A Risk-Benefit Analysis of French High Fish Consumption: A QALY Approach

The health risk and the nutritional benefit of a food are usually assessed separately. Toxicologists recommend limiting the consumption of certain fish because of methylmercury; while nutritionists recommend eating more oily fish because of omega 3. A common evaluation is imperative to provide coherent recommendations. In order to evaluate the risks along with the benefits related to fish consumption, a common metric based on the quality-adjusted life year (QALY) method has been used. The impact of a theoretical change from a medium n-3 PUFAs intake to a high intake is studied, in terms of the cardiovascular system (CHD mortality, stroke mortality and morbidity) and on fetal neuronal development (IQ loss or gain). This application can be considered as a sensitive analysis of the model used and looks at the impact of changing the dose-response relationships between cardiovascular diseases and n-3 PUFAs intakes. Results show that increasing fish consumption may have a beneficial impact on health. However, the confidence interval of the overall estimation has a negative lower bound, which means that this increase in fish consumption may have a negative impact due to MeHg contamination. Some limits of the QALY approach are identified. The first concerns determination of the dose-response relationships. The second concerns the economic origins of the approach and of individual preferences. Finally, since only one beneficial aspect and one risk element were studied, consideration should be given to how other beneficial and risk components may be integrated in the model.     

Internal slackening scoring methods

We deal with the ranking problem of the nodes in a directed graph. The bilateral relationships specified by a directed graph may reflect the outcomes of a sport competition, the mutual reference structure between websites, or a group preference structure over alternatives. We introduce a class of scoring methods for directed graphs, indexed by a single nonnegative parameter α. This parameter reflects the internal slackening of a node within an underlying iterative process. The class of so-called internal slackening scoring methods, denoted by λ ^α , consists of the limits of these processes. It is seen that λ⁰ extends the invariant scoring method, while λ ^∞ extends the fair bets scoring method. Method λ¹ corresponds with the existing λ-scoring method of Borm et al. (Ann Oper Res 109(1):61–75, 2002) and can be seen as a compromise between λ⁰ and λ ^∞ . In particular, an explicit proportionality relation between λ ^α and λ¹ is derived. Moreover, the internal slackening scoring methods are applied to the setting of social choice situations where they give rise to a class of social choice correspondences that refine both the Top cycle correspondence and the Uncovered set correspondence.     

Service coordination for frail elderly individuals: an analysis of case management practices in Québec

The objective of this article is to understand coordination as it unfolds in case management practices in the context of integrated care networks devoted to frail elderly individuals. More specifically, my goal is to describe practical coordination processes. I conducted a qualitative exploratory study using an embedded case study design. My research covers three Health and Social Services Centres in Québec. I observed that case management is more frequently justified by a situation in which home care is precarious than by the intensity and multidimensionality present in a situation. In such instances, case management intervenes through a standby mode.     

Structuring mental health within senior services: a case study of an outpatient mental health clinic serving latinos

The article presents a case study of an outpatient mental health clinic serving Latino older adults. The study explored staff perceptions on the clinic development and the context within an immigrant multicultural community. The study used in-depth, semistructured interviews with support staff, clinical social workers, and administrators. Interviews were analyzed using a thematic content analysis. The mental health clinic formation was perceived by staff as an ecological process stemming from the needs of the Latino immigrant senior clients. A close knit and interdependent culture allowed the clinic to adjust to diversity and changing cultural contexts.     

Bimodality based on the generalized skew-normal distribution

This paper focuses on the development of a new extension of the generalized skew-normal distribution introduced in Gómez et al. [Generalized skew-normal models: properties and inference. Statistics. 2006;40(6):495–505]. To produce the generalization a new parameter is introduced, the signal of which has the flexibility of yielding unimodal as well as bimodal distributions. We study its properties, derive a stochastic representation and state some expressions that facilitate moments derivation. Maximum likelihood is implemented via the EM algorithm which is based on the stochastic representation derived. We show that the Fisher information matrix is singular and discuss ways of getting round this problem. An illustration using real data reveals that the model can capture well special data features such as bimodality and asymmetry.     

