Violence as a research object and intervention in the health field: an analysis from the production of the Research Group on Gender, Health and Nursingi

The study aimed to describe how violence is revealed in the production of the Research Group on Gender, Health and Nursing. This is a historical research of qualitative approach, which evaluated the production of the Research Group, through content analysis. The results show gender as a central category in determining violence and health practices. This aspect determines limitations on professional practices of coping, such as the invisibility of the problem. The female autonomy, the use of alcohol and drugs and social vulnerability play an important relation with the phenomenon and the bond is revealed as potentiality of health practices to address the problem. Conclusion: The gender perspective in nursing research is an innovative field and counter-hegemonic, a possibility to assume a meaning of praxis by transforming potential of understanding and modes of intervention in the phenomenon of gender violence.

Family dynamics in face of Alzheimer's in one of its members

Abstract OBJECTIVE To understand the family dynamics when there is a member in the residence with Alzheimer's disease. METHOD A study of qualitative approach, using the creative sensitive method (CSM), and with participation of two families who had a member with Alzheimer's disease at home. RESULTS Three categories emerged: Effects of Alzheimer's disease and the family dynamics; Development process of Alzheimer's disease and Coping strategies in face of the disease. CONCLUSION It was possible to know the manifestations and consequences of Alzheimer's disease in the family, such as mutual help, the mobilization of resources to activate memories of the past, spirituality and faith. There was also understanding of the structure of family dynamics.

Aitchison Geometry for Probability and Likelihood as a new approach to mathematical statistics

The Aitchison vector space structure for the simplex is generalized to a Hilbert space structure A2(P) for distributions and likelihoods on arbitrary spaces. Centralnotations of statistics, such as Information or Likelihood, can be identified in the algebraical structure of A2(P) and their corresponding notions in compositional data analysis, such as Aitchison distance or centered log ratio transform.In this way very elaborated aspects of mathematical statistics can be understoodeasily in the light of a simple vector space structure and of compositional data analysis. E.g. combination of statistical information such as Bayesian updating,combination of likelihood and robust M-estimation functions are simple additions/perturbations in A2(Pprior). Weighting observations corresponds to a weightedaddition of the corresponding evidence.Likelihood based statistics for general exponential families turns out to have aparticularly easy interpretation in terms of A2(P). Regular exponential families formfinite dimensional linear subspaces of A2(P) and they correspond to finite dimensionalsubspaces formed by their posterior in the dual information space A2(Pprior).The Aitchison norm can identified with mean Fisher information. The closing constant itself is identified with a generalization of the cummulant function and shown to be Kullback Leiblers directed information. Fisher information is the local geometry of the manifold induced by the A2(P) derivative of the Kullback Leibler information and the space A2(P) can therefore be seen as the tangential geometry of statistical inference at the distribution P.The discussion of A2(P) valued random variables, such as estimation functionsor likelihoods, give a further interpretation of Fisher information as the expected squared norm of evidence and a scale free understanding of unbiased reasoning

The psychosocial impacts caused by diagnosis and treatment of Coeliac Disease

Abstract OBJECTIVE To comprehend the psychosocial effects that Coeliac Disease diagnosis entails. METHOD Qualitative study, achieved through semi-structured interviews, analyzed in accordance to the Association of ideas map Technique. A total 12 recently-diagnosed patients from the Centro de diagnóstico, tratamento e apoio ao paciente com doença celíaca (Coeliac Disease Prevention, Support and Treatment Diagnose Centre) from the Hospital Universitário de Brasília (University Hospital of Brasilia) were enrolled for the study, between the years of 2013 and 2014. RESULTS The interviewed patients presented negative impacts in three categories: psychoaffective, family and social relationships, indicating issues with social readaptation once the treatment had started, as well as difficulty coping with a gluten free diet. CONCLUSION Coeliac Disease holds substantial impact on psychological functions, family and social relationships to diagnosed patients, requiring a clinical biopsychological assistance for better adherence to treatment and patients quality of life.

Exome Sequencing Identifies INPPL1 Mutations as a Cause of Opsismodysplasia.

