other phenotypes was explained by shared overlap with Neu.

We found evidence that most genomic regions (25/37) associated with depression are likely to be shared with Neu. The overlapping common genetic variance of depression and Neu was genetically correlated primarily with psychiatric disorders. We found that the genetic contributions to depression, that were not shared with Neu, were positively correlated with metabolic phenotypes and cardiovascular disease, and negatively correlated with the personality trait conscientiousness. After removing shared genetic overlap with Neu, depression still had a specific association with schizophrenia, bipolar disorder, coronary artery disease and age of first birth. Independent of depression, Neu had specific genetic correlates in ulcerative colitis, pubertal growth, anorexia and education.

Our findings demonstrate that, while genetic risk factors for depression are largely shared with Neu, there are also non-Neu-related features of depression that may be useful for further patient or phenotypic stratification.