Principles that underpin effective school-based drug education

This study identifies the conceptual underpinnings of effective school-based drug education practice in light of contemporary research evidence and the practical experience of a broad range of drug education stakeholders. The research involved a review of the literature, a national survey of 210 Australian teachers and others involved in drug education, and structured interviews with 22 key Australian drug education policy stakeholders. The findings from this research have been distilled and presented as a list of 16 principles that underpin effective drug education. In broad terms, drug education should be evidence-based, developmentally appropriate, sequential, and contextual. Programs should be initiated before drug use commences. Strategies should be linked to goals and should incorporate harm minimization. Teaching should be interactive and use peer leaders. The role of the classroom teacher is central. Certain program content is important, as is social and resistance skills training. Community values, the social context of use, and the nature of drug harm have to be addressed. Coverage needs to be adequate and supported by follow-up. It is envisaged that these principles will provide all those involved in the drug education field with a set of up-to-date, research-based guidelines against which to reference decisions on program design, selection, implementation, and evaluation.     

Verflochtene Mobilitäten und ihr Management. Mobilitätspraktiken von Expatriate-Managern und ihren <Emphasis Type="Italic">‚trailing spouses‘</Emphasis> im Auslandseinsatz

This article analyzes forms and enabling practices of expatriate mobility, i. e. the mobility of managers and skilled professionals assigned to a foreign subsidiary of their company. We will show that (1) expatriate mobility has to be conceived of as complex entangled mobilities that add up to a hyper-mobility, and (2) that this hyper-mobility inevitably depends on the active mobility work of the expatriates’ ‘trailing spouses’. Thus, it becomes clear that the mobility management on which expatriate mobility depends is highly gendered. By focusing on the specifics of expatriate mobility, the article also opens up new theoretical perspectives for mobility research in general.     

Competent and Warm but Unemotional: The Influence of Occupational Stereotypes on the Attribution of Emotions

The present research aims to assess how occupational stereotypes, and in particular, stereotypes about doctors, influence the observers’ perception of the emotions expressed by members of this group. For this, 60 men and women judged the emotions of women who expressed either happiness, anger, sadness, or a neutral expression and whose faces were either uncovered or covered with a surgical mask, a niqab, or a hat and scarf such that only an identical portion of the face around the eyes was visible. Congruent with the occupational stereotype, women dressed as doctors were perceived highest on competence and warmth, but also as emotionally restrained such that they were rated as experiencing lower levels of emotions relative to the same women wearing other face covers or with uncovered faces.     

A note On outlier sensitivity of Sliced Inverse Regression

Sliced Inverse Regression (SIR) is a promising technique for the purpose of dimension reduction. Several properties of this method have been examined already, but little attention has been paid to robustness aspects. In this article, we focus on the sensitivity of SIR to outliers and show in what sense and how severely SIR can be influenced by outliers in the data.     

A note on contamination models and outliers

In order to describe or generate so-called outliers in univariate statistical data, contamination models are often used. These models assume that k out of n independent random variables are shifted or multiplicated by some constant, whereas the other observations still come i.i.d. from some common target distribution. Of course, these contaminants do not necessarily stick out as the extremes in the sample. Moreover, it is the amount and magnitude of ‘contamination” which determines the number of obvious outliers. Using the concept of Davies and Gather (1993) to formalize the outlier notion we quantify the amount of contamination needed to produce a prespecified expected number of ‘genuine’ outliers. In particular, we demonstrate that for sample of moderate size from a normal target distribution a rather large shift of the contaminants is necessary to yield a certain expected number of outliers. Such an insight is of interest when designing simulation studies where outliers shoulod occur as well as in theoretical investigations on outliers.     

Multivariate Real-Time Signal Extraction by a Robust Adaptive Regression Filter

We propose a new regression-based filter for extracting signals online from multivariate high frequency time series. It separates relevant signals of several variables from noise and (multivariate) outliers.

Unlike parallel univariate filters, the new procedure takes into account the local covariance structure between the single time series components. It is based on high-breakdown estimates, which makes it robust against (patches of) outliers in one or several of the components as well as against outliers with respect to the multivariate covariance structure. Moreover, the trade-off problem between bias and variance for the optimal choice of the window width is approached by choosing the size of the window adaptively, depending on the current data situation.

Furthermore, we present an advanced algorithm of our filtering procedure that includes the replacement of missing observations in real time. Thus, the new procedure can be applied in online-monitoring practice. Applications to physiological time series from intensive care show the practical effect of the proposed filtering technique.