An average of 1300 adults develop First Episode Psychosis (FEP) in Ireland each year. Early Intervention in Psychosis (EIP) is now widely accepted as best practice in the treatment of conditions such as schizophrenia. A local EIP programme was established in the Dublin South Central Mental Health Service in 2012.

This is a cross-sectional study of service users presenting to the Dublin South Central Mental Health Service with FEP from 2016 to 2022 following the introduction of the EIP programme. We compared this to a previously published retrospective study of treatment as usual from 2002 to 2012.

Most service users in this study were male, single, unemployed and living with their partner or spouse across both time periods. Cognitive Behavioural Therapy for psychosis was provided to 12% (n = 8) of service users pre-EIP as compared to 52% (n = 30) post-programme introduction (p < 0.001), and 3% (n = 2) of service users engaged with behavioural family therapy pre-EIP as opposed to 15% (n = 9) after (p < 0.01). Rates of composite baseline physical healthcare monitoring improved significantly (p < 0.001).

Exclusive allocation of multidisciplinary team staff to EIP leads to improved compliance with recommended guidelines, particularly CBT-p, formal family therapy and physical health monitoring.

To determine how engagement of the hospital and/or vendor with performance improvement strategies combined with an automated hand hygiene monitoring system (AHHMS) influence hand hygiene (HH) performance rates.

Prospective, before-and-after, controlled observational study.

The study was conducted in 58 adult and pediatric inpatient units located in 10 hospitals.

HH performance rates were estimated using an AHHMS. Rates were expressed as the number of soap and alcohol-based hand rub portions dispensed divided by the number of room entries and exits. Each hospital self-assigned to one of the following intervention groups: AHHMS alone (control group), AHHMS plus clinician-based vendor support (vendor-only group), AHHMS plus hospital-led unit-based initiatives (hospital-only group), or AHHMS plus clinician-based vendor support and hospital-led unit-based initiatives (vendor-plus-hospital group). Each hospital unit produced 1–2 months of baseline HH performance data immediately after AHHMS installation before implementing initiatives.

Hospital units in the vendor-plus-hospital group had a statistically significant increase of at least 46% in HH performance compared with units in the other 3 groups (P ≤ .006). Units in the hospital only group achieved a 1.3% increase in HH performance compared with units that had AHHMS alone (P = .950). Units with AHHMS plus other initiatives each had a larger change in HH performance rates over their baseline than those in the AHHMS-alone group (P < 0.001).

AHHMS combined with clinician-based vendor support and hospital-led unit-based initiatives resulted in the greatest improvements in HH performance. These results illustrate the value of a collaborative partnership between the hospital and the AHHMS vendor.

Relapse rates for individuals with anorexia nervosa after intensive hospital treatment (in-patient or full-time day care) are high. Better knowledge about the difficulties and opportunities that arise during this transition is needed to identify factors that support or hinder continued recovery upon discharge.

The aim of this study was to explore the experiences of adult patients and their chosen carers on the process of transitioning from intensive eating disorder treatment settings to the community.

Semi-structured interviews were conducted with patients with anorexia nervosa (n = 11) discharged from day or in-patient care from specialised eating disorder units across the UK, and their chosen carers (n = 20). Data were analysed with inductive thematic analysis.

Four interrelated themes were identified for both groups. For patients, themes were continuity of care, ambivalence about continued recovery, the value of social support and a call for enhanced transition support. For carers, themes were the impact of the eating disorder on themselves and the family, perceptions of recovery and support post-discharge, the impact of previous treatment and care experiences, and desire to create a supportive transition process.

The study provides an insight into the unique challenges that individuals with anorexia nervosa face upon leaving intensive treatment. A lack of post-discharge planning, support system and identity formation outside of anorexia nervosa were perceived as barriers to continued recovery. Patients and carers advocated for transition support that incorporates a phased, inclusive approach with accessible professional and social support in the community.

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.

Although insomnia disorder and social anxiety disorder are among the most prevalent psychiatric disorders, no studies have yet evaluated the use of sequential evidence-based treatment protocols in the population with co-morbid social anxiety disorder and insomnia disorder.

This study aimed to investigate the effects of sequential treatments on co-morbid insomnia disorder and social anxiety disorder. As depression is a common co-morbid syndrome for both insomnia and social anxiety, a secondary aim was to examine depressive symptoms.

A single-case repeated crossover AB design was used. Ten participants between 18 and 59 years of age with co-morbid DSM-5 diagnoses of insomnia disorder and social anxiety disorder received sequential treatments with cognitive behavioural therapy (CBT). Seven participants completed the treatment course. The primary outcomes were symptoms of insomnia and social anxiety, and the secondary outcome was symptoms of depression.

The effects of CBT on people with co-morbid social anxiety disorder and insomnia disorder were mixed. The majority of participants improved their sleep quality and lessened symptoms of social anxiety and depression. However, participants differed in their degree of improvement concerning all three disorders.

Sequential CBT treatments are potentially effective at decreasing symptoms of social anxiety and insomnia for people with co-morbid social anxiety disorder and insomnia disorder. The variation in outcome across participants makes firm conclusions about the treatment efficacy difficult to draw.

There is global interest in the reconfiguration of community mental health services, including primary care, to improve clinical and cost effectiveness.

This study seeks to describe patterns of service use, continuity of care, health risks, physical healthcare monitoring and the balance between primary and secondary mental healthcare for people with severe mental illness in receipt of secondary mental healthcare in the UK.

We conducted an epidemiological medical records review in three UK sites. We identified 297 cases randomly selected from the three participating mental health services. Data were manually extracted from electronic patient medical records from both secondary and primary care, for a 2-year period (2012–2014). Continuous data were summarised by mean and s.d. or median and interquartile range (IQR). Categorical data were summarised as percentages.

The majority of care was from secondary care practitioners: of the 18 210 direct contacts recorded, 76% were from secondary care (median, 36.5; IQR, 14–68) and 24% were from primary care (median, 10; IQR, 5–20). There was evidence of poor longitudinal continuity: in primary care, 31% of people had poor longitudinal continuity (Modified Modified Continuity Index ≤0.5), and 43% had a single named care coordinator in secondary care services over the 2 years.

The study indicates scope for improvement in supporting mental health service delivery in primary care. Greater knowledge of how care is organised presents an opportunity to ensure some rebalancing of the care that all people with severe mental illness receive, when they need it. A future publication will examine differences between the three sites that participated in this study.

Relapse prevention strategies based on monitoring of early warning signs (EWS) are advocated for the management of psychosis. However, there has been a lack of research exploring how staff, carers and patients make sense of the utility of EWS, or how these are implemented in context.

To develop a multiperspective theory of how EWS are understood and used, which is grounded in the experiences of mental health staff, carers and patients.

Twenty-five focus groups were held across Glasgow and Melbourne (EMPOWER Trial, ISRCTN: 99559262). Participants comprised 88 mental health staff, 21 patients and 40 carers from UK and Australia (total n = 149). Data were analysed using constructivist grounded theory.

All participants appeared to recognise EWS and acknowledged the importance of responding to EWS to support relapse prevention. However, recognition of and acting on EWS were constructed in a context of uncertainty, which appeared linked to risk appraisals that were dependent on distinct stakeholder roles and experiences. Within current relapse management, a process of weighted decision-making (where one factor was seen as more important than others) described how stakeholders weighed up the risks and consequences of relapse alongside the risks and consequences of intervention and help-seeking.

Mental health staff, carers and patients speak about using EWS within a weighted decision-making process, which is acted out in the context of relationships that exist in current relapse management, rather than an objective response to specific signs and symptoms.

Sleep disturbances are prevalent in cancer patients, especially those with advanced disease. There are few published intervention studies that address sleep issues in advanced cancer patients during the course of treatment. This study assesses the impact of a multidisciplinary quality of life (QOL) intervention on subjective sleep difficulties in patients with advanced cancer.

This randomized trial investigated the comparative effects of a multidisciplinary QOL intervention (n = 54) vs. standard care (n = 63) on sleep quality in patients with advanced cancer receiving radiation therapy as a secondary endpoint. The intervention group attended six intervention sessions, while the standard care group received informational material only. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS), administered at baseline and weeks 4 (post-intervention), 27, and 52.

The intervention group had a statistically significant improvement in the PSQI total score and two components of sleep quality and daytime dysfunction than the control group at week 4. At week 27, although both groups showed improvements in sleep measures from baseline, there were no statistically significant differences between groups in any of the PSQI total and component scores, or ESS. At week 52, the intervention group used less sleep medication than control patients compared to baseline (p = 0.04) and had a lower ESS score (7.6 vs. 9.3, p = 0.03).

A multidisciplinary intervention to improve QOL can also improve sleep quality of advanced cancer patients undergoing radiation therapy. Those patients who completed the intervention also reported the use of less sleep medication.

• • Understand the different payment models currently being used and proposed in mental health services in England

• • Understand the role of clustering in measuring mental health activity and providing a basis for funding

• • Understand how a robust model of clustering can benefit the provision of mental health services

None.