Distance Education: Methods of Education for Students in Remote Areas of China

This paper illustrates that distance education is a useful mechanism of education for students living in remote areas or those who desire a native English-speaking teacher to improve their own language skills. However, it will also show the ways in which distance education is not the perfect solution. This paper will overall find that distance education improves future economic opportunities, causes changes in teacher/student power dynamics, and does, to some extent, increase access to schooling for children living in rural, remote areas

A population-based study of race-specific risk for placental abruption

<p>Abstract</p> <p>Background</p> <p>Efforts to elucidate risk factors for placental abruption are imperative due to the severity of complications it produces for both mother and fetus, and its contribution to preterm birth. Ethnicity-based differences in risk of placental abruption and preterm birth have been reported. We tested the hypotheses that race, after adjusting for other factors, is associated with the risk of placental abruption at specific gestational ages, and that there is a greater contribution of placental abruption to the increased risk of preterm birth in Black mothers, compared to White mothers.</p> <p>Methods</p> <p>We conducted a population-based cohort study using the Missouri Department of Health's maternally-linked database of all births in Missouri (1989–1997) to assess racial effects on placental abruption and the contribution of placental abruption to preterm birth, at different gestational age categories (n = 664,303).</p> <p>Results</p> <p>Among 108,806 births to Black mothers and 555,497 births to White mothers, 1.02% (95% CI 0.96–1.08) of Black births were complicated by placental abruption, compared to 0.71% (95% CI 0.69–0.73) of White births (aOR 1.32, 95% CI 1.22–1.43). The magnitude of risk of placental abruption for Black mothers, compared to White mothers, increased with younger gestational age categories. The risk of placental abruption resulting in term and extreme preterm births (< 28 weeks) was higher for Black mothers (aOR 1.15, 95% CI 1.02–1.29 and aOR 1.98, 95% CI 1.58–2.48, respectively). Compared to White women delivering in the same gestational age category, there were a significantly higher proportion of placental abruption in Black mothers who delivered at term, and a significantly lower proportion of placental abruption in Black mothers who delivered in all preterm categories (p < 0.05).</p> <p>Conclusion</p> <p>Black women have an increased risk of placental abruption compared to White women, even when controlling for known coexisting risk factors. This risk increase is greatest at the earliest preterm gestational ages when outcomes are the poorest. The relative contribution of placental abruption to term births was greater in Black women, whereas the relative contribution of placental abruption to preterm birth was greater in White women.</p

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

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

Educating the next generation of cancer researchers: Evaluation of a cancer research partnership training program.

African American, American Indian and Alaska Native, Hispanic (or Latinx), Native Hawaiian, and other Pacific Islander groups are underrepresented in the biomedical workforce, which is one of the barriers to addressing cancer disparities among minority populations. The creation of a more inclusive biomedical workforce dedicated to reducing the burden of cancer health disparities requires structured, mentored research and cancer-related research exposure during the earlier stages of training. The Summer Cancer Research Institute (SCRI) is a multicomponent 8-week intensive summer program funded under the Partnership between a Minority Serving Institute and a National Institutes of Health-designated Comprehensive Cancer Center. In this survey study, we found that students who participated in the SCRI Program reported greater knowledge and interest in pursuing careers in cancer-related fields than their counterparts who did not participate in SCRI. Successes, challenges, and solutions in providing training in cancer and cancer health disparities research to improve diversity in the biomedical fields were also discussed

An evidence-based approach to establish the functional and clinical significance of copy number variants in intellectual and developmental disabilities

Purpose: Copy number variants have emerged as a major cause of human disease such as autism and intellectual disabilities. Because copy number variants are common in normal individuals, determining the functional and clinical significance of rare copy number variants in patients remains challenging. The adoption of whole-genome chromosomal microarray analysis as a first-tier diagnostic test for individuals with unexplained developmental disabilities provides a unique opportunity to obtain large copy number variant datasets generated through routine patient care.Methods: A consortium of diagnostic laboratories was established (the International Standards for Cytogenomic Arrays consortium) to share copy number variant and phenotypic data in a central, public database. We present the largest copy number variant case-control study to date comprising 15,749 International Standards for Cytogenomic Arrays cases and 10,118 published controls, focusing our initial analysis on recurrent deletions and duplications involving 14 copy number variant regions.Results: Compared with controls, 14 deletions and seven duplications were significantly overrepresented in cases, providing a clinical diagnosis as pathogenic.Conclusion: Given the rapid expansion of clinical chromosomal microarray analysis testing, very large datasets will be available to determine the functional significance of increasingly rare copy number variants. This data will provide an evidence-based guide to clinicians across many disciplines involved in the diagnosis, management, and care of these patients and their families.<br/

Test Performance Characteristics of the AIR, GAD-7 and HADS-Anxiety Screening Questionnaires for Anxiety in Chronic Obstructive Pulmonary Disease

Rationale: Anxiety is a common comorbidity of chronic obstructive pulmonary disease (COPD) that is associated with higher morbidity and mortality. We evaluated three anxiety screening questionnaires: the Generalized Anxiety Disorder 7-Item Scale (GAD-7), the Hospital Anxiety and Depression Scale Anxiety subscale (HADS-A), and the Anxiety Inventory for Respiratory Disease (AIR).Objectives: To evaluate and compare the test performance characteristics of three anxiety screening questionnaires, using the Mini-International Neuropsychiatric Interview (MINI), version 7.0, as the "gold standard."Methods: Individuals with COPD were recruited at 16 centers. The MINI and questionnaires were administered by trained research coordinators at an in-person visit and readministered by telephone 2-4 weeks later. A composite score for the presence of any Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-V) anxiety disorder was computed, based on the MINI as the gold standard, compared with a participant screening positive on self-report measures for these analyses.Results: Two hundred and twenty eligible individuals with COPD were enrolled; 219 completed the study. Eleven percent were identified as having a DSM-V anxiety disorder, based on the MINI. Elevated anxiety symptoms based on questionnaires were 38% for the AIR, 30% for the GAD-7, and 20% for the HADS-A. Area under the receiver operating characteristic curve (AUC) was highest for the GAD-7 (0.78; 95% confidence interval [CI], 0.69-0.87), followed by the HADS-A (0.74; 95% CI, 0.64-0.84) and the AIR (0.66; 95% CI, 0.56-0.76). The AUC for the GAD-7 was significantly greater than for the AIR (P = 0.014). Sensitivity was not statistically different among the questionnaires: 77% for the GAD-7, 63% for the HADS-A, and 66% for the AIR. The HADS-A had the highest specificity, 85%, which was significantly higher than that of the GAD-7 (77%; P &lt; 0.001) and the AIR (65%; P &lt; 0.001); GAD-7 specificity was higher than AIR specificity (P &lt; 0.001).Conclusions: Symptoms of anxiety among patients with COPD as identified by screening questionnaires were common and significantly higher than the prevalence of anxiety disorder meeting DSM-V criteria. The GAD-7, the HADS-A and the AIR questionnaires had fair to moderate psychometric properties as screening tools for anxiety in individuals with COPD, indicating the need for improved measures for this patient population