Communication interventions to promote the public's awareness of antibiotics: a systematic review.

BackgroundInappropriate antibiotic use is implicated in antibiotic resistance and resultant morbidity and mortality. Overuse is particularly prevalent for outpatient respiratory infections, and perceived patient expectations likely contribute. Thus, various educational programs have been implemented to educate the public.MethodsWe systematically identified public-directed interventions to promote antibiotic awareness in the United States. PubMed, Google Scholar, Embase, CINAHL, and Scopus were queried for articles published from January 1996 through January 2016. Two investigators independently assessed titles and abstracts of retrieved articles for subsequent full-text review. References of selected articles and three review articles were likewise screened for inclusion. Identified educational interventions were coded for target audience, content, distribution site, communication method, and major outcomes.ResultsOur search yielded 1,106 articles; 34 met inclusion criteria. Due to overlap in interventions studied, 29 distinct educational interventions were identified. Messages were primarily delivered in outpatient clinics (N = 24, 83%) and community sites (N = 12, 41%). The majority included clinician education. Antibiotic prescription rates were assessed for 22 interventions (76%). Patient knowledge, attitudes, and beliefs (KAB) were assessed for 10 interventions (34%). Similar rates of success between antibiotic prescription rates and patient KAB were reported (73 and 70%, respectively). Patient interventions that did not include clinician education were successful to increase KAB but were not shown to decrease antibiotic prescribing. Three interventions targeted reductions in Streptococcus pneumoniae resistance; none were successful.ConclusionsMessaging programs varied in their designs, and many were multifaceted in their approach. These interventions can change patient perspectives regarding antibiotic use, though it is unclear if clinician education is also necessary to reduce antibiotic prescribing. Further investigations are needed to determine the relative influence of interventions focusing on patients and physicians and to determine whether these changes can influence rates of antibiotic resistance long-term

First measurement of discrimination between helium and electron recoils in liquid xenon for low-mass dark matter searches

We report the first measurement of discrimination between low-energy helium recoils and electron recoils in liquid xenon. This result is relevant to proposed low-mass dark matter searches which seek to dissolve light target nuclei in the active volume of liquid-xenon time projection chambers. Low-energy helium recoils were produced by degrading $\alpha$ particles from $^{210}$Po with a gold foil situated on the cathode of a liquid xenon time-projection chamber. The resulting population of helium recoil events is well separated from electron recoils and is also offset from the expected position of xenon nuclear recoil events.Comment: 4 pages, 3 figure

Identifying the sources of uncertainty in climate model simulations of solar radiation modification with the G6sulfur and G6solar Geoengineering Model Intercomparison Project (GeoMIP) simulations

We present here results from the Geoengineering Model Intercomparison Project (GeoMIP) simulations for the experiments G6sulfur and G6solar for six Earth system models participating in the Climate Model Intercomparison Project (CMIP) Phase 6. The aim of the experiments is to reduce the warming that results from a high-tier emission scenario (Shared Socioeconomic Pathways SSP5-8.5) to that resulting from a medium-tier emission scenario (SSP2-4.5). These simulations aim to analyze the response of climate models to a reduction in incoming surface radiation as a means to reduce global surface temperatures, and they do so either by simulating a stratospheric sulfate aerosol layer or, in a more idealized way, through a uniform reduction in the solar constant in the model. We find that over the final two decades of this century there are considerable inter-model spreads in the needed injection amounts of sulfate (29±9Tg-SO2/yr between 2081 and 2100), in the latitudinal distribution of the aerosol cloud and in the stratospheric temperature changes resulting from the added aerosol layer. Even in the simpler G6solar experiment, there is a spread in the needed solar dimming to achieve the same global temperature target (1.91±0.44). The analyzed models already show significant differences in the response to the increasing CO2 concentrations for global mean temperatures and global mean precipitation (2.05K±0.42K and 2.28±0.80, respectively, for SSP5-8.5 minus SSP2-4.5 averaged over 2081-2100). With aerosol injection, the differences in how the aerosols spread further change some of the underlying uncertainties, such as the global mean precipitation response (-3.79±0.76 for G6sulfur compared to -2.07±0.40 for G6solar against SSP2-4.5 between 2081 and 2100). These differences in the behavior of the aerosols also result in a larger uncertainty in the regional surface temperature response among models in the case of the G6sulfur simulations, suggesting the need to devise various, more specific experiments to single out and resolve particular sources of uncertainty. The spread in the modeled response suggests that a degree of caution is necessary when using these results for assessing specific impacts of geoengineering in various aspects of the Earth system. However, all models agree that compared to a scenario with unmitigated warming, stratospheric aerosol geoengineering has the potential to both globally and locally reduce the increase in surface temperatures. © 2021 Daniele Visioni et al

