Functional impairment in daily activities, such as work and socializing, is part of the diagnostic criteria for major depressive disorder and most anxiety disorders. Despite evidence that symptom severity and functional impairment are partially distinct, functional impairment is often overlooked. To assess whether functional impairment captures diagnostically relevant genetic liability beyond that of symptoms, we aimed to estimate the heritability of, and genetic correlations between, key measures of current depression symptoms, anxiety symptoms, and functional impairment.

In 17,130 individuals with lifetime depression or anxiety from the Genetic Links to Anxiety and Depression (GLAD) Study, we analyzed total scores from the Patient Health Questionnaire-9 (depression symptoms), Generalized Anxiety Disorder-7 (anxiety symptoms), and Work and Social Adjustment Scale (functional impairment). Genome-wide association analyses were performed with REGENIE. Heritability was estimated using GCTA-GREML and genetic correlations with bivariate-GREML.

The phenotypic correlations were moderate across the three measures (Pearson’s r = 0.50–0.69). All three scales were found to be under low but significant genetic influence (single-nucleotide polymorphism-based heritability [h2SNP] = 0.11–0.19) with high genetic correlations between them (rg = 0.79–0.87).

Among individuals with lifetime depression or anxiety from the GLAD Study, the genetic variants that underlie symptom severity largely overlap with those influencing functional impairment. This suggests that self-reported functional impairment, while clinically relevant for diagnosis and treatment outcomes, does not reflect substantial additional genetic liability beyond that captured by symptom-based measures of depression or anxiety.

The primary purpose of this study was to assess perceived burdens and benefits of participating in implementation research among staff employed in resource-constrained healthcare settings. Another objective was to use findings to generate considerations for engaging staff in research across different phases of implementation research.

This qualitative focus group and consensus building study involved researchers affiliated with the National Cancer Institute Implementation Science Centers in Cancer Control program and nine Community Health Centers (CHCs) in Massachusetts. Six focus groups (n = 3 with CHC staff; n = 3 with researchers) assessed barriers and facilitators to staff participation in implementation research. During consensus discussions, we used findings to develop considerations for engaging staff as participants and partners throughout phases of implementation research.

Sixteen researchers and 14 staff participated in separate focus groups; nine researchers and seven staff participated in separate consensus discussions. Themes emerged across participant groups in three domains: (1) influences on research participation; (2) research burdens and benefits; and (3) ways to facilitate staff participation in research. Practical considerations included: (a) aligning research with organizational and staff values and priorities; (b) applying user-centered design to research methods; (c) building organizational and individual research capacity; and (d) offering equitable incentives for staff participation.

Engaging staff as participants and partners across different phases of implementation research requires knowledge about what contributes to research burden and benefits and addressing context-specific burdens and benefits.

Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD).

We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis.

Based on individual genotypes from case–control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case–case–control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses.

Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case–case GWAS and that of case–control BPD.

We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

Most patients with long-term conditions (LTC) receive regular blood tests to monitor disease progression and response to treatment and to detect complications. There is currently no robust evidence to inform recommendations on monitoring. Creating this evidence base is challenging because the benefits and harms of testing are dependent on what is done in response to the test results.

We identified a list of commonly used tests. We defined a series of filtering questions to determine whether there was evidence to support the rationale of monitoring, such as “Can the general practitioner do anything in response to an abnormal test result?” Through a series of rapid reviews we identified evidence to answer each question. The evidence was presented at a consensus meeting where clinicians and patients voted for inclusion, exclusion, or further analysis. A process evaluation was performed alongside this. Further analyses were performed using routinely collected healthcare data and by performing incidence analyses, emulating randomized controlled trials (RCTs), and modeling disease progression.

We tested this methodology on three common LTCs: chronic kidney disease (CKD), type 2 diabetes mellitus (T2DM), and hypertension. We found sufficient evidence to include hemoglobin A1C and estimated glomerular filtration rate (eGFR) for monitoring patients with T2DM; hemoglobin and eGFR for patients with CKD; and eGFR for patients with hypertension. The consensus panel excluded four tests, while 10 tests were selected for further analysis. The emulated RCTs will investigate the effect of regular monitoring with certain tests on health outcomes among routinely monitored patients. In addition, we will investigate the signal-to-noise ratio of each test over time using a modeling approach.

The cost effectiveness of the evidence-based testing panels needs to be tested in clinical practice. We are currently developing an intervention package and are planning to run a feasibility trial. This program of work has the potential to change how LTCs are monitored in primary care, ultimately improving patient outcomes and leading to more efficient use of healthcare resources.

