236 research outputs found

    Multiple Dimensions of the Moral Majority Platform: Shifting Interest Group Coalitions

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    The issues raised by the New Political Right and the Moral Majority have overlapped in recent political history. Researchers have assumed that a single additive scale across conservative issues can identify the base of support for the Moral Majority as an organization. We examine general support for the Moral Majority separately from support for six specific issues: teaching creationism, voluntary public school prayer, military defense spending, gun control, pornography and abortion. Data are from a 1982 random sample of adult respondents from Nebraska (N = 1907). Overall, support for the Moral Majority organization is low. Discriminant analysis identifies fundamentalist and evangelical religious affiliation and Biblical literalism as independent predictors of support for the Moral Majority per se. Education increases knowledge of the organization, but does not influence support for it. Respondents with high income levels are more likely to support the Moral Majority organization. These findings contradict theories of both status politics and cultural fundamentalism. Support for the six specific platform items also varies considerably and is affected by religious conservatism and, independently, by other attitudinal and demographic indicators including age, sex, income, rural residence, education and perception of declining economic conditions. These patterns do not entirely fit the predictions of status politics or cultural fundamentalism theories. Rather, they provide evidence that distinct coalitions form on specific issues. Our conclusion is that a simple additive index of support for the Moral Majority masks these differences and oversimplifies complex patterns of coalitions in the religio-political arena

    Evolving cohesion metrics of a research network on rare diseases: a longitudinal study over 14 years

