Key Determinants to using Telehealth Technology to Serve Medically Ill and Depressed Homebound Older Adults

Despite the increasing evidence for the effectiveness of telehealth technology in screening and treating chronic diseases, and comorbid depression among older adults, they have been slowly adopted by home health care (HHC) agencies. Therefore, this study aimed to identify factors that determine telehealth technology adoption. Twenty directors from the National Association for Homecare & Hospice member agencies completed a 45-min telephone interview. Questions were asked regarding their perceptions of telehealth, the key determinants of telehealth adoption and use, and recommendations they would give on telehealth adoption. The majority of the participants perceived telehealth as effective for managing symptoms and reducing cost. Meanwhile, some participants had a mixed feeling toward telehealth for depression care as they did not recognize their agency as equipped with the necessary resources and trained staff. Moreover, significant determinants of telehealth adoption included the agency-related characteristics, the patient-home environment, reimbursement and cost-related factors, and staff telehealth perception. Findings imply that there is a need for financial support both at the state and the federal levels to encourage telehealth adoption among HHC agencies. Future studies should consider exploring strategies used by successful programs to overcome barriers.     

Working together in a deficit logic: home–school partnerships with Somali diaspora parents

Drawing on discursive psychology this article examines the understandings teachers and principals in Danish Public Schools have regarding Somali diaspora parenting practices. Furthermore, the article investigates what these understandings mean in interaction with children in the classrooms and with parents in home–school communication. It is argued that in a society with increased focus on parental responsibility the teachers and principals draw on a deficit logic when dealing with Somali diaspora parents and children which consequently leads to teachers either transmitting their expertise by educating parents or compensating for perceived deficiencies in parental practices. Both these strategies result in significant marginalizing consequences where ‘difference’ is understood as ‘wrong’ or ‘inadequate’.     

The Use of Simulation to Reduce the Domain of “Black Swans” with Application to Hurricane Impacts to Power Systems

Recently, the concept of black swans has gained increased attention in the fields of risk assessment and risk management. Different types of black swans have been suggested, distinguishing between unknown unknowns (nothing in the past can convincingly point to its occurrence), unknown knowns (known to some, but not to relevant analysts), or known knowns where the probability of occurrence is judged as negligible. Traditional risk assessments have been questioned, as their standard probabilistic methods may not be capable of predicting or even identifying these rare and extreme events, thus creating a source of possible black swans. In this article, we show how a simulation model can be used to identify previously unknown potentially extreme events that if not identified and treated could occur as black swans. We show that by manipulating a verified and validated model used to predict the impacts of hazards on a system of interest, we can identify hazard conditions not previously experienced that could lead to impacts much larger than any previous level of impact. This makes these potential black swan events known and allows risk managers to more fully consider them. We demonstrate this method using a model developed to evaluate the effect of hurricanes on energy systems in the United States; we identify hurricanes with potentially extreme impacts, storms well beyond what the historic record suggests is possible in terms of impacts.     

A clarifying comparison of methods for controlling the false discovery rate

Traditional multiple hypothesis testing procedures fix an error rate and determine the corresponding rejection region. In 2002 Storey proposed a fixed rejection region procedure and showed numerically that it can gain more power than the fixed error rate procedure of Benjamini and Hochberg while controlling the same false discovery rate (FDR). In this paper it is proved that when the number of alternatives is small compared to the total number of hypotheses, Storey's method can be less powerful than that of Benjamini and Hochberg. Moreover, the two procedures are compared by setting them to produce the same FDR. The difference in power between Storey's procedure and that of Benjamini and Hochberg is near zero when the distance between the null and alternative distributions is large, but Benjamini and Hochberg's procedure becomes more powerful as the distance decreases. It is shown that modifying the Benjamini and Hochberg procedure to incorporate an estimate of the proportion of true null hypotheses as proposed by Black gives a procedure with superior power.     

Using Qualitative Methods with Poor Children in Urban Ethiopia: Opportunities &; Challenges

This paper discusses the advantages and challenges of using qualitative methods to elicit poor children’s perspectives about threats and positive influences on their wellbeing. It draws on research carried out by the author on the subjective experiences of poor children in Addis Ababa, the capital of Ethiopia in terms of their understandings of wellbeing, threats to their wellbeing, coping strategies, and positive or resilient outcomes. After a brief introduction reviewing previous approaches to child poverty in general and research on Ethiopian children in particular, the second section describes the research setting and the ethical approach to the study, which influenced how consent was obtained and the data analysed. The paper then describes the use of qualitative methods such as semi-structured interviews, draw-and-tell, and diaries, the kinds of data they produced and the methodological and ethical dilemmas and tensions encountered in using them. It concludes that despite the challenges qualitative methods are invaluable in order to understand what poor children see as threats and positive influences on their wellbeing.

