Zu den Auswirkungen von Arbeitszeitmodellen im ärztlichen Dienst von Krankenhäusern

In 2004 a new working time law for physicians in hospitals was introduced, which has up until now been rarely researched in theory and is implemented in practice partially in form of new working time models, partially by relying on allowed variation rules within the law. Meanwhile, there are new discussions about changes of working time directives on the European level. This article aims to analyze the desired effects of the new working time law to decrease the workload, improve the possibilities of patient care and increase the working time satisfaction of physicians. To this end, a primary data collection is conducted in 15 hospitals and 35 hospital departments, generating 261 questionnaires, in order to empirically assess the theoretical model with the constructs working time model, workload, working time satisfaction, and possibilities of patient care using regression analyses. It can be shown that the new working time models decrease workload and enhance working time satisfaction of hospital physicians, but have no significant influence on the possibilities of patient care. These results are consistent for different ownerships and sizes of hospitals as well as for most services. No significant differences in the answers between various physician groups exist either.     

Rank covariance matrix estimation of a partially known covariance matrix

Classical multivariate methods are often based on the sample covariance matrix, which is very sensitive to outlying observations. One alternative to the covariance matrix is the affine equivariant rank covariance matrix (RCM) that has been studied in Visuri et al. [2003. Affine equivariant multivariate rank methods. J. Statist. Plann. Inference 114, 161–185]. In this article we assume that the covariance matrix is partially known and study how to estimate the corresponding RCM. We use the properties that the RCM is affine equivariant and that the RCM is proportional to the inverse of the regular covariance matrix, and hence reduce the problem of estimating the original RCM to estimating marginal rank covariance matrices. This is a great computational advantage when the dimension of the original data vector is large.     

Elicitation of Expert Judgments of Uncertainty in the Risk Assessment of Herbicide-Tolerant Oilseed Crops

One of the lay public's concerns about genetically modified (GM) organisms (GMO) and related emerging technologies is that not all the important risks are evaluated or even identified yet--and that ignorance of the unanticipated risks could lead to severe environmental or public health consequences. To some degree, even the scientists who participated in the analysis of the risks from GMOs (arguably the people most qualified to critique these analyses) share some of this concern. To formally explore the uncertainty in the risk assessment of a GM crop, we conducted detailed interviews of seven leading experts on GM oilseed crops to obtain qualitative and quantitative information on their understanding of the uncertainties associated with the risks to agriculture from GM oilseed crops (canola or rapeseed). The results of these elicitations revealed three issues of potential concern that are currently left outside the scope of risk assessments. These are (1) the potential loss of the agronomic and environmental benefits of glyphosate (a herbicide widely used in no-till agriculture) due to the combined problems of glyphosate-tolerant canola and wheat volunteer plants, (2) the growing problem of seed lot contamination, and (3) the potential market impacts. The elicitations also identified two areas where knowledge is insufficient. These are: the occurrence of hybridization between canola and wild relatives and the ability of the hybrids to perpetuate themselves in nature, and the fate of the herbicide-tolerance genes in soil and their interaction with soil microfauna and -flora. The methodological contribution of this work is a formal approach to analyzing the uncertainty surrounding complex problems.     

Small area estimation under a multivariate linear model for repeated measures data

In this article, small area estimation under a multivariate linear model for repeated measures data is considered. The proposed model aims to get a model which borrows strength both across small areas and over time. The model accounts for repeated surveys, grouped response units, and random effects variations. Estimation of model parameters is discussed within a likelihood based approach. Prediction of random effects, small area means across time points, and per group units are derived. A parametric bootstrap method is proposed for estimating the mean squared error of the predicted small area means. Results are supported by a simulation study.     

Following the River’s Flow: A Conversation about Single Session Approaches with Aboriginal Families

Alison Elliott and James Dokona were interviewed by Henry von Doussa, and this article is the written version of that interview. In it, Alison and James separately refer to issues such as early skepticism about the applicability of a single session therapy approach with Indigenous families (Alison), a growing experience of its ‘fit,' philosophically and culturally, and the hope that can be engendered in one conversation. They underline the importance of the oral tradition, and other cultural concepts such as Dadirri (deep listening) as well as the trauma-informed principles of choice, collaboration, and empowerment, through using their language, asking permission, working together on solutions, and not coming across as an expert. The article is infused with the practical ideas and the values inherent in the authors’ work, including permission-seeking, reflection, containment, and their use of a whiteboard as a resource to capture multiple perspectives, a genogram (including pets), and to facilitate yarning. The flow of this conversation in itself reflects James’ imagery of the therapeutic conversation being like a river running – you don’t know which way it’s going to go.     

Body Image Development and Sexual Satisfaction: A Prospective Study From Adolescence to Adulthood

The aim of the current study was to explore whether developmental trajectories of body satisfaction from adolescence to young adulthood predicted measures of sexual satisfaction in young adulthood, even when controlling for important covariates such as gender, weight development, relationship status, mental health, and frequency of sexual intercourse and masturbation. Data were collected from a population-based prospective cohort of Norwegian adolescents (n = 2,587) over a period of 13 years in four waves (1992, 1994, 1999, and 2005; mean age = 14.9 in 1992, 57.3% women). Latent growth curves were estimated for body satisfaction and body mass index (BMI). Men reported higher sexual satisfaction, sexual activity, baseline body satisfaction, and BMI than women. The developmental trajectories revealed a slight increase in body satisfaction and BMI from adolescence to young adulthood in both genders. Moreover, structural equation models showed that baseline body satisfaction in both genders predicted sexual satisfaction as a young adult, independent of relationship status and frequency of sexual activity. Neither the development of BMI nor of body satisfaction predicted sexual satisfaction. The results elucidate the vital role of body satisfaction in sexual satisfaction in adults and the importance of addressing body dissatisfaction in childhood.