Self-esteem and self-concept as correlates of life satisfaction and attitudes toward school among Ghanaian girls

During adolescence, youth experience several physical, psychosocial, and cognitive changes. Self-esteem and self-concept are identified as protective factors for adolescents in high-income countries, but studies are limited in sub-Saharan Africa. We examined the associations of self-esteem and self-concept with life satisfaction and attitudes toward school using baseline data from 97 Ghanaian adolescent girls at risk of school dropout. Ordinary Least Squares regression models were fitted to examine the association between self-esteem and self-concept on school attitudes and life satisfaction. Self-esteem was positively associated with life satisfaction. Self-concept was associated with more positive attitudes toward school. Hence, self-esteem and self-concept may be critical protective factors in promoting adolescent girls' life satisfaction and positive attitudes toward school.     

Perceived Racial Discrimination in Health Care and Race Differences in Physician Trust

Racial discrimination in health care is more often perceived by racial minority patients than by whites. In this study, we explored whether two types of perceived racial discrimination, perceptions that the healthcare system is racially biased in general (perceived institutional racial discrimination) and perceptions that one has personally encountered racial discrimination while seeking health care (perceived interpersonal racial discrimination), mediated racial differences in patients’ trust in physicians. We examined this in a sample of black (N = 127) and white (N = 303) patients being treated in two Veterans Affairs orthopedic clinics for advanced osteoarthritis. Patients completed measures of perceived institutional and interpersonal racial discrimination in health care before meeting with an orthopedic surgeon and a measure of physician trust after the visit. Using a multiple mediator bootstrapping procedure, we tested whether perceived institutional and/or interpersonal racial discrimination mediated the association between race and trust. Compared to whites, blacks reported lower physician trust (M = 4.00 vs. 4.17, β = ?0.15, 95 % CI = ?0.25, ?0.05), more perceived institutional racial discrimination (M = 3.13 vs. 2.60, β = 0.43, 95 % CI = 0.25, 0.61), and more perceived interpersonal racial discrimination (M = 1.94 vs. 1.21, β = 0.60, 95 % CI = 0.47, 0.74). Perceived interpersonal, but not institutional, racial discrimination mediated the race difference in physician trust and accounted for 55 % of the variance. Our finding that lower physician trust among black patients than white patients was explained by perceptions of interpersonal racial discrimination in health care suggests that issues of racial discrimination may need to be addressed in order to foster minority patients’ trust in physicians.     

Cure rate models: A unified approach

The authors propose a novel class of cure rate models for right‐censored failure time data. The class is formulated through a transformation on the unknown population survival function. It includes the mixture cure model and the promotion time cure model as two special cases. The authors propose a general form of the covariate structure which automatically satisfies an inherent parameter constraint and includes the corresponding binomial and exponential covariate structures in the two main formulations of cure models. The proposed class provides a natural link between the mixture and the promotion time cure models, and it offers a wide variety of new modelling structures as well. Within the Bayesian paradigm, a Markov chain Monte Carlo computational scheme is implemented for sampling from the full conditional distributions of the parameters. Model selection is based on the conditional predictive ordinate criterion. The use of the new class of models is illustrated with a set of real data involving a melanoma clinical trial.     

Academic Buildings and Their Influence on Students’ Wellbeing in Higher Education Institutions

The purpose of this study is to explore the perception of students about aspects of academic building that affect their wellbeing. The study adopts focus group discussion using semi structured interview guide to elicit their responses. Six different groups of students participated in the study. Interviews were recorded using digital audio recorder and were later transcribed to text. The qualitative data obtained was analysed through content analysis. Six key themes that emerged from the analysis are: comfort; health and safety; access and quality of facilities; space provision and adequacy; participation and inclusiveness; interaction. These six items are considered as parameters that are important to students’ wellbeing in relation to academic buildings. The most emphasised aspects of academic building that are essential to meeting students need include thermal conditions, internet access, furniture, duration of access, availability of refreshment facilities, availability of discussion room and availability of personal workstation. This implies that facilities managers in higher education institutions should give adequate attention to these identified aspects of academic buildings as they can potentially affect students output.     

Semiparametric Estimation with Profile Algorithm for Longitudinal Binary Data

This article considers analyzing longitudinal binary data semiparametrically and proposing GEE-Smoothing spline in the estimation of parametric and nonparametric components. The method is an extension of the parametric generalized estimating equation to semiparametric. The nonparametric component is estimated by smoothing spline approach, i.e., natural cubic spline. We use profile algorithm in the estimation of both parametric and nonparametric components. Properties of the estimators are evaluated by simulation.     

Outlier Detection in a Circular Regression Model Using COVRATIO Statistic

In this article, we model the relationship between two circular variables using the circular regression models, to be called JS circular regression model, which was proposed by Jammalamadaka and Sarma (1993). The model has many interesting properties and is sensitive enough to detect the occurrence of outliers. We focus our attention on the problem of identifying outliers in this model. In particular, we extend the use of the COVRATIO statistic, which has been successfully used in the linear case for the same purpose, to the JS circular regression model via a row deletion approach. Through simulation studies, the cut-off points for the new procedure are obtained and its power of performance is investigated. It is found that the performance improves when the resulting residuals have small variance and when the sample size gets larger. An example of the application of the procedure is presented using a real dataset.     

On Bayesian Inference for Proportional Hazards Models Using Noninformative Priors

In this article, we investigate the propertiesof the posterior distribution under the uniform improper priorfor two commonly used proportional hazards models; the Weibullregression model and the extreme value regression model. We allowthe observations to be right censored. We obtain sufficient conditionsfor the existence of the posterior moment generating functionof the regression coefficients. A dataset involving a lung cancerclinical trial and a simulation are presented to illustrate ourresults.     

Models for survival data from cancer prevention studies

Summary. We propose a new parametric survival model for cancer prevention studies. The formulation of the model is in the spirit of stochastic modelling of the occurrences of tumours through two stages: initiation of an undetected tumour and promotion of the tumour to a detectable cancer. Several novel properties of the model proposed are derived. In addition, we examine the relationship of our model with the existing lagged regression model of Zucker and Lakatos. Also, we bridge the difference between two distinct stochastic modelling methods for cancer data, one used primarily for cancer therapeutic trials and the other used for cancer prevention trials.     

Contamination,deception and ‘othering’: the media framing of the horsemeat scandal

Food and consumption practices are cultural symbols of communities, nations, identity and a collective imaginary which bind people in complex ways. The media framed the 2013 horsemeat scandal by fusing discourses beyond the politics of food. Three recurrent media frames and dominant discourses converged with wider political debates and cultural stereotypes in circulation in the media around immigration and intertextual discourse on historical food scandals. What this reveals is how food consumption and food-related scandals give rise to affective media debates and frames which invoke fear of the other and the transgression of a sacred British identity, often juxtaposing ‘Britishness’ with a constructed ‘Otherness’.