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    [EN] Research collaboration is necessary, rewarding, and beneficial. Cohesion between team members is related to their collective efficiency. To assess collaboration processes and their eventual outcomes, agencies need innovative methods-and social network approaches are emerging as a useful analytical tool. We identified the research output and citation data of a network of 61 research groups formally engaged in publishing rare disease research between 2000 and 2013. We drew the collaboration networks for each year and computed the global and local measures throughout the period. Although global network measures remained steady over the whole period, the local and subgroup metrics revealed a growing cohesion between the teams. Transitivity and density showed little or no variation throughout the period. In contrast the following points indicated an evolution towards greater network cohesion: the emergence of a giant component (which grew from just 30 % to reach 85 % of groups); the decreasing number of communities (following a tripling in the average number of members); the growing number of fully connected subgroups; and increasing average strength. Moreover, assortativity measures reveal that, after an initial period where subject affinity and a common geographical location played some role in favouring the connection between groups, the collaboration was driven in the final stages by other factors and complementarities. The Spanish research network on rare diseases has evolved towards a growing cohesion-as revealed by local and subgroup metrics following social network analysis.The Spanish Ministry of Economics and Competitiveness partially supported this research (Grant Number ECO2014-59381-R).Benito Amat, C.; Perruchas, F. (2016). Evolving cohesion metrics of a research network on rare diseases: a longitudinal study over 14 years. Scientometrics. 108(1):41-56. https://doi.org/10.1007/s11192-016-1952-zS41561081Aymé, S., & Schmidtke, J. (2007). Networking for rare diseases: A necessity for Europe. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz, 50(12), 1477–1483. doi: 10.1007/s00103-007-0381-9 .Barabási, A. L., Jeong, H., Néda, Z., Ravasz, E., Schubert, A., & Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and its Applications, 311(3–4), 590–614. doi: 10.1016/S0378-4371(02)00736-7 .Bettencourt, L. M. A., Kaiser, D. I., & Kaur, J. (2009). Scientific discovery and topological transitions in collaboration networks. Journal of Informetrics, 3(3), 210–221. doi: 10.1016/j.joi.2009.03.001 .Bian, J., Xie, M., Topaloglu, U., Hudson, T., Eswaran, H., & Hogan, W. (2014). Social network analysis of biomedical research collaboration networks in a CTSA institution. Journal of Biomedical Informatics, 52, 130–140. doi: 10.1016/j.jbi.2014.01.015 .Bordons, M., Aparicio, J., González-Albo, B., & Díaz-Faes, A. A. (2015). The relationship between the research performance of scientists and their position in co-authorship networks in three fields. Journal of Informetrics, 9(1), 135–144. doi: 10.1016/j.joi.2014.12.001 .Börner, K., Dall’Asta, L., Ke, W., & Vespignani, A. (2005). Studying the emerging global brain: Analyzing and visualizing the impact of co-authorship teams. Complexity, 10(4), 57–67. doi: 10.1002/cplx.20078 .Casey-Campbell, M., & Martens, M. L. (2009). Sticking it all together: A critical assessment of the group cohesion–performance literature. International Journal of Management Reviews, 11(2), 223–246. doi: 10.1111/j.1468-2370.2008.00239.x .Chiocchio, F., & Essiembre, H. (2009). Cohesion and performance: A meta-analytic review of disparities between project teams, Production teams, and service teams. Small group research, 40(4), 382–420. doi: 10.1177/1046496409335103 .Cho, A. (2011). Particle physicists’ new extreme teams. Science, 333(6049), 1564–1567. doi: 10.1126/science.333.6049.1564 .Cooke, N. J., & Hilton, M. L. (2015). Enhancing the effectiveness of team science. Washington, D.C.: National Academies Press. Recuperado a partir de http://www.nap.edu/catalog/19007/enhancing-the-effectiveness-of-team-science .Cugmas, M., Ferligoj, A., & Kronegger, L. (2015). The stability of co-authorship structures. Scientometrics, 106(1), 163–186. doi: 10.1007/s11192-015-1790-4 .Estrada, E. (2011). The structure of complex networks: Theory and applications. Oxford: University Press.Gallivan, M., & Ahuja, M. (2015). Co-authorship, homophily, and scholarly influence in information systems research. Journal of the Association for Information Systems, 16(12), 980.Ghosh, J., Kshitij, A., & Kadyan, S. (2014). Functional information characteristics of large-scale research collaboration: Network measures and implications. Scientometrics, 102(2), 1207–1239. doi: 10.1007/s11192-014-1475-4 .Heymann, S. (2014). Gephi. In R. Alhajj & J. Rokne (Eds.), Encyclopedia of social network analysis and mining (pp. 612–625). New York: Springer.Himmelstein, D. S., & Powell, K. (2016). Analysis for “the history of publishing delays” blog post v1.0. Zenodo,. doi: 10.5281/zenodo.45516 .Hunt, J. D., Whipple, E. C., & McGowan, J. J. (2012). Use of social network analysis tools to validate a resources infrastructure for interinstitutional translational research: A case study. Journal of the Medical Library Association, 100(1), 48–54. doi: 10.3163/1536-5050.100.1.009 .Kolaczyk, E. D., & Csardi, G. (2014). Statistical analysis of network data with R (Vol. 65). New York: Springer.Kumar, S. (2015). Efficacy of a giant component in co-authorship networks: Evidence from a Southeast Asian dataset in economics. Aslib Journal of Information Management, 68(1), 19–32. doi: 10.1108/AJIM-12-2014-0172 .Larivière, V., Gingras, Y., Sugimoto, C. R., & Tsou, A. (2015). Team size matters: Collaboration and scientific impact since 1900. Journal of the Association for Information Science and Technology, 66(7), 1323–1332. doi: 10.1002/asi.23266 .Laudel, G. (2002). What do we measure by co-authorships? Research Evaluation, 11(1), 3–15. doi: 10.3152/147154402781776961 .Liu, X., Bollen, J., Nelson, M. L., & Van de Sompel, H. (2005). Co-authorship networks in the digital library research community. Information Processing and Management, 41(6), 1462–1480. doi: 10.1016/j.ipm.2005.03.012 .Liu, P., & Xia, H. (2015). Structure and evolution of co-authorship network in an interdisciplinary research field. Scientometrics, 103(1), 101–134. doi: 10.1007/s11192-014-1525-y .Ministerio de Sanidad y Consumo. Resolución de 30 de marzo de. (2006) del Instituto de Salud Carlos III, por la que se convocan ayudas destinadas a financiar estructuras estables de investigación cooperativa, en el área de biomedicina y ciencias de la salud, en el marco de la iniciativa Ingenio 2010, programa Consolider, acciones CIBER, 83 Boletín Oficial del Estado (pp. 13770–13777).Newman, M. E. J. (2001a). Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Physical Review E, 64(1), 016132. doi: 10.1103/PhysRevE.64.016132 .Newman, M. E. J. (2001b). Scientific collaboration networks. I. Network construction and fundamental results. Physical Review E, 64(1), 016131. doi: 10.1103/PhysRevE.64.016131 .Newman, M. E. J. (2003a). Mixing patterns in networks. Physical Review E, 67(2), 026126. doi: 10.1103/PhysRevE.67.026126 .Newman, M. E. J. (2003b). The structure and function of complex networks. SIAM Review, 45, 167–256.OECD. (2010). Measuring innovation: A new perspective. Paris: OCDE Publishing.Ramasco, J., & Morris, S. (2006). Social inertia in collaboration networks. Physical Review E, 73(1), 016122. doi: 10.1103/PhysRevE.73.016122 .Sonnenwald, D. H. (2007). Scientific collaboration. Annual Review of Information Science and Technology, 41(1), 643–681. doi: 10.1002/aris.2007.1440410121 .Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The increasing dominance of teams in production of knowledge. Science, 316(5827), 1036–1039. doi: 10.1126/science.1136099

