Die Förderung von Tax Literacy als Beitrag zur ökonomischen Bildung von Schüler/innen - Erste Einblicke in ein Projekt der WU Wien und der Joachim Herz Stiftung

Der im Jahr 2015 erschienene Grundsatzerlass zur Wirtschafts- und Verbraucher/innenbildung sieht vor, dass Schüler/innen im Rahmen ihrer Schulausbildung mit Kompetenzen ausgestattet werden sollen, "die zu einer aktiven und reflektierten Teilnahme am Wirtschaftsleben [...] befähigen" (BMBF 2015, 1). Diese Teilnahme beinhaltet ein kompetentes und moralisches Urteilsvermögen sowie eine grundlegende Handlungsfähigkeit in wirtschaftlich geprägten Lebens -und Alltagssituationen. Hierbei sind u. a. ein fundiertes Wissen und gute Problemlösungsfähigkeiten im Bereich der Steuerlehre zentral. Dies kann durch die regelmäßige Konfrontation der Schüler/innen mit der Thematik, sowohl freiwillig als auch unfreiwillig, begründet werden (vgl. Doralt/Ruppe/Mayr 2013,1). Steuerthematiken erfordern ein fundiertes Verständnis, um in den verschiedenstenRollen alltägliche Situationen angemessen bewältigen zu können. Eine wissenschaftliche Interviewstudie hat außerdem gezeigt, dass eine Forderung nach der Vermittlung von Wissen im Bereich der Steuerlehre nicht nur seitens des Bundesministeriums für Bildung und Frauen (BMBF) besteht, sondern dass sich auch die betroffenen Schüler/innen mehr Aufklärung und Kenntnisse in diesem Fachgebiet wünschen (vgl. Szoncsitz et al. 2017, 51). Im vorliegenden Beitrag wird ein gemeinschaftliches Projekt zwischen der Wirtschaftsuniversität Wien und der Joachim Herz Stiftung (Hamburg) vorgestellt und auf gezeigt, welche Möglichkeiten bestehen, den Forderungen des BMBF und der Schüler/innen nachzukommen

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function

Background: Most confirmatory randomised controlled clinical trials (RCTs) are designed with specified power, usually 80% or 90%, for a hypothesis test conducted at a given significance level, usually 2.5% for a one-sided test. Approval of the experimental treatment by regulatory agencies is then based on the result of such a significance test with other information to balance the risk of adverse events against the benefit of the treatment to future patients. In the setting of a rare disease, recruiting sufficient patients to achieve conventional error rates for clinically reasonable effect sizes may be infeasible, suggesting that the decision-making process should reflect the size of the target population. Methods: We considered the use of a decision-theoretic value of information (VOI) method to obtain the optimal sample size and significance level for confirmatory RCTs in a range of settings. We assume the decision maker represents society. For simplicity we assume the primary endpoint to be normally distributed with unknown mean following some normal prior distribution representing information on the anticipated effectiveness of the therapy available before the trial. The method is illustrated by an application in an RCT in haemophilia A. We explicitly specify the utility in terms of improvement in primary outcome and compare this with the costs of treating patients, both financial and in terms of potential harm, during the trial and in the future. Results: The optimal sample size for the clinical trial decreases as the size of the population decreases. For non-zero cost of treating future patients, either monetary or in terms of potential harmful effects, stronger evidence is required for approval as the population size increases, though this is not the case if the costs of treating future patients are ignored. Conclusions: Decision-theoretic VOI methods offer a flexible approach with both type I error rate and power (or equivalently trial sample size) depending on the size of the future population for whom the treatment under investigation is intended. This might be particularly suitable for small populations when there is considerable information about the patient population