A new Geoengineering Model Intercomparison Project (GeoMIP) experiment designed for climate and chemistry models

A new Geoengineering Model Intercomparison Project (GeoMIP) experiment "G4 specified stratospheric aerosols" (short name: G4SSA) is proposed to investigate the impact of stratospheric aerosol geoengineering on atmosphere, chemistry, dynamics, climate, and the environment. In contrast to the earlier G4 GeoMIP experiment, which requires an emission of sulfur dioxide (SO2) into the model, a prescribed aerosol forcing file is provided to the community, to be consistently applied to future model experiments between 2020 and 2100. This stratospheric aerosol distribution, with a total burden of about 2 Tg S has been derived using the ECHAM5-HAM microphysical model, based on a continuous annual tropical emission of 8 Tg SO2 yr−1. A ramp-up of geoengineering in 2020 and a ramp-down in 2070 over a period of 2 years are included in the distribution, while a background aerosol burden should be used for the last 3 decades of the experiment. The performance of this experiment using climate and chemistry models in a multi-model comparison framework will allow us to better understand the impact of geoengineering and its abrupt termination after 50 years in a changing environment. The zonal and monthly mean stratospheric aerosol input data set is available at https://www2.acd.ucar.edu/gcm/geomip-g4-specified-stratospheric-aerosol-data-set

Phase field approach to optimal packing problems and related Cheeger clusters

In a fixed domain of $\Bbb{R}^N$ we study the asymptotic behaviour of optimal clusters associated to $\alpha$-Cheeger constants and natural energies like the sum or maximum: we prove that, as the parameter $\alpha$ converges to the "critical" value $\Big (\frac{N-1}{N}\Big ) _+$, optimal Cheeger clusters converge to solutions of different packing problems for balls, depending on the energy under consideration. As well, we propose an efficient phase field approach based on a multiphase Gamma convergence result of Modica-Mortola type, in order to compute $\alpha$-Cheeger constants, optimal clusters and, as a consequence of the asymptotic result, optimal packings. Numerical experiments are carried over in two and three space dimensions

North Atlantic Oscillation response in GeoMIP experiments G6solar and G6sulfur: why detailed modelling is needed for understanding regional implications of solar radiation management

This is the final version. Available from Copernicus Publications via the DOI in this record. The realization of the difficulty of limiting global-mean temperatures to within 1.5 or 2.0 ∘C above pre-industrial levels stipulated by the 21st Conference of Parties in Paris has led to increased interest in solar radiation management (SRM) techniques. Proposed SRM schemes aim to increase planetary albedo to reflect more sunlight back to space and induce a cooling that acts to partially offset global warming. Under the auspices of the Geoengineering Model Intercomparison Project, we have performed model experiments whereby global temperature under the high-forcing SSP5-8.5 scenario is reduced to follow that of the medium-forcing SSP2-4.5 scenario. Two different mechanisms to achieve this are employed: the first via a reduction in the solar constant (experiment G6solar) and the second via modelling injections of sulfur dioxide (experiment G6sulfur) which forms sulfate aerosol in the stratosphere. Results from two state-of-the-art coupled Earth system models (UKESM1 and CESM2-WACCM6) both show an impact on the North Atlantic Oscillation (NAO) in G6sulfur but not in G6solar. Both models show a persistent positive anomaly in the NAO during the Northern Hemisphere winter season in G6sulfur, suggesting an increase in zonal flow and an increase in North Atlantic storm track activity impacting the Eurasian continent and leading to high-latitude warming over Europe and Asia. These results are broadly consistent with previous findings which show similar impacts from stratospheric volcanic aerosol on the NAO and emphasize that detailed modelling of geoengineering processes is required if accurate impacts of SRM effects are to be simulated. Differences remain between the two models in predicting regional changes over the continental USA and Africa, suggesting that more models need to perform such simulations before attempting to draw any conclusions regarding potential continental-scale climate change under SRM.US National Science Foundatio

