How data science can advance mental health research

Accessibility of powerful computers and availability of so-called big data from a variety of sources means that data science approaches are becoming pervasive. However, their application in mental health research is often considered to be at an earlier stage than in other areas despite the complexity of mental health and illness making such a sophisticated approach particularly suitable. In this Perspective, we discuss current and potential applications of data science in mental health research using the UK Clinical Research Collaboration classification: underpinning research; aetiology; detection and diagnosis; treatment development; treatment evaluation; disease management; and health services research. We demonstrate that data science is already being widely applied in mental health research, but there is much more to be done now and in the future. The possibilities for data science in mental health research are substantial

Developing a Professional Studies Curriculum to Support Veterinary Professional Identity Formation

Professional studies teaching in medical and veterinary education is undergoing a period of change. Traditional approaches, aiming to teach students professional values and behaviors, are being enhanced by curricula designed to support students' professional identity formation. This development offers the potential for improving student engagement and graduates' mental well-being. The veterinary professional identity associated with emotional resilience and success in practice incorporates complexity in professional decision making and the importance of context on behaviors and actions. The veterinarian must make decisions that balance the sometimes conflicting needs of patient, clients, veterinarian, and practice; their subsequent actions are influenced by environmental challenges such as financial limitations, or stress and fatigue caused by a heavy workload. This article aims to describe how curricula can be designed to support the development of such an identity in students. We will review relevant literature from medical education and the veterinary profession to describe current best practices for supporting professional identity formation, and then present the application of these principles using the curriculum at the Royal Veterinary College (RVC) as a case study. Design of a “best practice” curriculum includes sequential development of complex thinking rather than notions of a single best solution to a problem. It requires managing a hidden curriculum that tends to reinforce a professional identity conceived solely on clinical diagnosis and treatment. It includes exposure to veterinary professionals with different sets of professional priorities, and those who work in different environments. It also includes the contextualization of taught content through reflection on workplace learning opportunities

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders