Mixed results in a transitional planning program for alternative school students

Disciplinary alternative schools have a reputation as gateways to the juvenile and criminal justice systems. The authors conducted an evaluation of an intervention (Strategies for Success) designed to divert seventh-, eighth-, and ninth-grade alternative school students from this gateway. They used propensity score matching and a multivariate random effects model to estimate program impacts and found that the program not only increased attendance rates, at least in the short term, but also increased the likelihood of reassignment to alternative schools. The discussion focuses on possible reasons and solutions for high rates of return to alternative school and for the erosion of program effects.     

Are Informal Connections a Functional Alternative to Associational Life in Enhancing Social Cohesion? Findings from Hong Kong

This article aims to ascertain whether organizational life and informal connections, which made up part of Putnam’s (Bowling alone: the collapse and revival of American community. Simon & Schuster, New York, 2000) Social Capital Index, have separate effects on social cohesion. Postulating that informal gatherings with family and friends might be a functional alternative to associational life, we employed multiple regression analysis to test the hypothesis. The analysis was based on a 2011 territory-wide door-to-door survey in Hong Kong. Controlling for the effects of demographic variables including gender, age, educational level, and employment status, it was found that formal participation in organizations contributed significantly to the explanation in five of the eight subindexes of social cohesion. In contrast, informal connections contributed significantly only to one subindex. The pattern persisted when attitudinal variables such as life satisfaction, social support, and perceived social class were added to the regression analysis. In short, our analysis demonstrated that participation in formal organizations fosters various aspects of social cohesion, and that this effect cannot be replaced by informal gatherings with family and friends.     

Childbearing traditions of Indian women at home and abroad: An integrative literature review

BackgroundThe percentage of overseas-born mothers giving birth in Australia has increased to 31.5% in 2012 and Indian women represent 10% (the highest proportion). It is important for midwives in Australia to be aware of the childbearing traditions of Indian women and how these influence Indian women birthing in Australia.AimTo explore childbearing practices in India and Indian women's experience of giving birth abroad; and to discuss the relevant findings for midwives working with Indian women in Australia.MethodAn integrative literature review was employed. 32 items, including 18 original research articles were thematically reviewed to identify commonly occurring themes relating to Indian women's childbearing traditions.FindingsFive themes relating to traditional childbearing practices of women birthing in India were identified. These themes included diversity and disparity; social context of childbirth and marriage; diet based on Ayurveda; pollution theory and confinement; and finally, rituals and customs.ConclusionIndian women giving birth abroad and by implication in Australia experience a transition to motherhood in a new culture. While adjusting to motherhood, they are also negotiating between their old and new cultural identities. To provide culturally safe care, it is essential that midwives reflect on their own culture while exploring what traditions are important for Indian women.     

Young People, Risk Taking and Risk Making: Some Thoughts for Social Work

Policy makers, professionals and the public have become increasinglyconcerned with identifying and managing young people who arenot only troubled or at risk, but troubling or risky. Socialwork, however, has been relatively silent on the subject. Insocial work practice, young people have become largely ‘someoneelse’s problem’; in the academy, relatively littlecritical attention has been given to their risk taking, or tothe way we ‘make’ or construct it. This paper takesan exploratory rather than systematically comprehensive journey,across a range of discursive terrains, to open up the debate.Examining current concerns with youth and risk, it exploressome of the social and psychological theory bases whereby youthis constructed as a risky business. Drawing on empirical researchfrom several disciplines, it examines patterns and dynamicsof young people’s risk taking, and explores concepts ofrisk culture and cultural learning, identity capital and Bourdieu’snotion of ‘habitus’, to frame these. The discussionhighlights the need for critically reflective social work tounderstand the complex interplay of identity and agency, structure,culture and context that underpins young people’s risktaking. It encourages us to scrutinize our judgements of whatis acceptable or unacceptable riskiness, what within and whatbeyond the pale.     

Adjusting overall survival for treatment switches: commonly used methods and practical application

In parallel group trials, long‐term efficacy endpoints may be affected if some patients switch or cross over to the alternative treatment arm prior to the event. In oncology trials, switch to the experimental treatment can occur in the control arm following disease progression and potentially impact overall survival. It may be a clinically relevant question to estimate the efficacy that would have been observed if no patients had switched, for example, to estimate ‘real‐life’ clinical effectiveness for a health technology assessment. Several commonly used statistical methods are available that try to adjust time‐to‐event data to account for treatment switching, ranging from naive exclusion and censoring approaches to more complex inverse probability of censoring weighting and rank‐preserving structural failure time models. These are described, along with their key assumptions, strengths, and limitations. Best practice guidance is provided for both trial design and analysis when switching is anticipated. Available statistical software is summarized, and examples are provided of the application of these methods in health technology assessments of oncology trials. Key considerations include having a clearly articulated rationale and research question and a well‐designed trial with sufficient good quality data collection to enable robust statistical analysis. No analysis method is universally suitable in all situations, and each makes strong untestable assumptions. There is a need for further research into new or improved techniques. This information should aid statisticians and their colleagues to improve the design and analysis of clinical trials where treatment switch is anticipated. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimating Transition Probabilities for Ignorable Intermittent Missing Data in a Discrete-Time Markov Chain

This article considers a discrete-time Markov chain for modeling transition probabilities when multiple successive observations are missing at random between two observed outcomes using three methods: a na\"?ve analog of complete-case analysis using the observed one-step transitions alone, a non data-augmentation method (NL) by solving nonlinear equations, and a data-augmentation method, the Expectation-Maximization (EM) algorithm. The explicit form of the conditional log-likelihood given the observed information as required by the E step is provided, and the iterative formula in the M step is expressed in a closed form. An empirical study was performed to examine the accuracy and precision of the estimates obtained in the three methods under ignorable missing mechanisms of missing completely at random and missing at random. A dataset from the mental health arena was used for illustration. It was found that both data-augmentation and nonaugmentation methods provide accurate and precise point estimation, and that the na\"?ve method resulted in estimates of the transition probabilities with similar bias but larger MSE. The NL method and the EM algorithm in general provide similar results whereas the latter provides conditional expected row margins leading to smaller standard errors.     

Business intelligence and analytics value creation in Industry 4.0: a multiple case study in manufacturing medium enterprises

Abstract

Medium enterprises (MEs) form a majority of enterprises in several regions, yet they are underrepresented in the literature. The digital transformation known as Industry 4.0 (I4.0) brings new data streams into enterprises. MEs and large enterprises will both leverage business intelligence and analytics (BI&A) to improve their business performance, so the study of the conditions favouring value creation of BI&A is of interest. However, there are few studies focusing on the impact of business intelligence and analytics (BI&A) on value creation in I4.0 and none focusing on MEs. Using a multiple case-study design, this paper explores factors linked to BI&A business value creation in manufacturing MEs that are undergoing an I4.0 transformation. Findings suggest enterprises resources and capabilities are not sufficient to predict business value: organizational learning and organizational culture have a non-negligible influence for MEs.