Measuring Child Poverty in South Africa: Sensitivity to the Choice of Equivalence Scale and an Updated Profile

This paper offers evidence on the sensitivity of child poverty in South Africa to changes in the adult equivalence scale (AES) and updates the child poverty profile based on the Income and Expenditure Survey 2005/06. Setting the poverty line at the 40th percentile of households calculated with different AESs the scope and composition of child poverty are found to be relatively insensitive to the scale used. The rankings of children of different ages, girls versus boys, racial groupings and children living in rural versus urban areas are unaffected by choice of AES, although some provincial rankings on the poverty headcount measure are. The proportions of children and households ‘correctly’ identified as poor for the full range of scales is extremely high. These findings support the argument that it may be appropriate for profiling poverty in South Africa to use a poverty line based on a per capita welfare measure. For the construction of the child poverty profile, per capita income is used as the welfare indicator with the poverty line set at the 40th percentile of household. The profile suggests that poverty amongst children is more extensive than amongst the population or adults even after the massive injection of transfers into households with poor children through the child support grant. The child poverty headcount, depth and severity are all highest amongst children age 0–4 and lowest amongst those aged 15–17, who are not yet beneficiaries of the grants. They are also highest amongst African and Coloured children. Large variations across provinces remain. The analysis underlines the importance of prioritising children in the fight against poverty, particularly in their earliest years.     

Peer violence in foster care: a review of the research evidence

Whilst a small amount of research has been undertaken on peer violence in residential settings, very little is known about peer violence in foster care. This paper reviews the published research since 1995 about the nature and extent of peer violence in foster care and interventions for preventing and managing these negative peer interactions. The evidence indicates that young people in foster care can be the instigators and recipients of peer violence, but the limited number of studies found means that conclusions cannot be drawn about the extent of the problem. There is some evidence about the impact of this type of violence on young people and fostering households. However, there remain gaps in the evidence about the full extent of all forms of exploitation and violence that are experienced and instigated by young people in foster care, the circumstances in which it takes place, the young people affected and its co‐occurrence with other difficulties. Critically, young people's views were largely absent from included studies, an important area that requires further research.     

What is gained and what is left to be done when content analysis is added to network analysis in the study of a social movement: Twitter use during Gezi Park

As social movements relying on the weak ties found in social networks have spread around the world, researchers have taken several approaches to understanding how networks function in such instances as the Arab Spring. While social scientists have primarily relied on survey or content analysis methodology, network scientists have used social network analysis. This research combines content analysis with the automated techniques of network analysis to determine the roles played by those using Twitter to communicate during the Turkish Gezi Park uprising. Based on a network analysis of nearly 2.4 million tweets and a content analysis of a subset of 5126 of those tweets, we found that information sharing was by far the most common use of the tweets and retweets, while tweets that indicated leadership of the movement constituted a small percentage of the overall number of tweets. Using automated techniques, we experimented with coded variables from content analysis to compute the most discriminative tokens and to predict values for each variable using only textual information. We achieved 0.61 precision on identifying types of shared information. Our results on detecting the position of user in the protest and purpose of the tweets achieved 0.42 and 0.33 precision, respectively, illustrating the necessity of user cooperation and the shortcomings of automated techniques. Based on annotated values of user tweets, we computed similarities between users considering their information production and consumption. User similarities are used to compute clusters of individuals with similar behaviors, and we interpreted average activities for those groups.     

Computationally and statistically efficient model fitting techniques

A significant challenge in fitting metamodels of large-scale simulations with sufficient accuracy is in the computational time required for rigorous statistical validation. This paper addresses the statistical computation issues associated with the Bootstrap and modified PRESS statistic, which yield key metrics for error measurements in metamodelling validation. Experimentation is performed on different programming languages, namely, MATLAB, R, and Python, and implemented on different computing architectures including traditional multicore personal computers and high-power clusters with parallel computing capabilities. This study yields insight into the effect that programming languages and computing architecture have on the computational time for simulation metamodel validation. The experimentation is performed across two scenarios with varying complexity.