The Effect of Patients’ Met Expectations on Consultation Outcomes. A Study with Family Medicine Residents

OBJECTIVES: To know the patients’ expectations and the fulfillment of these at family medicine consultations by resident doctors and to assess their effect on some consultation outcomes. DESIGN: A prospective cohort study. PARTICIPANTS: Patients attending family medicine consultations held by 38 resident doctors: 1,301 eligible patients, 702 filled in all questionnaires. MEASUREMENTS: Before each visit, the patients’ expectations about that particular consultation were registered. Right after the visit was over, their perception of several aspects of the communicative interaction with the doctor was measured. Later, patients were interviewed on the phone to know how their expectations had been fulfilled, how satisfied they were about the consultation, how they had followed the doctor’s suggestions, if they were going to seek further care for the same cause later, and the evolution of their clinical problem. Logistic regression was the main analysis used. RESULTS: The most common expectations were the doctor showing interest and listening (30.5%), getting some information about the diagnosis (16.3%), and sharing problems and doubts (11.1%). The rate of main expectations that were met was 76.5%. Satisfaction with the encounter was associated with the clinical evolution [odds ratio (OR) 2.23; confidence interval (CI): 1.32–3.75], and the fulfilling of the patients’ main or two main expectations was significantly related to all the measured outcomes (satisfaction OR 3.51, CI: 1.73–7.8; adherence OR 1.80, CI: 1.11–2.92; clinical evolution OR 1.54, CI: 1.01–2.35; and seeking further care later OR 0.54, CI:0.36–0.81) CONCLUSIONS: Patients prioritize expectations of a more general sort when they attend primary care consultations and residents fulfill these acceptably. The fulfillment of expectations seems to affect the studied outcomes more than other factors

Centre selection for clinical trials and the generalisability of results: a mixed methods study.

BACKGROUND: The rationale for centre selection in randomised controlled trials (RCTs) is often unclear but may have important implications for the generalisability of trial results. The aims of this study were to evaluate the factors which currently influence centre selection in RCTs and consider how generalisability considerations inform current and optimal practice. METHODS AND FINDINGS: Mixed methods approach consisting of a systematic review and meta-summary of centre selection criteria reported in RCT protocols funded by the UK National Institute of Health Research (NIHR) initiated between January 2005-January 2012; and an online survey on the topic of current and optimal centre selection, distributed to professionals in the 48 UK Clinical Trials Units and 10 NIHR Research Design Services. The survey design was informed by the systematic review and by two focus groups conducted with trialists at the Birmingham Centre for Clinical Trials. 129 trial protocols were included in the systematic review, with a total target sample size in excess of 317,000 participants. The meta-summary identified 53 unique centre selection criteria. 78 protocols (60%) provided at least one criterion for centre selection, but only 31 (24%) protocols explicitly acknowledged generalisability. This is consistent with the survey findings (n = 70), where less than a third of participants reported generalisability as a key driver of centre selection in current practice. This contrasts with trialists' views on optimal practice, where generalisability in terms of clinical practice, population characteristics and economic results were prime considerations for 60% (n = 42), 57% (n = 40) and 46% (n = 32) of respondents, respectively. CONCLUSIONS: Centres are rarely enrolled in RCTs with an explicit view to external validity, although trialists acknowledge that incorporating generalisability in centre selection should ideally be more prominent. There is a need to operationalize 'generalisability' and incorporate it at the design stage of RCTs so that results are readily transferable to 'real world' practice