The relative performance of ensemble methods with deep convolutional neural networks for image classification

Artificial neural networks have been successfully applied to a variety of machine learning tasks, including image recognition, semantic segmentation, and machine translation. However, few studies fully investigated ensembles of artificial neural networks. In this work, we investigated multiple widely used ensemble methods, including unweighted averaging, majority voting, the Bayes Optimal Classifier, and the (discrete) Super Learner, for image recognition tasks, with deep neural networks as candidate algorithms. We designed several experiments, with the candidate algorithms being the same network structure with different model checkpoints within a single training process, networks with same structure but trained multiple times stochastically, and networks with different structure. In addition, we further studied the overconfidence phenomenon of the neural networks, as well as its impact on the ensemble methods. Across all of our experiments, the Super Learner achieved best performance among all the ensemble methods in this study.     

Modified slashed-Rayleigh distribution

A new family of slash distributions, the modified slashed-Rayleigh distribution, is proposed and studied. This family is an extension of the ordinary Rayleigh distribution, being more flexible in terms of distributional kurtosis. It arises as a quotient of two independent random variables, one being a Rayleigh distribution in the numerator and the other a power of the exponential distribution in denominator. We present properties of the proposed family. In addition, we carry out estimation of the model parameters by moment and maximum likelihood methods. Finally, we conduct a small-scale simulation study to evaluate the performance of the maximum likelihood estimators and apply the results to a real data set, revealing its good performance.     

Experiments with truth. A sociological variation on William James's Varieties of Religious Experience

William James's Varieties of Religious Experience is a classic psycho‐philosophical study of the experience of the sacred and of its practical effects on the ordinary life of extraordinary persons. In a pragmatic variation of Kant's proof of god's existence, James uses personal accounts of converts to empirically demonstrate that there's “something” that has causal effects on the well‐being of the person. While the article is largely sympathetic to James explorations of the mystical, it offers a sociological variation on the Varieties that foregrounds the social, cultural and political aspects of religion.     

Confidence biases and learning among intuitive Bayesians

We design a double-or-quits game to compare the speed of learning one’s specific ability with the speed of rising confidence as the task gets increasingly difficult. We find that people on average learn to be overconfident faster than they learn their true ability and we present an intuitive-Bayesian model of confidence which integrates confidence biases and learning. Uncertainty about one’s true ability to perform a task in isolation can be responsible for large and stable confidence biases, namely limited discrimination, the hard–easy effect, the Dunning–Kruger effect, conservative learning from experience and the overprecision phenomenon (without underprecision) if subjects act as Bayesian learners who rely only on sequentially perceived performance cues and contrarian illusory signals induced by doubt. Moreover, these biases are likely to persist since the Bayesian aggregation of past information consolidates the accumulation of errors and the perception of contrarian illusory signals generates conservatism and under-reaction to events. Taken together, these two features may explain why intuitive Bayesians make systematically wrong predictions of their own performance.     

A Support Group for Caregivers of Children with Craniofacial Differences

ABSTRACT

Caregivers of children with craniofacial differences (CFD) experience psychosocial stressors; however, few groups are described for this population. The authors outline an eight-session group and qualitative analysis of caregivers’ experiences. The majority of participants (n = 100) were mothers (76%) of children who were female (75%) and identified as Latino (79%). Children’s mean age was 10.6 (SD = 2.8) years, and they were born with cleft lip/palate (56%) along with other CFD diagnoses. Themes included: group appreciation (21%), mutual acceptance (18%), coping (18%), parenting skills (17%), learning (9%), resiliency (7%), empathy (4%), diagnosis information (3%), and self-care (3%). Caregivers’ reported experiences largely corresponded with group goals.