Opsismodysplasia (OPS) is a severe autosomal-recessive chondrodysplasia characterized by pre- and postnatal micromelia with extremely short hands and feet. The main radiological features are severe platyspondyly, squared metacarpals, delayed skeletal ossification, and metaphyseal cupping. In order to identify mutations causing OPS, a total of 16 cases (7 terminated pregnancies and 9 postnatal cases) from 10 unrelated families were included in this study. We performed exome sequencing in three cases from three unrelated families and only one gene was found to harbor mutations in all three cases: inositol polyphosphate phosphatase-like 1 (INPPL1). Screening INPPL1 in the remaining cases identified a total of 12 distinct INPPL1 mutations in the 10 families, present at the homozygote state in 7 consanguinous families and at the compound heterozygote state in the 3 remaining families. Most mutations (6/12) resulted in premature stop codons, 2/12 were splice site, and 4/12 were missense mutations located in the catalytic domain, 5-phosphatase. INPPL1 belongs to the inositol-1,4,5-trisphosphate 5-phosphatase family, a family of signal-modulating enzymes that govern a plethora of cellular functions by regulating the levels of specific phosphoinositides. Our finding of INPPL1 mutations in OPS, a severe spondylodysplastic dysplasia with major growth plate disorganization, supports a key and specific role of this enzyme in endochondral ossification.

Strategies for sequential prediction of stationary time series

We present simple procedures for the prediction of a real valued sequence. The algorithms are based on a combinationof several simple predictors. We show that if the sequence is a realization of a bounded stationary and ergodic random process then the average of squared errors converges, almost surely, to that of the optimum, given by the Bayes predictor. We offer an analog result for the prediction of stationary gaussian processes.

The contributions of rare objects in correspondence analysis

Correspondence analysis, when used to visualize relationships in a table of counts(for example, abundance data in ecology), has been frequently criticized as being too sensitiveto objects (for example, species) that occur with very low frequency or in very few samples. Inthis statistical report we show that this criticism is generally unfounded. We demonstrate this inseveral data sets by calculating the actual contributions of rare objects to the results ofcorrespondence analysis and canonical correspondence analysis, both to the determination ofthe principal axes and to the chi-square distance. It is a fact that rare objects are oftenpositioned as outliers in correspondence analysis maps, which gives the impression that theyare highly influential, but their low weight offsets their distant positions and reduces their effecton the results. An alternative scaling of the correspondence analysis solution, the contributionbiplot, is proposed as a way of mapping the results in order to avoid the problem of outlying andlow contributing rare objects.

Compact matrix expressions for generalized Wald tests of equality of moment vectors

Asymptotic chi-squared test statistics for testing the equality ofmoment vectors are developed. The test statistics proposed aregeneralizedWald test statistics that specialize for different settings by inserting andappropriate asymptotic variance matrix of sample moments. Scaled teststatisticsare also considered for dealing with situations of non-iid sampling. Thespecializationwill be carried out for testing the equality of multinomial populations, andtheequality of variance and correlation matrices for both normal andnon-normaldata. When testing the equality of correlation matrices, a scaled versionofthe normal theory chi-squared statistic is proven to be an asymptoticallyexactchi-squared statistic in the case of elliptical data.

Negativity effect and the emergence of ideologies

``Negativity effect'' refers to the psychological phenomenon that peopletend to attach greater weight to negative information than to equallyextreme and equally likely positive information in a variety of informationprocessing tasks. Numerous studies of impression formation have found thatnegative information is weighted more heavily than positive information asimpressions of others are formed. There is empirical evidence in politicalscience that shows the importance of the negativity effect in the informationprocessing of the voters. This effect can explain the observed decreaseof popularity for a president the longer he is in office. \\We construct a dynamic model of political competition, incorporating thenegativity effect in the decision rule of the voters and allowing their preferencesto change over time, according to the past performance of the candidateswhile in office. Our model may explain the emergence of ideologies out ofthe competition for votes of myopic candidates freely choosing policypositions. This result gives rise to the formation of political parties,as infinitely--lived agents with a certain ideology. Furthermore, in thismodel some voters may start out by switching among parties associated withdifferent policies, but find themselves supporting one of the parties fromsome point on. Thus, the model describes a process by which some votersbecome identified with a ``right'' or ``left'' bloc, while others ``swing''between the two parties.