    A cost-of-illness analysis of β-Thalassaemia major in children in Sri Lanka - experience from a tertiary level teaching hospital

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    Background Sri Lanka has a high prevalence of β-thalassaemia major. Clinical management is complex and long-term and includes regular blood transfusion and iron chelation therapy. The economic burden of β-thalassaemia for the Sri Lankan healthcare system and households is currently unknown. Methods A prevalence-based, cost-of-illness study was conducted on the Thalassaemia Unit, Department of Paediatrics, Kandy Teaching Hospital, Sri Lanka. Data were collected from clinical records, consultations with the head of the blood bank and a consultant paediatrician directly involved with the care of patients, alongside structured interviews with families to gather data on the personal costs incurred such as those for travel. Results Thirty-four children aged 2–17 years with transfusion dependent thalassaemia major and their parent/guardian were included in the study. The total average cost per patient year to the hospital was US2601ofwhichUS 2601 of which US 2092 were direct costs and US509wereoverheadcosts.MeanhouseholdexpenditurewasUS 509 were overhead costs. Mean household expenditure was US 206 per year with food and transport per transfusion (US7.57andUS 7.57 and US 4.26 respectively) being the highest cost items. Nine (26.5%) families experienced catastrophic levels of healthcare expenditure (> 10% of income) in the care of their affected child. The poorest households were the most likely to experience such levels of expenditure. Conclusions β-thalassaemia major poses a significant economic burden on health services and the families of affected children in Sri Lanka. Greater support is needed for the high proportion of families that suffer catastrophic out-of-pocket costs

    Disparities in the use of ambulatory surgical centers: a cross sectional study

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    <p>Abstract</p> <p>Background</p> <p>Ambulatory surgical centers (ASCs) provide outpatient surgical services more efficiently than hospital outpatient departments, benefiting patients through lower co-payments and other expenses. We studied the influence of socioeconomic status and race on use of ASCs.</p> <p>Methods</p> <p>From the 2005 State Ambulatory Surgery Database for Florida, a cohort of discharges for urologic, ophthalmologic, gastrointestinal, and orthopedic procedures was created. Socioeconomic status was established at the zip code level. Logistic regression models were fit to assess associations between socioeconomic status and ASC use.</p> <p>Results</p> <p>Compared to the lowest group, patients of higher socioeconomic status were more likely to have procedures performed in ASCs (OR 1.07 CI 1.05, 1.09). Overall, the middle socioeconomic status group was the most likely group to use the ASC (OR 1.23, CI 1.21 to 1.25). For whites and blacks, higher status is associated with increased ASC use, but for Hispanics this relationship was reversed (OR 0.84 CI 0.78, 0.91).</p> <p>Conclusion</p> <p>Patients of lower socioeconomic status treated with outpatient surgery are significantly less likely to have their procedures in ASCs, suggesting that less resourced patients are encountering higher cost burdens for care. Thus, the most economically vulnerable group is unnecessarily subject to higher charges for surgery.</p

    ICTs and the Challenge of Health System Transition in Low and Middle-Income Countries

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    The aim of this paper is to contribute to debates about how governments and other stakeholders can influence the application of ICTs to increase access to safe, effective and affordable treatment of common illnesses, especially by the poor. First, it argues that the health sector is best conceptualized as a ‘knowledge economy’. This supports a broadened view of health service provision that includes formal and informal arrangements for the provision of medical advice and drugs. This is particularly important in countries with a pluralistic health system, with relatively underdeveloped institutional arrangements. It then argues that reframing the health sector as a knowledge economy allows us to circumvent the blind spots associated with donor-driven ICT-interventions and consider more broadly the forces that are driving e-health innovations. It draws on small case studies in Bangladesh and China to illustrate new types of organization and new kinds of relationship between organizations that are emerging. It argues that several factors have impeded the rapid diffusion of ICT innovations at scale including: the limited capacity of innovations to meet health service needs, the time it takes to build new kinds of partnership between public and private actors and participants in the health and communications sectors and the lack of a supportive regulatory environment. It emphasises the need to understand the political economy of the digital health knowledge economy and the new regulatory challenges likely to emerge. It concludes that governments will need to play a more active role to facilitate the diffusion of beneficial ICT innovations at scale and ensure that the overall pattern of health system development meets the needs of the population, including the poor

    The economic pressures for biosimilar drug use in cancer medicine

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    The main rationale for using biosimilar drugs is for cost saving. The market development for biosimilar drugs will therefore depend on the degree to which cost saving measures are required by nations, medical insurers and individuals and the absolute savings that could be gained by switching from original drugs. This paper is designed to discover the degree to which financial constraints will drive future health spending and to discover if legal or safety issues could impact on any trend. A structured literature search was performed for papers and documents to 27 August 2011. Where multiple sources of data were available on a topic, data from papers and reports by multinational or national bodies were used in preference to data from regions or individual hospitals. Almost all health systems face current significant cost pressures. The twin driver of increasing cancer prevalence as populations age and cancer medicine costs rising faster than inflation places oncology as the most significant single cost problem. For some countries, this is predicted to make medicine unaffordable within a decade. Most developed countries have planned to embrace biosimilar use as a cost-control measure. Biosimilar introduction into the EU has already forced prices down, both the price of biosimilar drugs and competitive price reductions in originator drugs. Compound annual growth rates of use have been predicted at 65.8% per year. Most developed countries have planned to embrace biosimilar use as a major cost-control measure. Only legal blocks and safety concerns are likely to act against this trend. For centralised healthcare systems, and those with a strong tradition of generic medicine use, biosimilar use will clearly rise with predictions of more than 80% of prescriptions of some biologic drugs within 1 year of market entry in the USA. Delaying the implementation of such programmes however risks a real crisis in healthcare delivery for many countries and hospitals that few can now afford

    Socialization and generational political trajectories: an age, period and cohort analysis of political participation in Britain

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    The role of political socialization in explaining disengagement from specific modes of activism beyond voting remains largely unexplored, limited to date by available data and methods. While most previous studies have tended to propose explanations for disengagement linked to specific repertoires of political action, we propose a unified theory based on the different socialization experiences of subsequent generations. We test this theory using a new dataset of collated waves of the British Social Attitudes Survey and by applying age–period–cohort models for repeated cross-sectional data and generalized additive models to identify generational effects. We show that generational effects underlie the participatory decline across repertoires. Consistent with our expectations, the results reveal that the generation of “Thatcher’s Children” are much less likely to engage in a range of repertoires of political action than “Wilson/Callaghan’s Children”, who came of age in the more politicized 1960s and 1970s. Significantly, and in line with our theoretical expectations, the “Blair’s Babies” generation is the least politically engaged of all. We reflect on these findings and highlight the concerning implications of falling levels of activism for advanced democracies
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