Trust in biomedical research is essential, multidimensional, and shaped by individual experiences, culture, and communication. Participants’ trust relies on researchers’ commitment to ethical practices. As public trust in science declines due to misinformation and disinformation campaigns, biomedical researchers (BmRs) must ensure trust and cultivate trustworthiness. This study explores BmR’s perspectives on trust and trustworthiness.

We employed a qualitative, phenomenological approach to explore the experiences of BmRs. Through purposive sampling via the Indiana Clinical and Translational Sciences Institute, we invited BmRs to participate in semi-structured interviews. We employed rapid qualitative analysis (RQA) to identify key themes from interviews with BmRs. This action-oriented approach enables a research team to efficiently summarize experiences and perspectives, using structured templates and matrixes for systematic analysis and interpretation.

Fourteen BmRs were interviewed. Volunteer demographics were collected for race/ethnicity, gender, faculty rank, and investigator experience level. The following domains were identified: individual trust and trustworthiness, institutional trustworthiness, and trust and equity as a crucial part of structural and social drivers of health.

We recognize that BmRs are dedicated to health equity and addressing disparities. However, in addition to committing to “best practices,” BmRs should prioritize actions that foster genuine trust from the communities they serve. More development opportunities are needed for reflection of what it means to be trusted by research volunteers and communities. Furthermore, intentions alone aren’t sufficient; earned trust and trustworthiness are vital.

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.

In the United Kingdom, 14.6 million people reported having a disability in the year 2020–2021. Cognition may be one factor that contributes to disability, as previous studies have shown that cognitive abilities predict later health outcomes and prevalence of disability increases with decreasing cognitive function. Furthermore, studies have demonstrated a link between cognition and common psychiatric disorders, such as depression and anxiety. To our knowledge, no studies have examined the role of current mental health in the association between cognition and disability in a general population sample. The aim of this study was to examine the relationship between cognition, mental health and measures of disability/daily functioning in an online population sample. Our hypotheses were: 1) that lower cognitive performance would be associated with increased reported disability, and 2) that this association would be partly explained by current depression and anxiety symptoms.

The sample consisted of 3679 participants recruited from HealthWise Wales. Participants completed the Cardiff ONline Cognitive Assessment, a web-based battery of five tasks assessing processing speed, working memory, vocabulary, reasoning, and emotion identification. Disability was assessed using the World Health Organisation Disability Assessment Schedule (WHODAS). Real world measures of functioning were also included (currently employed, living with a partner, children and ever married). Current depression and anxiety symptoms were assessed using the Hospital Anxiety and Depression Scale (HADS). Linear and logistic regressions were conducted to assess the associations between cognitive performance and measures of disability/functioning. Structural equation modelling was performed to assess whether these associations could be partially explained by HADS scores, as well as measures of education and health/lifestyle factors.

Higher cognitive performance was associated with lower overall WHODAS scores (B=−0.1, SE = 0.01, P = 1 × 10–13), living with a partner (OR = 1.13, 95% CIs = 1.06–1.21, P = 4.3 × 10–4) and being in employment or education (OR = 1.22, 95% CIs = 1.13–1.33, P = 2.1 × 10-6). HADS scores partially explained the relationship between cognition and: 1) WHODAS (80%), 2) employment (63%) and 3) living with a partner (37%). In addition, smoking status explained 3% of the relationship between cognition and WHODAS.

Current symptoms of depression and anxiety partially explained the relationship between cognition and three measures of disability/functioning. Alleviating these symptoms may improve patients’ daily difficulties. Future research should establish the direction of causality of these associations.

Women with bipolar disorder have a high recurrence rate in the perinatal period. However, the use of prophylactic medication can be a concern during pregnancy and breastfeeding. There are few studies looking at the impact of prophylactic medication on the risk of recurrence.The aims of this study are to describe the use of medication in women with bipolar disorder in the perinatal period and the impact of that prophylactic medication on the rate of postnatal recurrence.

The BDRN (Bipolar Disorder Research Network Study) is the largest individual network of individuals with bipolar disorder and related mood disorders in the world. The BDRN pregnancy study is a prospective observational study which took place in the UK. We collected sociodemographic, clinical and medication data from pregnant women with a diagnosis of bipolar disorder and who were euthymic entering the postpartum period. The clinical data were collected via interviews during pregnancy and the postpartum and access to clinical records where those were available.

Data were analysed for association using χ2 tests and logistic regression.

Our total sample for this analysis comprised of 103 women who met the criteria.

We found that 71 (70%) were taking medication at delivery: 43 (43%) antipsychotics, 9 (9%) antidepressants, 10 (10%) mood stabilisers, (6 lithium, 4 anticonvulsants and 9 multiple medication classes).

Of the total sample, 44 (43%) experienced a postpartum recurrence: 21 (20%) had an episode of postpartum psychosis, 15 (15%) of non-psychotic depression and 8 (8%) of hypomania. Of the postpartum psychotic episodes 11 were of mania with psychosis, 8 of mania without psychosis and 2 of psychotic depression.

There was no significant association between taking medication at delivery and postpartum recurrence χ2 (1)=0.116, p=0.73.

In a multivariable analysis there continued to be no association when adjusted for age, ethnicity, parity, severity (previous admissions, age at impairment, bipolar subtype) and previous psychotic symptoms aOR 1.35 95%CI [0.45; 4.00], p=0.59.

A high number of bipolar women are taking medication at delivery and in the majority, antipsychotics are prescribed. The postnatal recurrence rate in both medicated and unmedicated women is high.

Our findings align with recent electronic health records and observational studies, but differ from older clinical cohort and higher Lithium-prescribing sample studies. Limitations include the study design and confounding by indication. Further research in larger populations is necessary to inform clinical decision-making for women and their healthcare providers.

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.