Experiencing breast cancer in the context of mental illness in New Zealand

ABSTRACT

This study aimed to explore the experiences of women with mental illness who had also experienced breast cancer diagnosis and treatment, in particular, to identify barriers and facilitators to cancer treatment. Semi-structured interviews were conducted with ten breast cancer survivors who had had contact with secondary mental health services prior to their cancer diagnosis. Thematic analysis was used to identify key themes. Participants described positive experiences of cancer treatment, expressing surprise at both how well they coped with diagnosis and treatment and how well they were treated by services. Many contrasted this with their less positive experience of mental illness and mental health services. The women interviewed were active participants in their cancer treatment and did not report feeling stigmatised because of their mental health experiences. A lack of connection between cancer and mental health services was described, but this was not regarded as necessarily a bad thing. This study begins to counter the stereotypes of the difficult patient or the person unable to understand and cooperate in their own care which are prevalent in the literature. Further work is needed to understand the reasons for disparities in cancer outcomes.     

On variable bandwidth selection in local polynomial regression

The performances of data-driven bandwidth selection procedures in local polynomial regression are investigated by using asymptotic methods and simulation. The bandwidth selection procedures considered are based on minimizing 'prelimit' approximations to the (conditional) mean-squared error (MSE) when the MSE is considered as a function of the bandwidth h . We first consider approximations to the MSE that are based on Taylor expansions around h=0 of the bias part of the MSE. These approximations lead to estimators of the MSE that are accurate only for small bandwidths h . We also consider a bias estimator which instead of using small h approximations to bias naïvely estimates bias as the difference of two local polynomial estimators of different order and we show that this estimator performs well only for moderate to large h . We next define a hybrid bias estimator which equals the Taylor-expansion-based estimator for small h and the difference estimator for moderate to large h . We find that the MSE estimator based on this hybrid bias estimator leads to a bandwidth selection procedure with good asymptotic and, for our Monte Carlo examples, finite sample properties.     

试论近代西北地区的鸦片烟毒问题

鸦片泛滥曾是近代西北地区的一个非常严重的社会问题。西北的鸦片问题起源于英、俄等国不法商人的走 私,后因清王朝、国民党政府的放纵和谋利而兴盛。加之地方军闽、官僚的穷兵黩武和贪得无厌,甚至逼民种鸦片, 武装贩运,致使鸦片种植达到了惊人的地步。大量的鸦片生产使西北的城乡经济走向畸形,加速了农村经济的破 产,并造成了一幕幕的人间悲剧。     

Union Transitions Following the Birth of a Child to Cohabiting Parents

Despite a growing interest in the family trajectories of unmarried women, there has been limited research on union transitions among cohabiting parents. Using data from the 2002 National Survey of Family Growth, we examined how family complexity (including relationship and fertility histories), as well as characteristics of the union and birth, were associated with transitions to marriage or to separation among 1,105 women who had a birth in a cohabiting relationship. Cohabiting parents had complex relationship and fertility histories, which were tied to union transitions. Having a previous nonmarital birth was associated with a lower relative risk of marriage and a greater risk of separation. In contrast, a prior marriage or marital birth was linked to union stability (getting married or remaining cohabiting). Characteristics of the union and birth were also important. Important racial/ethnic differences emerged in the analyses. Black parents had the most complex family histories and the lowest relative risk of transitioning to marriage. Stable cohabitations were more common among Hispanic mothers, and measures of family complexity were particularly important to their relative risk of marriage. White mothers who began cohabiting after conception were the most likely to marry, suggesting that “shot-gun cohabitations” serve as a stepping-stone to marriage.     

A Bayesian Approach for Multiple Response Surface Optimization in the Presence of Noise Variables

An approach for the multiple response robust parameter design problem based on a methodology by Peterson (2000) is presented. The approach is Bayesian, and consists of maximizing the posterior predictive probability that the process satisfies a set of constraints on the responses. In order to find a solution robust to variation in the noise variables, the predictive density is integrated not only with respect to the response variables but also with respect to the assumed distribution of the noise variables. The maximization problem involves repeated Monte Carlo integrations, and two different methods to solve it are evaluated. A Matlab code was written that rapidly finds an optimal (robust) solution in case it exists. Two examples taken from the literature are used to illustrate the proposed method.     

Statistical Modelling of Brain Morphological Measures Within Family Pedigrees

Large, family-based imaging studies can provide a better understanding of the interactions of environmental and genetic influences on brain structure and function. The interpretation of imaging data from large family studies, however, has been hindered by the paucity of well-developed statistical tools for that permit the analysis of complex imaging data together with behavioral and clinical data. In this paper, we propose to use two methods for these analyses. First, a variance components model along with score statistics is used to test linear hypotheses of unknown parameters, such as the associations of brain measures (e.g., cortical and subcortical surfaces) with their potential genetic determinants. Second, we develop a test procedure based on a resampling method to assess simultaneously the statistical significance of linear hypotheses across the entire brain. The value of these methods lies in their computational simplicity and in their applicability to a wide range of imaging data. Simulation studies show that our test procedure can accurately control the family-wise error rate. We apply our methods to the detection of statistical significance of gender-by-age interactions and of the effects of genetic variation on the thickness of the cerebral cortex in a family study of major depressive disorder.     

Working with parents of disturbed adolescents: a multifaceted group approach

Experience with this parents' group model suggests that there are a number of advantages in using a multifaceted approach when working with parents of severely disturbed adolescents. Basic support and reduction of guilt and blaming are derived from the therapeutic aspect of the group process. This is augmented by having the parents in a leadership role, in the manner of a self-help group. Bringing in educational and advocacy elements allows the group to respond directly to the parents' need for detailed, accurate information about the disorders and treatment resources for dealing with them. This approach is not designed to replace family therapy, but to provide resources and support to parents. Future research will be necessary to substantiate the clinical impression that the group is quite helpful to parents and to elucidate all the factors producing success.