Social Networks among Elderly Women: Implications for Health Education Practice

The general aim of the present study was to examine and help clarify the properties of the distinctions between social networks and social support, their relationship to health status, and their impli cations for health education practice. More specifically, a secondary data analysis was conducted with 130 white women, community resi dents, between the ages of 60 and 68, which examined the relationship between psychological well-being and social network characteristics. These characteristics are categorized along three broad dimensions: structure—links in the overall network (size and density); interaction— nature of the linkages themselves (frequency, homogeneity, content, reciprocity, intensity, and dispersion); and functions which networks provide (affective support and instrumental support). A combination was made and relative strength investigated of several network char acteristics representative of the quality of interactions (i. e., reciprocal affective support, intensity, and affective support) and those repre senting the quantity of interactions (i.e., size, density, and frequency).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67277/2/10.1177_109019818301000304.pd

Data assimilation in a system with two scales-combining two initialization techniques

11 pages, 11 figures, 1 tableFull-text version available Open Access at: http://clivar.iim.csic.es/?q=es/node/319An ensemble Kalman filter (EnKF) is used to assimilate data onto a non-linear chaotic model, coupling two kinds of variables. The first kind of variables of the system is characterized as large amplitude, slow, large scale, distributed in eight equally spaced locations around a circle. The second kind of variables are small amplitude, fast, and short scale, distributed in 256 equally spaced locations. Synthetic observations are obtained from the model and the observational error is proportional to their respective amplitudes. The performance of the EnKF is affected by differences in the spatial correlation scales of the variables being assimilated. This method allows the simultaneous assimilation of all the variables. The ensemble filter also allows assimilating only the large-scale variables, letting the small-scale variables to freely evolve. Assimilation of the large-scale variables together with a few small-scale variables significantly degrades the filter. These results are explained by the spurious correlations that arise from the sampled ensemble covariances. An alternative approach is to combine two different initialization techniques for the slow and fast variables. Here, the fast variables are initialized by restraining the evolution of the ensemble members, using a Newtonian relaxation toward the observed fast variables. Then, the usual ensemble analysis is used to assimilate the large-scale observationsThis study is supported by the Spanish National Science Program under contracts ESP2005–06823-C05 and ESP2007–65667-C04Peer reviewe

Vacuum structure for scalar cosmological perturbations in Modified Gravity Models

We have found for the general class of Modified Gravity Models f(R,G) a new instability which can arise in vacuum for the scalar modes of the cosmological perturbations if the background is not de Sitter. In particular, the short-wavelength modes, if stable, in general have a group velocity which depends linearly in k, the wave number. Therefore these modes will be in general superluminal. We have also discussed the condition for which in general these scalar modes will be ghost-like. There is a subclass of these models, defined out of properties of the function f(R,G) and to which the f(R) and f(G) models belong, which however does not have this feature.Comment: 17 pages, 1 figure, uses RevTeX, references adde

Measurement of Dijet Azimuthal Decorrelations at Central Rapidities in pp-bar Collisions at sqrt(s)=1.96 TeV

Correlations in the azimuthal angle between the two largest transverse momentum jets have been measured using the D0 detector in pp-bar collisions at a center-of-mass energy sqrt(s)=1.96 TeV. The analysis is based on an inclusive dijet event sample in the central rapidity region corresponding to an integrated luminosity of 150 pb-1. Azimuthal correlations are stronger at larger transverse momenta. These are well-described in perturbative QCD at next-to-leading order in the strong coupling constant, except at large azimuthal differences where soft effects are significant.Comment: 6 pages, 3 Figures submitted to Phys. Rev. Let

Search for doubly charged Higgs boson pair production in the decay to mu(+)mu(+)mu(-)mu(-) in p(p)over-bar collisions at root s=1.96 TeV

A search for pair production of doubly charged Higgs bosons in the process p (p) over bar -->H++H---->mu(+)mu(+)mu(-)mu(-) is performed with the D0 run II detector at the Fermilab Tevatron. The analysis is based on a sample of inclusive dimuon data collected at an energy of roots=1.96 TeV, corresponding to an integrated luminosity of 113 pb(-1). In the absence of a signal, 95% confidence level mass limits of M(H-L(+/-+/-))>118.4 GeV/c(2) and M(H-R(+/-+/-))>98.2 GeV/c(2) are set for left-handed and right-handed doubly charged Higgs bosons, respectively, assuming 100% branching into muon pairs

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

Physician, Practice, and Patient Characteristics Associated With Biosimilar Use in Medicare Recipients

Biosimilars, or highly similar versions of complex biologic drugs, have the potential to slow drug spending growth; however, biosimilar uptake in the United States has been slow. Little is known about barriers to biosimilar uptake following drug launch. To examine the patient, physician, and practice characteristics associated with biosimilar use in the Medicare population. This cross-sectional study used regression analysis to estimate the association between biosimilar use and various characteristics. Medicare fee-for-service beneficiaries who received a filgrastim product or an infliximab product between the launch of a class's first biosimilar (quarter 3 2015 for filgrastim-sndz and quarter 4 2016 for infliximab-dyyb) and December 2018. Data analysis was conducted from March to November 2020. Patient demographic characteristics and product clinical indications; physician demographic characteristics, specialty, and volume of filgrastim or infliximab biologic administration; hospital size, ownership, 340B status, academic medical center status, and system affiliation; physician office size and multispecialty status. Administration of a filgrastim or infliximab biosimilar. The final filgrastim sample included 25 870 patients (11 857 [45.8%] men; 14 224 [55.0%] aged 65-74 years; 22 617 [87.4%] White individuals) who had 259 178 administrations (79 017 [30.5%] biosimilar administrations), and the final infliximab sample included 14 786 patients (4765 [32.2%] men; 8773 [59.3%] aged 65-74 years; 13 467 [91.1%] White individuals) who had 174 973 administrations (9012 [5.2%] biosimilar administrations). In adjusted analyses, no patient demographic characteristics and 2 of 9 clinical indications (22.2%) were associated with biosimilar use (filgrastim, neutropenia: adjusted difference, -2.0 [95% CI, -3.9 to -0.2] percentage points; P = .03; infliximab, Crohn disease: adjusted difference, -1.8 [95% CI, -2.9 to -0.8] percentage points; P = .001). Several physician characteristics were associated with biosimilar administrations, including high filgrastim or infliximab prescribing volume (high vs low volume, filgrastim: adjusted difference, 3.6 [95% CI, 1.5 to 5.8] percentage points; P = .001; infliximab: adjusted difference, 1.2 [95% CI, 0.3 to 2.2] percentage points; P = .007) and specialty (eg, hematologist-oncologists vs primary care, filgrastim: adjusted difference, -3.0 [95% CI, -5.4 to -0.5] percentage points; P = .02). Numerous practice characteristics were associated with biosimilar use, including practice setting (outpatient hospital department vs office practice, filgrastim: adjusted difference, -16.1 [95% CI, -18.1 to -14.1] percentage points; P < .001; infliximab: adjusted difference, 3.0 [95% CI, 2.2 to 3.7] percentage points; P < .001) and hospital outpatient department ownership status (for-profit vs not-for-profit, filgrastim: adjusted difference, -17.4 [95% CI, -21.6 to -13.3] percentage points; P < .001; infliximab: adjusted difference, 10.8 [95% CI, 6.7 to 14.9] percentage points; P < .001). In this study, practice setting and hospital ownership status had the largest associations with biosimilar usage, suggesting practices play a role in steering physicians toward certain medications. However, the types of practices with high biosimilar use differed by drug class. Further research is needed to understand the reasons for these differences across drug classes