The social value of place-based creative wellbeing: A rapid review and evidence synthesis.

Creative well-being is an increasing field of interest to which biomedical and social sciences have made uneven contributions. The instrumental value of culture and its subsequential public investment is grounded in the interplay of social, cultural and economic capital to attain and preserve wellbeing and health and foster social mobility. The current evidence addresses the effectiveness of arts interventions in improving illnesses. Little attention has been paid to the social value of creative wellbeing for the general population. This paper is a rapid review and evidence synthesis that aims to answer the question, 'What is the social value of place-based arts and culture interventions at individual (wellbeing) and community (social inequalities) levels in the UK and Europe?'. After a systematic search of five databases, search engines, and a call for evidence in August 2022, 14 out of 974 sources met the inclusion criteria. Studies were organised into three themes (Community, Events, Museums), and outcomes were analysed considering the indicators and dimensions of wellbeing (Office for National Statistics). The review evidenced that creative wellbeing leads to improvements in wellbeing outcomes and can contribute to alleviating social determinants of health. However, considering their impact on the underlying causes of structural social inequalities requires caution.

Effectiveness of complex behaviour change interventions tested in randomised controlled trials for people with multiple long-term conditions (M-LTCs): systematic review with meta-analysis.

INTRODUCTION: The prevalence of multiple long-term conditions (M-LTCs) increases as adults age and impacts quality of life and health outcomes. To help people manage these conditions, complex behaviour change interventions are used, often based on research conducted in those with single LTCs. However, the needs of those with M-LTCs can differ due to complex health decision-making and engagement with multiple health and care teams. OBJECTIVES: The aim of this review is to identify whether current interventions are effective for people living with M-LTCs, and which outcomes are most appropriate to detect this change. METHODS: Five databases (MEDLINE, Embase, PsycINFO, CINAHL and Web of Science) were systematically searched, between January 1999 and January 2022, to identify randomised controlled trials evaluating effectiveness of behaviour change interventions in people with M-LTCs. Intervention characteristics, intervention effectiveness and outcome measures were meta-analysed and narratively synthesised. RESULTS: 53 eligible articles were included. Emotional well-being and psychological distress (depression and anxiety) outcomes were most amenable to change (emotional well-being: standardised mean difference (SMD) 0.31 (95% CI 0.04 to 0.58); depression psychological distress: SMD -0.45 (95% CI -0.73 to -0.16); anxiety psychological distress: SMD -0.14 (95% CI -0.28 to 0.00)), particularly for interventions with a collaborative care approach. Interventions targeting those with a physical and mental health condition and those with cognitive and/or behavioural activation approach saw larger reductions in psychological distress outcomes. Interventions that lasted for longer than 6 months significantly improved the widest variety of outcomes. CONCLUSION: Complex interventions can be successfully delivered to those with M-LTCs. These are most effective at reducing psychological distress in those with physical and mental LTCs. Further research is needed to identify the effective components of interventions for people with two or more physical LTCs and which outcome is most appropriate for detecting this change.

Centralized Interactive Phenomics Resource: an integrated online phenomics knowledgebase for health data users.

OBJECTIVE: Development of clinical phenotypes from electronic health records (EHRs) can be resource intensive. Several phenotype libraries have been created to facilitate reuse of definitions. However, these platforms vary in target audience and utility. We describe the development of the Centralized Interactive Phenomics Resource (CIPHER) knowledgebase, a comprehensive public-facing phenotype library, which aims to facilitate clinical and health services research. MATERIALS AND METHODS: The platform was designed to collect and catalog EHR-based computable phenotype algorithms from any healthcare system, scale metadata management, facilitate phenotype discovery, and allow for integration of tools and user workflows. Phenomics experts were engaged in the development and testing of the site. RESULTS: The knowledgebase stores phenotype metadata using the CIPHER standard, and definitions are accessible through complex searching. Phenotypes are contributed to the knowledgebase via webform, allowing metadata validation. Data visualization tools linking to the knowledgebase enhance user interaction with content and accelerate phenotype development. DISCUSSION: The CIPHER knowledgebase was developed in the largest healthcare system in the United States and piloted with external partners. The design of the CIPHER website supports a variety of front-end tools and features to facilitate phenotype development and reuse. Health data users are encouraged to contribute their algorithms to the knowledgebase for wider dissemination to the research community, and to use the platform as a springboard for phenotyping. CONCLUSION: CIPHER is a public resource for all health data users available at https://phenomics.va.ornl.gov/ which facilitates phenotype reuse, development, and dissemination of phenotyping knowledge.

Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program.

One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third (n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.