Individuals with cocaine use disorder or gambling disorder demonstrate impairments in cognitive flexibility: the ability to adapt to changes in the environment. Flexibility is commonly assessed in a laboratory setting using probabilistic reversal learning, which involves reinforcement learning, the process by which feedback from the environment is used to adjust behavior.

It is poorly understood whether impairments in flexibility differ between individuals with cocaine use and gambling disorders, and how this is instantiated by the brain. We applied computational modelling methods to gain a deeper mechanistic explanation of the latent processes underlying cognitive flexibility across two disorders of compulsivity.

We present a re-analysis of probabilistic reversal data from individuals with either gambling disorder (n = 18) or cocaine use disorder (n = 20) and control participants (n = 18), using a hierarchical Bayesian approach. Furthermore, we relate behavioural findings to their underlying neural substrates through an analysis of task-based functional magnetic resonanceimaging (fMRI) data.

We observed lower ‘stimulus stickiness’ in gambling disorder, and report differences in tracking expected values in individuals with gambling disorder compared to controls, with greater activity during reward expected value tracking in the cingulate gyrus and amygdala. In cocaine use disorder, we observed lower responses to positive punishment prediction errors and greater activity following negative punishment prediction errors in the superior frontal gyrus compared to controls.

Using a computational approach, we show that individuals with gambling disorder and cocaine use disorder differed in their perseverative tendencies and in how they tracked value neurally, which has implications for psychiatric classification.

This national pre-pandemic survey compared demand and capacity of adult community eating disorder services (ACEDS) with NHS England (NHSE) commissioning guidance.

Thirteen services in England and Scotland responded (covering 10.7 million population). Between 2016–2017 and 2019–2020 mean referral rates increased by 18.8%, from 378 to 449/million population. Only 3.7% of referrals were from child and adolescent eating disorder services (CEDS-CYP), but 46% of patients were aged 18–25 and 54% were aged >25. Most ACEDS had waiting lists and rationed access. Many could not provide full medical monitoring, adapt treatment for comorbidities, offer assertive outreach or provide seamless transitions. For patient volume, the ACEDS workforce budget was 15%, compared with the NHSE workforce calculator recommendations for CEDS-CYP. Parity required £7 million investment/million population for the ACEDS.

This study highlights the severe pressure in ACEDS, which has increased since the COVID-19 pandemic. Substantial investment is required to ensure NHS ACEDS meet national guidance, offer evidence-based treatment, reduce risk and preventable deaths, and achieve parity with CEDS-CYP.

The World Health Organization (WHO) has developed and supported numerous initiatives to build capacity and awareness about health emergency and disaster risk management (Health EDRM). These include establishing the Health EDRM Research Network (Health EDRM RN) in 2018 and the publication of the Health EDRM Framework in 2019. These initiatives recognize that research is vital to generating the evidence to inform decision making and research that is integral to disaster preparedness, response and recovery will be vital to delivering the aspirations associated with caring, coping and overcoming in an increasingly challenging world.

To strengthen the capacity for conduct and use of research, resources were developed by the WHO Guidance on Research Methods for Health EDRM.

This first WHO textbook on Health EDRM research methods was published in 2021 and updated in 2022 with a chapter on Health EDRM research in the context of COVID-19. The 44 chapters offer practical advice about how to plan, conduct and report on a variety of quantitative and qualitative studies that can inform questions about policies and programs for health-related emergencies and disasters across different settings and level of resources. Case studies of direct relevance to Health EDRM provide real-life examples of research methods and how they have modified policies.

More than 160 authors in 30 countries contributed to the guidance, which is relevant to researchers, would-be researchers, policy makers and practitioners. It should help improve the quality of Health EDRM research; the quality of policy, practice and guidance supported by the evidence generated; and research capacity, collaboration and engagement among researchers, the research community, policy-makers, practitioners and other stakeholders.

The Guidance is being supplemented by additional resources, including audio podcasts, slideshows, video presentations and webinars, and the content as a whole will be discussed in this presentation.

Recent well-powered genome-wide association studies have enhanced prediction of substance use outcomes via polygenic scores (PGSs). Here, we test (1) whether these scores contribute to prediction over-and-above family history, (2) the extent to which PGS prediction reflects inherited genetic variation v. demography (population stratification and assortative mating) and indirect genetic effects of parents (genetic nurture), and (3) whether PGS prediction is mediated by behavioral disinhibition prior to substance use onset.

PGSs for alcohol, cannabis, and nicotine use/use disorder were calculated for Minnesota Twin Family Study participants (N = 2483, 1565 monozygotic/918 dizygotic). Twins' parents were assessed for histories of substance use disorder. Twins were assessed for behavioral disinhibition at age 11 and substance use from ages 14 to 24. PGS prediction of substance use was examined using linear mixed-effects, within-twin pair, and structural equation models.

Nearly all PGS measures were associated with multiple types of substance use independently of family history. However, most within-pair PGS prediction estimates were substantially smaller than the corresponding between-pair estimates, suggesting that prediction is driven in part by demography and indirect genetic effects of parents. Path analyses indicated the effects of both PGSs and family history on substance use were mediated via disinhibition in preadolescence.

PGSs capturing risk of substance use and use disorder can be combined with family history measures to augment prediction of substance use outcomes. Results highlight indirect sources of genetic associations and preadolescent elevations in behavioral disinhibition as two routes through which these scores may relate to substance use.

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.

There is increasing evidence of a strong association between sleep and mental health in both adolescents and adults. CBT for insomnia is being applied to good effect with adults with mental health difficulties but there are few studies examining its applicability to adolescents within mental health services.

We carried out a case series analysis (n = 15) looking at the feasibility, accessibility and impact of a low-intensity sleep intervention for young people (14–25 years) being seen by a secondary care Youth Mental Health team in the UK. The intervention was based on cognitive behavioural therapy for insomnia (CBTi) and acceptance and commitment therapy (ACT) approaches and involved six individual sessions delivered on a weekly basis by a graduate psychologist. Routine outcome measures were used to monitor insomnia, psychological distress and functioning with assessments at baseline, session 3, session 6 and at 4 weeks after end of intervention. All participants scored in the clinical range for insomnia at the start of the study.

High uptake, attendance and measure completion rates were observed. Large effect sizes were observed for insomnia, psychological distress and functioning. Twelve of the fifteen participants (80%) no longer scored above threshold for insomnia at follow-up. All seven under-18s no longer met threshold for clinical ‘caseness’ on the Revised Child Anxiety and Depression Scale (RCADS) at follow-up.

The findings suggest that the intervention was well accepted by young people and feasible to apply within a secondary care setting. Strong effect sizes are encouraging but are probably inflated by the small sample size, uncontrolled design and unblinded assessments.