Loss functions for estimation of extrema with an application to disease mapping

It is often of interest to find the maximum or near maxima among a set of vector‐valued parameters in a statistical model; in the case of disease mapping, for example, these correspond to relative‐risk “hotspots” where public‐health intervention may be needed. The general problem is one of estimating nonlinear functions of the ensemble of relative risks, but biased estimates result if posterior means are simply substituted into these nonlinear functions. The authors obtain better estimates of extrema from a new, weighted ranks squared error loss function. The derivation of these Bayes estimators assumes a hidden‐Markov random‐field model for relative risks, and their behaviour is illustrated with real and simulated data.     

Connecting and Strengthening Young Aboriginal Men: A Family Wellbeing Pilot Study

A significant proportion of young people in Australia are currently not being engaged in school and other social systems. This article presents the results of a mixed-methods study of a pilot Family Wellbeing intervention designed to enhance the social and emotional wellbeing (SEWB) of young Aboriginal men and improve engagement in education, employment, and other social participation. A questionnaire incorporating the Kessler Psychological Distress Scale and respondent self-assessment SEWB questions was administered to program participants pre and post intervention (N = 30) and qualitative data were collected from program organisers (N = 6). The results suggest that the Family Wellbeing intervention has the capacity to make a marked contribution to the SEWB of young Aboriginal men; participants experienced strong improvement in capacity to manage relationships, engagement in education and employment, and mental and physical health. The factors that enabled the program to be adapted to the target group and setting are documented.     

Predictive Inference for Big,Spatial, Non‐Gaussian Data: MODIS Cloud Data and its Change‐of‐Support

Remote sensing of the earth with satellites yields datasets that can be massive in size, nonstationary in space, and non‐Gaussian in distribution. To overcome computational challenges, we use the reduced‐rank spatial random effects (SRE) model in a statistical analysis of cloud‐mask data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board NASA's Terra satellite. Parameterisations of cloud processes are the biggest source of uncertainty and sensitivity in different climate models’ future projections of Earth's climate. An accurate quantification of the spatial distribution of clouds, as well as a rigorously estimated pixel‐scale clear‐sky‐probability process, is needed to establish reliable estimates of cloud‐distributional changes and trends caused by climate change. Here we give a hierarchical spatial‐statistical modelling approach for a very large spatial dataset of 2.75 million pixels, corresponding to a granule of MODIS cloud‐mask data, and we use spatial change‐of‐Support relationships to estimate cloud fraction at coarser resolutions. Our model is non‐Gaussian; it postulates a hidden process for the clear‐sky probability that makes use of the SRE model, EM‐estimation, and optimal (empirical Bayes) spatial prediction of the clear‐sky‐probability process. Measures of prediction uncertainty are also given.     

Injunctive Norms and Problem Gambling among College Students

Two studies examined the relationships among injunctive norms and college student gambling. In study 1 we evaluated the accuracy of perceptions of other students’ approval of gambling and the relationship between perceived approval and gambling behavior. In study 2 we evaluated gambling behavior as a function of perceptions of approval of other students, friends, and family. In study 1, which included 2524 college students, perceptions of other students’ approval of gambling were found to be overestimated and were negatively associated with gambling behavior. The results of study 2, which included 565 college students, replicated the findings of study 1 and revealed positive associations between gambling behavior and perceived approval of friends and family. Results highlight the complexity of injunctive norms and the importance of considering the reference group (e.g., peers, friends, family members) in their evaluation. Results also encourage caution in considering the incorporation of injunctive norms in prevention and intervention approaches.     

Extending Bayesian back-calculation to estimate age and time specific HIV incidence

Lifetime Data Analysis - CD4-based multi-state back-calculation methods are key for monitoring the HIV epidemic, providing estimates of HIV incidence and diagnosis rates by disentangling their...     