Military Servicemembers and Veterans are at elevated risk for suicide, but rarely self-identify to their leaders or clinicians regarding their experience of suicidal thoughts. We developed an algorithm to identify posts containing suicide-related content on a military-specific social media platform.

Publicly-shared social media posts (n = 8449) from a military-specific social media platform were reviewed and labeled by our team for the presence/absence of suicidal thoughts and behaviors and used to train several machine learning models to identify such posts.

The best performing model was a deep learning (RoBERTa) model that incorporated post text and metadata and detected the presence of suicidal posts with relatively high sensitivity (0.85), specificity (0.96), precision (0.64), F1 score (0.73), and an area under the precision-recall curve of 0.84. Compared to non-suicidal posts, suicidal posts were more likely to contain explicit mentions of suicide, descriptions of risk factors (e.g. depression, PTSD) and help-seeking, and first-person singular pronouns.

Our results demonstrate the feasibility and potential promise of using social media posts to identify at-risk Servicemembers and Veterans. Future work will use this approach to deliver targeted interventions to social media users at risk for suicide.

The importance of the humanities has been highlighted in developing a holistic person-centred model of psychiatry. The use of film to explore topics related to psychiatry, known as ‘cinemeducation’, has been shown to encourage reflection. Wellbeing has been identified as a key area in the quality of psychiatry training, however there is currently no evidence exploring the wellbeing and educational benefits of ‘cinemeducation’ within psychaitry training programmes

Our primary aim was to measure the impact of ‘cinemeducation’ events on attendees’ wellbeing and professional development, with a secondary aim to explore attendees experience of ‘cinemeduation’.

The hypothesis is that attendees will experience a wellbeing and educational benefit from the initiative.

6 events were assessed between January and August 2023. Each event involved the showing of a feature length film, followed by a 30-minute discussion. 4 out of 6 events were facilitated by guest speakers, usually a consultant psychiatrist. Following events, questionnaires were distributed which included a series of statements with Likert scales and open ended questions. Mean Likert scale scores were calculated with qualitative data interpreted by the authors using thematic analysis.

A total of 108 trainees attended events, predominantly core trainees (64.52%). All events scored consistently high for self-reported wellbeing, however facilitated events demonstrated higher scores for self-reported reflective and educational benefits. The themes derived from qualitative data were of ‘cinemeducation’ being a novel educational opportunity where attendees were able to use film to work through challenges associated with psychiatry, as well as being an opportunity for connecting with other trainees, where attendees could share experiences and foster a sense of community.

Core psychiatry trainees in particular, appear to value ‘cinemeducation’ as a tool to connect with their peers and develop their understanding of psychiatry in a relaxed, but stimulating environment, which is best achieved under the guidance of a senior colleague. The study suggests that the introduction of ‘cinemeducation’ across psychiatry training programmes would benefit trainees’ wellbeing and development. Further research is required to assess the impact of such initiatives across a broader cohort of trainees, using more robust methods of data collection, as well as formal measures of skills such as reflective functioning.

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.

Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood.

Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research.

As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant.

We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation.

DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.

There is evidence that the COVID-19 pandemic has negatively affected mental health, but most studies have been conducted in the general population.

To identify factors associated with mental health during the COVID-19 pandemic in individuals with pre-existing mental illness.

Participants (N = 2869, 78% women, ages 18–94 years) from a UK cohort (the National Centre for Mental Health) with a history of mental illness completed a cross-sectional online survey in June to August 2020. Mental health assessments were the GAD-7 (anxiety), PHQ-9 (depression) and WHO-5 (well-being) questionnaires, and a self-report question on whether their mental health had changed during the pandemic. Regressions examined associations between mental health outcomes and hypothesised risk factors. Secondary analyses examined associations between specific mental health diagnoses and mental health.

A total of 60% of participants reported that mental health had worsened during the pandemic. Younger age, difficulty accessing mental health services, low income, income affected by COVID-19, worry about COVID-19, reduced sleep and increased alcohol/drug use were associated with increased depression and anxiety symptoms and reduced well-being. Feeling socially supported by friends/family/services was associated with better mental health and well-being. Participants with a history of anxiety, depression, post-traumatic stress disorder or eating disorder were more likely to report that mental health had worsened during the pandemic than individuals without a history of these diagnoses.

We identified factors associated with worse mental health during the COVID-19 pandemic in individuals with pre-existing mental illness, in addition to specific groups potentially at elevated risk of poor mental health during the pandemic.