1,399 research outputs found

    The various power decays of the survival probability at long times for free quantum particle

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    The long time behaviour of the survival probability of initial state and its dependence on the initial states are considered, for the one dimensional free quantum particle. We derive the asymptotic expansion of the time evolution operator at long times, in terms of the integral operators. This enables us to obtain the asymptotic formula for the survival probability of the initial state ψ(x)\psi (x), which is assumed to decrease sufficiently rapidly at large x|x|. We then show that the behaviour of the survival probability at long times is determined by that of the initial state ψ\psi at zero momentum k=0k=0. Indeed, it is proved that the survival probability can exhibit the various power-decays like t2m1t^{-2m-1} for an arbitrary non-negative integers mm as tt \to \infty , corresponding to the initial states with the condition ψ^(k)=O(km)\hat{\psi} (k) = O(k^m) as k0k\to 0.Comment: 15 pages, to appear in J. Phys.

    Looking inside the black box : a theory-based process evaluation alongside a randomised controlled trial of printed educational materials (the Ontario printed educational message, OPEM) to improve referral and prescribing practices in primary care in Ontario, Canada

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    Background: Randomised controlled trials of implementation strategies tell us whether (or not) an intervention results in changes in professional behaviour but little about the causal mechanisms that produce any change. Theory-based process evaluations collect data on theoretical constructs alongside randomised trials to explore possible causal mechanisms and effect modifiers. This is similar to measuring intermediate endpoints in clinical trials to further understand the biological basis of any observed effects (for example, measuring lipid profiles alongside trials of lipid lowering drugs where the primary endpoint could be reduction in vascular related deaths). This study protocol describes a theory-based process evaluation alongside the Ontario Printed Educational Message (OPEM) trial. We hypothesize that the OPEM interventions are most likely to operate through changes in physicians' behavioural intentions due to improved attitudes or subjective norms with little or no change in perceived behavioural control. We will test this hypothesis using a well-validated social cognition model, the theory of planned behaviour (TPB) that incorporates these constructs. Methods/design: We will develop theory-based surveys using standard methods based upon the TPB for the second and third replications, and survey a subsample of Ontario family physicians from each arm of the trial two months before and six months after the dissemination of the index edition of informed, the evidence based newsletter used for the interventions. In the third replication, our study will converge with the "TRY-ME" protocol (a second study conducted alongside the OPEM trial), in which the content of educational messages was constructed using both standard methods and methods informed by psychological theory. We will modify Dillman's total design method to maximise response rates. Preliminary analyses will initially assess the internal reliability of the measures and use regression to explore the relationships between predictor and dependent variable (intention to advise diabetic patients to have annual retinopathy screening and to prescribe thiazide diuretics for first line treatment of uncomplicated hypertension). We will then compare groups using methods appropriate for comparing independent samples to determine whether there have been changes in the predicted constructs (attitudes, subjective norms, or intentions) across the study groups as hypothesised, and will assess the convergence between the process evaluation results and the main trial results.The OPEM trial and OPEM process evaluation are funded by the Canadian Institute of Health Research (CIHR). The OPEM process evaluation study was developed as part of the CIHR funded interdisciplinary capacity enhancement team KT-ICEBeRG. Gaston Godin, Jeremy Grimshaw and France Légaré hold Canada Research Chairs. Louise Lemyre holds an R.S. McLaughlin Research Chair

    Mandatory Disclosure of Pharmaceutical Industry-Funded Events for Health Professionals

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    David Henry and colleagues examine compliance with new disclosure requirements of Medicines Australia, the pharmaceutical industry representative body, and argue that they fall short and instead more comprehensive reporting standards are needed

    Cardiovascular disease in a cohort exposed to the 1940-45 Channel Islands occupation

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    BACKGROUND To clarify the nature of the relationship between food deprivation/undernutrition during pre- and postnatal development and cardiovascular disease (CVD) in later life, this study examined the relationship between birth weight (as a marker of prenatal nutrition) and the incidence of hospital admissions for CVD from 1997–2005 amongst 873 Guernsey islanders (born in 1923–1937), 225 of whom had been exposed to food deprivation as children, adolescents or young adults (i.e. postnatal undernutrition) during the 1940–45 German occupation of the Channel Islands, and 648 of whom had left or been evacuated from the islands before the occupation began. METHODS Three sets of Cox regression models were used to investigate (A) the relationship between birth weight and CVD, (B) the relationship between postnatal exposure to the occupation and CVD and (C) any interaction between birth weight, postnatal exposure to the occupation and CVD. These models also tested for any interactions between birth weight and sex, and postnatal exposure to the occupation and parish of residence at birth (as a marker of parish residence during the occupation and related variation in the severity of food deprivation). RESULTS The first set of models (A) found no relationship between birth weight and CVD even after adjustment for potential confounders (hazard ratio (HR) per kg increase in birth weight: 1.12; 95% confidence intervals (CI): 0.70 – 1.78), and there was no significant interaction between birth weight and sex (p = 0.60). The second set of models (B) found a significant relationship between postnatal exposure to the occupation and CVD after adjustment for potential confounders (HR for exposed vs. unexposed group: 2.52; 95% CI: 1.54 – 4.13), as well as a significant interaction between postnatal exposure to the occupation and parish of residence at birth (p = 0.01), such that those born in urban parishes (where food deprivation was worst) had a greater HR for CVD than those born in rural parishes. The third model (C) found no interaction between birth weight and exposure to the occupation (p = 0.43). CONCLUSION These findings suggest that the levels of postnatal undernutrition experienced by children, adolescents and young adults exposed to food deprivation during the 1940–45 occupation of the Channel Islands were a more important determinant of CVD in later life than the levels of prenatal undernutrition experienced in utero prior to the occupatio

    Erectile Dysfunction as an Independent Predictor of Future Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis

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    Vascular erectile dysfunction (ED) and cardiovascular disease (CVD) share common risk factors including obesity, hypertension, metabolic syndrome, diabetes mellitus, and smoking. ED and CVD also have common underlying pathological mechanisms, including endothelial dysfunction, inflammation, and atherosclerosis.1 Despite these close relationships, the evidence documenting ED as an independent predictor of future CVD events is limited

    An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

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    The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects. I describe 4 different propensity score methods: matching on the propensity score, stratification on the propensity score, inverse probability of treatment weighting using the propensity score, and covariate adjustment using the propensity score. I describe balance diagnostics for examining whether the propensity score model has been adequately specified. Furthermore, I discuss differences between regression-based methods and propensity score-based methods for the analysis of observational data. I describe different causal average treatment effects and their relationship with propensity score analyses

    Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox

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    This article discusses three statistical paradoxes that pervade epidemiological research: Simpson's paradox, Lord's paradox, and suppression. These paradoxes have important implications for the interpretation of evidence from observational studies. This article uses hypothetical scenarios to illustrate how the three paradoxes are different manifestations of one phenomenon – the reversal paradox – depending on whether the outcome and explanatory variables are categorical, continuous or a combination of both; this renders the issues and remedies for any one to be similar for all three. Although the three statistical paradoxes occur in different types of variables, they share the same characteristic: the association between two variables can be reversed, diminished, or enhanced when another variable is statistically controlled for. Understanding the concepts and theory behind these paradoxes provides insights into some controversial or contradictory research findings. These paradoxes show that prior knowledge and underlying causal theory play an important role in the statistical modelling of epidemiological data, where incorrect use of statistical models might produce consistent, replicable, yet erroneous results
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