Using the Shapley Decomposition to Disentangle the Impact of Circumstances and Efforts on Health Inequality

Following previous work on inequality in health opportunity, this paper attempts to determine the contribution of circumstances, efforts and lifestyle, and demographic variables to the overall inequality in health in Luxembourg. Health is measured via the answers given to a question on self-assessed health and is considered as an ordinal variable. The educational level of each parent, the financial situation of the family during childhood, the area of birth of the individual, and of his/her parents, and the year of immigration are considered as circumstances. Effort and lifestyle variables are proxied by information on the educational level of the individual, whether he/she smoked and whether he/she had a physical activity on a regular basis. Sex and age are considered as demographic variables. To solve the issue of correlation between circumstances and effort and lifestyle the estimation is implemented in two stages. In the first stage, each effort and lifestyle variable is regressed in a separate equation against the vector of circumstances and demographic variables and, in a second stage, the individual health status is regressed against the vector of circumstances and demographic variables along with the estimated residuals of the effort equations described previously. The respective impacts of the three categories of explanatory variables (circumstances, effort and lifestyle and demographic variables) on health inequality are derived via a Shapley decomposition of the likelihood ratio of the health ordered logit regression. It appears that differences in circumstances and effort and lifestyle explain each around a quarter of this likelihood ratio.     

A Framework for Enabling Evidence-based Practice in Allied Health

Evidence-based practice (EBP) is upheld as best practice in health and human services but there is a need for more research on how this approach can be enabled in day-to-day practice. This qualitative study examined EBP with allied health managers and practitioners in a health service network (n = 17). The findings highlight the systemic nature of EBP and the extent to which it involves both individual and environmental attributes. Individual attributes include clear understanding of EBP, relevant knowledge and skills, and motivation and passion. Environmental attributes are the presence of an organisational culture that values and prioritises EBP and an integrated mix of research support services, professional development activities, supervision and mentorship, and university partnerships. Theoretical frameworks can be useful for making sense of complex processes, planning, and evaluating change. Therefore, the findings are presented as a framework incorporating reflective questions relating to the elements identified as enabling EBP.     

It Takes Two to Fight in School,Too: A Social Relations Model of the Psychometric Properties and Relative Variance of Dyadic Aggression and Victimization in Middle School

Aggressive behavior has been well studied in terms of interindividual differences among aggressors and victims, but has been understudied, especially within naturalistic contexts, in terms of aggressor–victim relationships. The social relations model (SRM) is a powerful conceptual and analytic tool for studying dyadic phenomena, and we describe the use of multivariate SRM to study aggression. Boys and girls (N = 210) in middle schools (sixth and seventh grades) completed a newly created dyadic aggression and victimization inventory (DAVI). Results support the reliability and validity of the DAVI in assessing inter‐individual and inter‐dyadic differences in aggression and victimization. Occurrences of aggression were accounted for primarily by inter‐dyadic variability, indicating the importance of considering aggressor–victim relationships. We discuss the implications of this relationship focus for future research and intervention efforts.     

Cognitive-behavioral treatment for adolescents who sexually offend and their families: individual and family applications in a collaborative outpatient program

This article describes an outpatient treatment program for adolescent sexual abusers that was established by a mental health agency in collaboration with a specialized probation program in the juvenile court. Individualized treatment is based on a comprehensive clinical assessment with the youth and guardian, for which examples are provided. Given the heterogeneity of this population, we describe several treatment strategies directed to various individual or family clinical targets, including psychiatric disorders, sexual deviance and sexuality, normal adolescent development and adaptive skills, and parent and family relationships. Ongoing collaborative and coordination issues are also reviewed. The integration of mental health and probationary services provides a balanced approach to the community management and treatment of the low-risk, primarily first-time, adolescent sexual offender.     

Forecasting: A hybrid approach

It has recently been shown that the Box-Jenkins approach to forecasting time series is superior to an econometric approach over a relatively short horizon. The results here support this contention. A combination of the two approaches, however, proves to be clearly superior to either one separately. By taking account of changes in economic and weather related variables in a time series model, improved forecasts are obtained.