What's so special about conversion disorder? A problem and a proposal for diagnostic classification.

Conversion disorder presents a problem for the revisions of DSM-IV and ICD-10, for reasons that are informative about the difficulties of psychiatric classification more generally. Giving up criteria based on psychological aetiology may be a painful sacrifice but it is still the right thing to do.

Does unemployment hurt less if there is more of it around? A panel analysis of life satisfaction in Germany and Switzerland

This paper examines the existence of a habituation effect to unemployment: Do theunemployed suffer less from job loss if unemployment is more widespread, if their ownunemployment lasts longer and if unemployment is a recurrent experience? Theunderlying idea is that unemployment hysteresis may operate through a sociologicalchannel: if many people in the community lose their job and remain unemployed over anextended period, the psychological cost of being unemployed diminishes and the pressureto accept a new job declines. We analyze this question with individual-level data from theGerman Socio-Economic Panel (1984-2009) and the Swiss Household Panel (2000-2009). We find no evidence for a mitigating effect of high surrounding unemployment onunemployed individuals' subjective well-being: Becoming unemployed hurts as muchwhen regional unemployment is high as when it is low. Likewise, the strongly harmfulimpact of being unemployed on well-being does not wear off over time, nor do repeatedepisodes of unemployment make it any better. It thus appears doubtful that anunemployment shock becomes persistent because the unemployed become used to, andhence reasonably content with, being without a job.

Enhanced compressed sensing recovery with level set normals.

We propose a compressive sensing algorithm that exploits geometric properties of images to recover images of high quality from few measurements. The image reconstruction is done by iterating the two following steps: 1) estimation of normal vectors of the image level curves, and 2) reconstruction of an image fitting the normal vectors, the compressed sensing measurements, and the sparsity constraint. The proposed technique can naturally extend to nonlocal operators and graphs to exploit the repetitive nature of textured images to recover fine detail structures. In both cases, the problem is reduced to a series of convex minimization problems that can be efficiently solved with a combination of variable splitting and augmented Lagrangian methods, leading to fast and easy-to-code algorithms. Extended experiments show a clear improvement over related state-of-the-art algorithms in the quality of the reconstructed images and the robustness of the proposed method to noise, different kind of images, and reduced measurements.

Learning about Bayesian networks for forensic interpretation : An example based on the "the problem of multiple propositions"

Both, Bayesian networks and probabilistic evaluation are gaining more and more widespread use within many professional branches, including forensic science. Notwithstanding, they constitute subtle topics with definitional details that require careful study. While many sophisticated developments of probabilistic approaches to evaluation of forensic findings may readily be found in published literature, there remains a gap with respect to writings that focus on foundational aspects and on how these may be acquired by interested scientists new to these topics. This paper takes this as a starting point to report on the learning about Bayesian networks for likelihood ratio based, probabilistic inference procedures in a class of master students in forensic science. The presentation uses an example that relies on a casework scenario drawn from published literature, involving a questioned signature. A complicating aspect of that case study - proposed to students in a teaching scenario - is due to the need of considering multiple competing propositions, which is an outset that may not readily be approached within a likelihood ratio based framework without drawing attention to some additional technical details. Using generic Bayesian networks fragments from existing literature on the topic, course participants were able to track the probabilistic underpinnings of the proposed scenario correctly both in terms of likelihood ratios and of posterior probabilities. In addition, further study of the example by students allowed them to derive an alternative Bayesian network structure with a computational output that is equivalent to existing probabilistic solutions. This practical experience underlines the potential of Bayesian networks to support and clarify foundational principles of probabilistic procedures for forensic evaluation.

Constitution, Diversification and Normalisation of a Health Problem: Organising the Fight against AIDS in Switzerland (1984-2005)

The article traces the formation, diversification and normalization of the AIDS cause in Switzerland. Particular emphasis is placed on interactions between the medical field, public authorities and associative space, the latter being understood as the place where individual and collective actors compete to define the cause. The authors argue that the major phases in the structuring of the struggle, the pace of state intervention and the creation of a multi-organizational field, can only be understood if one adopts a 'configurational perspective' attentive to the manner in which, in a given context and under the effect of particular constraints, key actors strategically interact and contribute to transforming their environment and their chances of reaching their goals. This approach takes into account the changing socio-biological characteristics of those who have committed themselves to the cause. In turn, internal movement divisions about how to respond to the epidemic as well as the changing perceptions of the disease have modified the opportunities for commitment, encouraging certain individual kinds of people and excluding others.

A satisfaction survey conducted on patients of a medico-legal consultation.

In 2006, a medico-legal consultation service devoted to adult victims of interpersonal violence was set up at the Lausanne University Hospital Centre, Switzerland: the Violence Medical Unit. Patients are received by forensic nurses for support, forensic examination (in order to establish medical report) and community orientation. In 2008, a telephone survey was conducted on patients. The objectives of the survey were to estimate the degree of patients' satisfaction and to document the use of the medical report by six questions. Among the 476 patients admitted to the VMU in 2007, 132 were interviewed. Their overall satisfaction was high with an average mark of 8.7/10. The medical report was used extensively by the interviewed victims (81%) for its primary function - to be produced as evidence. As the consultations are financed by public funds, these results were of interest for advocacy of long-lasting financial support.

Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.

Ulnar Nerve Transposition at the Elbow under Local Anesthesia: A Patient Satisfaction Study.

Background Ulnar nerve decompression at the elbow traditionally requires regional or general anesthesia. We wished to assess the feasibility of performing ulnar nerve decompression and transposition at the elbow under local anesthesia. Methods We examined retrospectively the charts of 50 consecutive patients having undergone ulnar nerve entrapment surgery either under general or local anesthesia. Patients were asked to estimate pain on postoperative days 1 and 7 and satisfaction was assessed at 1 year. Results On day 1, pain was comparable among all groups. On day 7, pain scores were twice as high when transposition was performed under general anesthesia when compared with local anesthesia. Patient satisfaction was slightly increased in the local anesthesia group. These patients were significantly more willing to repeat the surgery. Conclusion Ulnar nerve decompression and transposition at the elbow can be performed under local anesthesia without added morbidity when compared with general anesthesia.