Contribution biplots

In order to interpret the biplot it is necessary to know which points usually variables are the ones that are important contributors to the solution, and this information is available separately as part of the biplot s numerical results. We propose a new scaling of the display, called the contribution biplot, which incorporates this diagnostic directly into the graphical display, showing visually the important contributors and thus facilitating the biplot interpretation and often simplifying the graphical representation considerably. The contribution biplot can be applied to a wide variety of analyses such as correspondence analysis, principal component analysis, log-ratio analysis and the graphical results of a discriminant analysis/MANOVA, in fact to any method based on the singular-value decomposition. In the contribution biplot one set of points, usually the rows of the data matrix, optimally represent the spatial positions of the cases or sample units, according to some distance measure that usually incorporates some form of standardization unless all data are comparable in scale. The other set of points, usually the columns, is represented by vectors that are related to their contributions to the low-dimensional solution. A fringe benefit is that usually only one common scale for row and column points is needed on the principal axes, thus avoiding the problem of enlarging or contracting the scale of one set of points to make the biplot legible. Furthermore, this version of the biplot also solves the problem in correspondence analysis of low-frequency categories that are located on the periphery of the map, giving the false impression that they are important, when they are in fact contributing minimally to the solution.

Robust response transformations based on optimal prediction

Nonlinear regression problems can often be reduced to linearity by transforming the response variable (e.g., using the Box-Cox family of transformations). The classic estimates of the parameter defining the transformation as well as of the regression coefficients are based on the maximum likelihood criterion, assuming homoscedastic normal errors for the transformed response. These estimates are nonrobust in the presence of outliers and can be inconsistent when the errors are nonnormal or heteroscedastic. This article proposes new robust estimates that are consistent and asymptotically normal for any unimodal and homoscedastic error distribution. For this purpose, a robust version of conditional expectation is introduced for which the prediction mean squared error is replaced with an M scale. This concept is then used to develop a nonparametric criterion to estimate the transformation parameter as well as the regression coefficients. A finite sample estimate of this criterion based on a robust version of smearing is also proposed. Monte Carlo experiments show that the new estimates compare favorably with respect to the available competitors.

Hommes et femmes: sommes-nous tous égaux face à la douleur [Are there differences between men and women with pain?].

An increasing number of articles are published on the differences about pain in men and women. These differences seem to be due to the sex, the biological dimension of the person, and to the gender, which is the role given to that person in a given social and culture environment. The pain prevalence is higher in women, its threshold and tolerance are lower. The pain interpretation, its perception and the coping is also different in men and women. Finally doctors translate and treat pain differently. This article proposes some explanations on these differences which should help us to treat this frequent and noxious symptom for the quality of life in a better way.

Évaluation de la Pensée Constructive chez les adolescents délinquants: une approche pour comprendre les réponses inadaptées au stress

Objective: This pilot study aims at assessing Constructive Thinking in a sample of adolescent offenders and in a normative sample of adolescents. Method: 66 adolescent offenders (12-18 years) were compared to 540 control adolescents on the different subscales of the "Constructive Thinking Inventory". Results and Conclusion: Adolescent offenders show a less efficient Constructive Thinking: they show cognitive styles that may hamper their ability to take appropriate decisions when facing stressful situations, increasing self-defeating behaviors. Interventions may focus on improving adequate coping with stress.

An assessment of empirical Bayes and composite estimators for small areas

We compare a set of empirical Bayes and composite estimators of the population means of the districts (small areas) of a country, and show that the natural modelling strategy of searching for a well fitting empirical Bayes model and using it for estimation of the area-level means can be inefficient.

Using composite estimators to improve both domain and total area estimation

In this article we propose using small area estimators to improve the estimatesof both the small and large area parameters. When the objective is to estimateparameters at both levels accurately, optimality is achieved by a mixed sampledesign of fixed and proportional allocations. In the mixed sample design, oncea sample size has been determined, one fraction of it is distributedproportionally among the different small areas while the rest is evenlydistributed among them. We use Monte Carlo simulations to assess theperformance of the direct estimator and two composite covariant-freesmall area estimators, for different sample sizes and different sampledistributions. Performance is measured in terms of Mean Squared Errors(MSE) of both small and large area parameters. It is found that the adoptionof small area composite estimators open the possibility of 1) reducingsample size when precision is given, or 2) improving precision for a givensample size.