Approaches to sample size calculation for clinical trials in rare diseases

We discuss 3 alternative approaches to sample size calculation: traditional sample size calculation based on power to show a statistically significant effect, sample size calculation based on assurance, and sample size based on a decision-theoretic approach. These approaches are compared head-to-head for clinical trial situations in rare diseases. Specifically, we consider 3 case studies of rare diseases (Lyell disease, adult-onset Still disease, and cystic fibrosis) with the aim to plan the sample size for an upcoming clinical trial. We outline in detail the reasonable choice of parameters for these approaches for each of the 3 case studies and calculate sample sizes. We stress that the influence of the input parameters needs to be investigated in all approaches and recommend investigating different sample size approaches before deciding finally on the trial size. Highly influencing for the sample size are choice of treatment effect parameter in all approaches and the parameter for the additional cost of the new treatment in the decision-theoretic approach. These should therefore be discussed extensively

Measuring Political Commitment in Statistical Models for Evidence-based Agenda Setting in Nonmotorized Traffic

When investigating national and international transport policies of the last decade, an ever increasing emphasis on promoting non-motorized transport modes such as walking or cycling can be identified, aiming at reaching multiple political targets (eg. reducing pollution, increasing health or lowering land consumption). However, despite substantial financial efforts being put into infrastructural or awarenessraising activities, achieving the desired modal shift towards active mobility remains a challenge. This is frequently due to unclear cause and effect patterns between active mode shares and their determinants, which in turn leads to uncoordinated or highly fragmented initiatives that impede target-oriented planning. An internationally adopted approach to overcome this problem is applying aggregated statistical models that explain modal choice involving multiple regression techniques and hypothetical covariates. Still, general critique against these models points out that important intangible soft factors such as attitudinal characteristics of the local population or mind-sets and political commitment of decision makers are not duly reflected. Also, for Austria there is currently no systematic holistic approach to explain spatial variance in active travel shares on the scale of municipalities. Hence the main objective of our research is to design a comprehensive macroscopic model-based approach for the quantitative explanation of modal split shares in active travel modes in Austria. In our approach we attach great importance to the inclusion of soft factors in order to contribute novel findings on the dynamics behind active travel. The research outcomes will aid decision makers and planners in their question where and more specifically, how to effectively invest into active mobility by revealing key soft factors and intangible determinants of active travel mode shares alongside a broad range of more known, traditional factors. Based on this evidence-based decision support approach it is possible to simulate impacts of actions when aiming at locally promoting active travel modes

Recent advances in methodology for clinical trials in small populations : the InSPiRe project

Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This led to an EU FP7 call for proposals in 2013. One of the three projects funded was the Innovative Methodology for Small Populations Research (InSPiRe) project. This paper summarizes the main results of the project, which was completed in 2017. The InSPiRe project has led to development of novel statistical methodology for clinical trials in small populations in four areas. We have explored new decision-making methods for small population clinical trials using a Bayesian decision-theoretic framework to compare costs with potential benefits, developed approaches for targeted treatment trials, enabling simultaneous identification of subgroups and confirmation of treatment effect for these patients, worked on early phase clinical trial design and on extrapolation from adult to pediatric studies, developing methods to enable use of pharmacokinetics and pharmacodynamics data, and also developed improved robust meta-analysis methods for a small number of trials to support the planning, analysis and interpretation of a trial as well as enabling extrapolation between patient groups. In addition to scientific publications, we have contributed to regulatory guidance and produced free software in order to facilitate implementation of the novel methods

Impact of Age and Body Site on Adult Female Skin Surface pH

Background: pH is known as an important parameter in epidermal barrier function and homeostasis. Aim: The impact of age and body site on skin surface pH (pH(SS)) of women was evaluated in vivo. Methods: Time domain dual lifetime referencing with luminescent sensor foils was used for pH(SS) measurements. pH(SS) was measured on the forehead, the temple, and the volar forearm of adult females (n = 97, 52.87 +/- 18.58 years, 20-97 years). Every single measurement contained 2,500 pH values due to the luminescence imaging technique used. Results: pH(SS) slightly increases with age on all three investigated body sites. There are no significant differences in pH(SS) between the three investigated body sites. Conclusion: Adult pH(SS) on the forehead, the temple and the volar forearm increases slightly with age. This knowledge is crucial for adapting medical skin care products. Copyright (C) 2012 S. Karger AG, Base

Risk stratification for venous thromboembolism in patients with testicular germ cell tumors

