Effects of Changing Work Environments on Employer Support for Physical Activity During COVID-19

COVID-19 dramatically accelerated evolving changes in the way we define the “work environment” in the United States. In response to COVID-19, many employers have offered increased flexibility for where employees work, including remote (an employee’s workstation is at home) and hybrid work (an employee works both at the employer worksite and remotely, on predetermined schedules). Accordingly, worksite physical activity (PA) and sedentary behaviors (SB) such as extended sitting time (ST) may have changed.1,2 However, little is known about whether these work arrangements are associated with changes in employer support for PA. Interviews were conducted to assess this gap in understanding. Because little is known about employer support for equity with respect to PA and SB, this study sought to identify potential strategies to assure equity in PA opportunities across work environments

Masters in Serious Games Curriculum Framework

Thin, A. G., Lim, T., Louchart, S., De Gloria, A., Mayer, I., Kickmeier-Rust, M., Klamma, R., VeltKamp, R., Arnab, S., Bellotti, F., Boyle, L., Prada, R., Westera, W., Nadolski, R., & Abbas Petersen, S. (2013). Masters in Serious Games Curriculum Framework. Deliverable 5.3 of the Games and Learning Alliance Network of Excellence. Available at http://www.seriousgamessociety.org/download/SGMastersFwk.pdf.This report outlines a European Masters of Science programme on serious gaming.This report is a deliverable of the GALA project, which is sponsored by the the FP7 Programme of the European Commissio

Subsoil contraints and their management: Overview from five years of R&D

Subsoil constraints cost the grains industry more than $1.6b in lost production each year. Diagnosing and mapping subsoil constraints (SSC) was achieved at a shire scale using the DPIRD soils database and historic surveys

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

HeAlth System StrEngThening in four sub-Saharan African countries (ASSET) to achieve high-quality, evidence-informed surgical, maternal and newborn, and primary care: protocol for pre-implementation phase studies

To achieve universal health coverage, health system strengthening (HSS) is required to support the of delivery of high-quality care. The aim of the National Institute for Health Research Global Research Unit on HeAlth System StrEngThening in Sub-Saharan Africa (ASSET) is to address this need in a four-year programme, with three healthcare platforms involving eight work-packages. Key to effective health system strengthening (HSS) is the pre-implementation phase of research where efforts focus on applying participatory methods to embed the research programme within the existing health system. To conceptualise the approach, we provide an overview of the key methods applied across work-package to address this important phase of research conducted between 2017 and 2021. Work-packages are being undertaken in publicly funded health systems in rural and urban areas in Ethiopia, Sierra Leone, South Africa, and Zimbabwe. Stakeholders including patients and their caregivers, community representatives, clinicians, managers, administrators, and policymakers are the main research participants. In each work-package, initial activities engage stakeholders and build relationships to ensure co-production and ownership of HSSIs. A mixed-methods approach is then applied to understand and address determinants of high-quality care delivery. Methods such as situation analysis, cross-sectional surveys, interviews and focus group discussions are adopted to each work-package aim and context. At the end of the pre-implementation phase, findings are disseminated using focus group discussions and participatory Theory of Change workshops where stakeholders from each work package use findings to select HSSIs and develop a programme theory. ASSET places a strong emphasis of the pre-implementation phase in order to provide an in-depth and systematic diagnosis of the existing heath system functioning, needs for strengthening and stakeholder engagement. This common approach will inform the design and evaluation of the HSSIs to increase effectiveness across work packages and contexts, to better understand what works, for whom, and how

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.Peer reviewe

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder