Suchergebnisse

This report shows the immediate college enrollment rates for 4-year and for 2-year institutions in 2017 across the country. ; U.S Department of Education, National Center for Education Statistics

This study examines the influence of foreign direct investment (FDI), overseas development aid (ODA), and remittances on the enrollment of girls and boys in 103 countries over the years 1970–2011. The results suggest that remittances have a contemporaneous robust significant influence on enrollment, with the positive effect being slightly higher for girls than for boys. FDI and ODA have an influence on the enrollment of girls and boys only after a significant time lag. The results also suggest that the impact of remittances on enrollment is increased through income and a well-developed financial sector; FDI through better institutions and a well-developed financial sector; and ODA through better government policy.

This study examines the influence of foreign direct investment (FDI), overseas development aid (ODA), and remittances on the enrollment of girls and boys in 103 countries over the years 1970–2011. The results suggest that remittances have a contemporaneous robust significant influence on enrollment, with the positive effect being slightly higher for girls than for boys. FDI and ODA have an influence on the enrollment of girls and boys only after a significant time lag. The results also suggest that the impact of remittances on enrollment is increased through income and a well-developed financial sector; FDI through better institutions and a well-developed financial sector; and ODA through better government policy.

Because the ACA gave them choices in how to implement insurance coverage, health reform looks different state to state. This Data Brief examines a number of choices related to the establishment and running of the new health insurance marketplaces, and their potential impact on enrollment rates to date. We use existing data sources as well as a new database developed by researchers at the University of Pennsylvania that documents and codes state-level variation in the political setting, institutional structures, and operational decisions likely to affect outcomes on the marketplaces.

This comparative analysis of gender differences in time use among adolescents uses surveys from five developing countries and is motivated by an interest in gender role socialization and gendered patterns of behavior during adolescence. Exploring differences in work (both noneconomic household work and labor market work) and leisure time among adolescents according to school enrollment status, we examine the implications of school enrollment for adolescent development. Consistent differences in time use patterns exist between students and nonstudents across a range of settings. Students spend many fewer hours than nonstudents in work activities and the type of work they do is primarily domestic. Although females carry a heavier workload and enjoy less leisure time than males during their adolescent years regardless of enrollment status, the distribution of their time and the types of activities they participate in are much more similar to their male peers when they are students.

Twenty-three states and the District of Columbia have passed laws implementing medical marijuana programs. The nineteen programs that were in operation as of October 2014 collectively had over one million participants. All states (including D.C.) with medical marijuana laws require physicians directly or indirectly to authorize the use of marijuana at their discretion, yet little is known about how medical marijuana programs vary regarding adherence to basic principles of medical practice and associated rates of enrollment. To explore this, we analyzed marijuana programs according to seven components of traditional medical care and pharmaceutical regulation. We then examined enrollment rates, while controlling for potentially confounding state characteristics. We found that fourteen of the twenty-four programs were nonmedical and collectively enrolled 99.4 percent of participants nationwide, with enrollment rates twenty times greater than programs deemed to be "medicalized." Policy makers implementing or amending medical marijuana programs should consider the powerful relationship between less regulation and greater enrollment. Researchers should consider variations across programs when assessing programs' population-level effects.

AbstractThe 2008 Farm Bill created the Average Crop Revenue Election (ACRE) program to be a new commodity support program. Using a multinomial logit model to analyze a mail survey administered before the ACRE sign‐up deadline, we identify factors driving farmer intentions regarding ACRE participation. Using a Tobit model to analyze actual county‐level ACRE enrollment rates, we assess the effect of similar factors on actual farmer decisions. Results suggest that primary crops, risk perceptions, risk aversion, and program complexity were important factors affecting participation. Farmer beliefs and attitudes also played key roles, and were changing during the months before the ACRE deadline.

ABSTRACTInconsistent enrollment among hospitals for neonatal clinical trials may lead to study populations that are not representative of the patient population in the neonatal intensive care unit. The High‐Dose Erythropoietin for Asphyxia and Encephalopathy (HEAL) trial was a multisite randomized clinical trial investigating erythropoietin as a neuroprotective treatment for term infants (those born between 37 and 42 complete weeks) with hypoxic ischemic encephalopathy. Substantial variability was noted in enrollment rate by hospital. We developed survey questions across five conceptual domains to understand systems‐level issues that might contribute to variation in enrollment rate by hospital. Our study found that hospitals varied in their responses across these five domains. We propose three potential reasons that we found a lack of identifiable hospital‐level factors that correlated with enrollment rates: sample‐size limitations, methodological concerns, and confounding factors. Future studies with a larger sample size should be considered to evaluate contributors to hospital‐level variability. This will lead to more robust recruitment strategies, improved enrollment, and decreases in the waste of research resources.