BACKGROUND:Patients with testicular germ cell tumors (TGCT) have an increased risk for venous thromboembolism (VTE). We identified risk factors for VTE in this patient cohort and developed a clinical risk model. METHODS:In this retrospective cohort study at the Medical University of Graz we included 657 consecutive TGCT patients across all clinical stages. A predictive model for VTE was developed and externally validated in 349 TGCT patients treated at the University Hospital Zurich. RESULTS:Venous thromboembolic events occurred in 34 (5.2%) patients in the Graz cohort. In univariable competing risk analysis, higher clinical stage (cS) and a retroperitoneal lymphadenopathy (RPLN) were the strongest predictors of VTE (p<0.0001). As the presence of a RPLN with more than 5cm in greatest dimension without coexisting visceral metastases is classified as cS IIC, we constructed an empirical VTE risk model with the following four categories (12-month-cumulative incidence): cS IA-B 8/463 patients (1.7%), cS IS-IIB 5/86 patients (5.9%), cS IIC 3/21 patients (14.3%) and cS IIIA-C 15/70 patients (21.4%). This risk model was externally validated in the Zurich cohort (12-month-cumulative incidence): cS IA-B (0.5%), cS IS-IIB (6.0%), cS IIC (11.1%) and cS IIIA-C (19.1%). Our model had a significantly higher discriminatory performance than a previously published classifier (RPLN-VTE-risk-classifier) which is based on the size of RPLN alone (AUC-ROC: 0.75 vs. 0.63, p = 0.007). CONCLUSIONS:According to our risk stratification, TGCT patients with cS IIC and cS III disease have a very high risk of VTE and may benefit from primary thromboprophylaxis for the duration of chemotherapy

Cost and performance of some carbon capture technology options for producing different quality CO₂ product streams

A techno-economic assessment of power plants with CO2 capture technologies with a focus on process scenarios that deliver different grades of CO2 product purity is presented. The three leading CO2 capture technologies are considered, namely; oxyfuel combustion, pre-combustion and post-combustion capture. The study uses a combination of process simulation of flue gas cleaning processes, modelling with a power plant cost and performance calculator and literature values of key performance criteria in order to evaluate the performance, cost and CO2 product purity of the considered CO2 capture options. For oxyfuel combustion capture plants, three raw CO2 flue gas processing strategies of compression and dehydration only, double flash system purification and distillation purification are considered. Analysis of pre-combustion capture options is based on integrated gasification combined cycle plants using physical solvent systems for capturing CO2 and sulfur species via three routes; co-capture of sulfur impurities with the CO2 stream using Selexol™ solvent, separate capture of CO2 and sulfur impurities using Selexol™, and Rectisol® solvent systems for separate capture of sulfur impurities and CO2. Analysis of post-combustion capture plants was made with and without some conventional pollution control devices. The results highlight the wide variation in CO2 product purity for different oxyfuel combustion capture scenarios and the wide cost variation for the pre-combustion capture scenarios. The post-combustion capture plant with conventional pollution control devices offers high CO2 purity (99.99 mol%) for average cost of considered technologies. The calculations performed will be of use in further analyses of whole chain CCS for the safe and economic capture, transport and storage of CO2

Worldwide variations in artificial skyglow

Despite constituting a widespread and significant environmental change, understanding of artificial nighttime skyglow is extremely limited. Until now, published monitoring studies have been local or regional in scope, and typically of short duration. In this first major international compilation of monitoring data we answer several key questions about skyglow properties. Skyglow is observed to vary over four orders of magnitude, a range hundreds of times larger than was the case before artificial light. Nearly all of the study sites were polluted by artificial light. A non-linear relationship is observed between the sky brightness on clear and overcast nights, with a change in behavior near the rural to urban landuse transition. Overcast skies ranged from a third darker to almost 18 times brighter than clear. Clear sky radiances estimated by the World Atlas of Artificial Night Sky Brightness were found to be overestimated by ~25%; our dataset will play an important role in the calibration and ground truthing of future skyglow models. Most of the brightly lit sites darkened as the night progressed, typically by ~5% per hour. The great variation in skyglow radiance observed from site-to-site and with changing meteorological conditions underlines the need for a long-term international monitoring program