Championing the interface between mental health and child protection: evaluation of a service initiative to improve joint working in northern Ireland

The importance of establishing effective inter‐agency working between adult mental health services and child care services in order to safeguard children has been repeatedly identified by research, policy, inquiries and inspection reports. This article reports on the evaluation of an initiative in one health and social care trust in Northern Ireland that aimed to facilitate joint working and so improve service provision and protection for children and families. The Champions Initiative involved identifying a Champion in each multidisciplinary community mental health team and in each family and child care team that would have responsibility for providing information, promoting joint working and identifying any obstacles to better cooperation. The evaluation of this Initiative assessed levels of experience, training, confidence, understanding and awareness in the Champions and their team members at baseline. The Champions and their Team Leaders were then followed up after six months to obtain their qualitative views of the impact of the initiative. The results include comparisons between mental health and child care staff, and crucially, views about whether the initiative has had any impact on working together. This study also generated recommendations for further service development in this complex and important area of practice. Copyright © 2010 John Wiley & Sons, Ltd.

‘Identifying a Champion in each multidisciplinary community mental health team and in each family and child care team’

Citing Literature

Number of times cited according to CrossRef: 15

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Volume 21 , Issue 3 May/June 2012

Pages 157-172     

Flexible univariate and multivariate models based on hidden truncation

A broad spectrum of flexible univariate and multivariate models can be constructed by using a hidden truncation paradigm. Such models can be viewed as being characterized by a basic marginal density, a family of conditional densities and a specified hidden truncation point, or points. The resulting class of distributions includes the basic marginal density as a special case (or as a limiting case), but also includes an array of models that may unexpectedly include many well known densities. Most of the well known skew-normal models (developed from the seed distribution popularized by Azzalini [(1985). A class of distributions which includes the normal ones. Scand. J. Statist. 12(2), 171–178]) can be viewed as being products of such a hidden truncation construction. However, the many hidden truncation models with non-normal component densities undoubtedly deserve further attention.     

Construction of bivariate and multivariate weighted distributions via conditioning

Weighted distributions (univariate and bivariate) have received widespread attention over the last two decades because of their flexibility for analyzing skewed data. In this article, we propose an alternative method to construct a new family of bivariate and multivariate weighted distributions. For illustrative purposes, some examples of the proposed method are presented. Several structural properties of the bivariate weighted distributions including marginal distributions together with distributions of the minimum and maximum, evaluation of the reliability parameter, and verification of total positivity of order two are also presented. In addition, we provide some multivariate extensions of the proposed models. A real-life data set is used to show the applicability of these bivariate weighted distributions.     

Some alternative bivariate Kumaraswamy models

In this article we discuss various strategies for constructing bivariate Kumaraswamy distributions. As alternatives to the Nadarajah et al. (2011) bivariate model, four different models are introduced utilizing a conditional specification approach, a conditional survival function approach, and an Arnold–Ng bivariate beta distribution construction approach. Distributional properties for such bivariate distributions are investigated. Parameter estimation strategies for the models are discussed, as are the consequences of fitting two of the models to a particular data set involving the proportion of foggy days at two different airports in Colombia.     

Bivariate,multivariate, and matrix variate normal characterizations: A brief survey II

The paper entitled “Bivariate and Multivariate Normal Characterizations: A Brief Survey,” by Hamedani, which was published in 1992, covered the published characterizations of bivariate and multivariate normal (MVN) distributions from 1941 to 1991. The present work is a follow-up to the 1991/1992 survey which includes not only characterizations of the bivariate and MVN distributions, but also characterizations of the matrix variate normal distribution, which have appeared from 1991/1992 to the present.     

Community change for diverse democracy

This paper presents ideas about community change for diversedemocracy. It provides perspectives on change, identifies threetypes of practice, and examines some of its elements. It drawsupon secondary literature and empirical studies of practicein various communities and concludes with observations aboutfuture work in the field, with the general conclusion that democraticsocieties, especially ones whose populations are becoming morediverse, will depend in part on their ability to both recognizedifferences and also build bridges across cultural boundaries.The paper is based on the belief that strengthening the studyof these phenomena can contribute to their practice.     

Conditional moving linear regression: Modeling the recruitment process for ALLHAT

Effective recruitment is a prerequisite for successful execution of a clinical trial. ALLHAT, a large hypertension treatment trial (N = 42,418), provided an opportunity to evaluate adaptive modeling of recruitment processes using conditional moving linear regression. Our statistical modeling of recruitment, comparing Brownian and fractional Brownian motion, indicates that fractional Brownian motion combined with moving linear regression is better than classic Brownian motion in terms of higher conditional probability of achieving a global recruitment goal in 4-week ahead projections. Further research is needed to evaluate how recruitment modeling can assist clinical trialists in planning and executing clinical trials.     

畜牧业改变气候——澳洲打响同牲畜的减排战斗

有许多众所周知的方法可以减少二氧化碳的排放,例如:减少石化燃料的使用、使用太阳能或风力等再生能源、开省油的车子或替代能源车、使用省电的电子产品,并切实做到减量、重复使用和回收等。然而,当前有关全球变暖的辩论几乎都集中在能源及交通运输方面。