Using Technology to Facilitate Collaboration in Community-Based Participatory Research (CBPR)

This study explores the use of Computer-Supported Collaborative Work (CSCW) technologies, by way of a computer-based system called iCohere. This system was used to facilitate collaboration conducting Community-Based Participatory Research (CBPR). Data was gathered from 13 members of a Community Collaborative Board (CCB). Analysis revealed that iCohere served the following functions: facilitating communication, providing a depository for information and resource sharing, and allowing for remote meeting attendance. Results indicated that while iCohere was useful in performing these functions, less expensive technologies had the potential to achieve similar goals if properly implemented. Implications for future research on CSCW systems and CBPR are discussed.     

Bayesian adjustment for unidirectional misclassification in ordinal covariates

In this paper, we study the identification of Bayesian regression models, when an ordinal covariate is subject to unidirectional misclassification. Xia and Gustafson [Bayesian regression models adjusting for unidirectional covariate misclassification. Can J Stat. 2016;44(2):198–218] obtained model identifiability for non-binary regression models, when there is a binary covariate subject to unidirectional misclassification. In the current paper, we establish the moment identifiability of regression models for misclassified ordinal covariates with more than two categories, based on forms of observable moments. Computational studies are conducted that confirm the theoretical results. We apply the method to two datasets, one from the Medical Expenditure Panel Survey (MEPS), and the other from Translational Research Investigating Underlying Disparities in Acute Myocardial infarction Patients Health Status (TRIUMPH).     

An Assessment of Change in Risk Perception and Optimistic Bias for Hurricanes Among Gulf Coast Residents

This study focuses on levels of concern for hurricanes among individuals living along the Gulf Coast during the quiescent two‐year period following the exceptionally destructive 2005 hurricane season. A small study of risk perception and optimistic bias was conducted immediately following Hurricanes Katrina and Rita. Two years later, a follow‐up was done in which respondents were recontacted. This provided an opportunity to examine changes, and potential causal ordering, in risk perception and optimistic bias. The analysis uses 201 panel respondents who were matched across the two mail surveys. Measures included hurricane risk perception, optimistic bias for hurricane evacuation, past hurricane experience, and a small set of demographic variables (age, sex, income, and education). Paired t‐tests were used to compare scores across time. Hurricane risk perception declined and optimistic bias increased. Cross‐lagged correlations were used to test the potential causal ordering between risk perception and optimistic bias, with a weak effect suggesting the former affects the latter. Additional cross‐lagged analysis using structural equation modeling was used to look more closely at the components of optimistic bias (risk to self vs. risk to others). A significant and stronger potentially causal effect from risk perception to optimistic bias was found. Analysis of the experience and demographic variables’ effects on risk perception and optimistic bias, and their change, provided mixed results. The lessening of risk perception and increase in optimistic bias over the period of quiescence suggest that risk communicators and emergency managers should direct attention toward reversing these trends to increase disaster preparedness.     

Ambulance allocation for maximal survival with heterogeneous outcome measures

This paper proposes new models for locating emergency medical services (EMS) by incorporating survival functions for capturing multiple-classes of heterogeneous patients. The Maximal Expected Survival Location Model for Heterogeneous Patients (MESLMHP) aims to maximize the overall expected survival probability of multiple-classes of patients, whereby different classes could be defined according to agreed patient categories based on response time targets, or by capturing differing medical conditions each with a corresponding survival function. Furthermore, we propose and demonstrate an approximation approach to solving the extended stochastic version of MESLMHP, which utilizes queuing theory to permit the modeling of congestion and utilization at each ambulance station, and does not require assumptions to be made on the utilization of ambulances. Both models are demonstrated using data from the ambulance service in Wales. We show that our multiple outcome measures and survival-maximizing approach, rather than one based on average response time targets alone or a single patient class provides more effective EMS ambulance allocations.     

Bittersweet and Paradoxical

The American Red Cross is the most active nonprofit organization involved in disaster planning and response in the United States. The organization deployed nearly 50,000 volunteers to provide essential support to victims of some 125,000 domestic disasters, including home fires, hurricanes, wildfires, and floods, in a recent two‐year period. This study asks how American Red Cross disaster response volunteer experiences function to cultivate satisfaction and, at the other end of the spectrum, the kind of dissatisfaction that leads people to quit; it pays particular attention to ways in which volunteer management shapes dissatisfaction and fatigue because of implications for volunteer retention. Paradoxically, the Red Cross facilitates the highly satisfying act of helping victims, but volunteers feel dissatisfied when management practices get in the way of helping. The study suggests voluntary organizations that rely on skilled, long‐term volunteers to deliver services should evaluate and strengthen their communication strategies, recognition practices, and support systems for volunteers in distress.     

Coalition-building and the forging of solidarity across difference and inequality

Diverse coalitions hold great potential for social movements, but they also face tremendous challenges. In this article, I review the literature on diverse alliances with a focus on how trust, commitment, and ultimately, solidarity can be developed and sustained across divides. The article begins by discussing the needs of diverse alliances to build trust and commitment, and the coalitional characteristics deemed vital for doing so, with a focus on shared neutral space, ongoing interaction, and social ties and bridgebuilders. Five coalitional processes and practices are identified and discussed that have been empirically found or theorized to be imperative for cultivating solidarity across difference and inequality. These processes include (a) uniting around shared principles while engaging difference; (b) acknowledging and managing inequalities; (c) making space for each other; (d) attention to managing conflicts; and (e) actions that confirm the shared commitments and negotiated identity. I conclude by evaluating the state of research on developing and sustaining alliances across divides.     

Incomes after Job‐loss in the United States: From Programme Rules to Panel Data

Welfare state studies are usually motivated by one or both of two concerns: programme effects on the incidence of poverty, and the possibility of perverse incentive effects. Most research has been comparative, using cross‐national indicators from the Organisation for Economic Co‐operation and Development and other international organizations. That research often contrasts the generosity of programmes in a number of European countries and the lack of it in the USA. Focusing on income transfers after job‐loss, in this article we critically examine the comparative evidence on US welfare state generosity and then use the Panel Study of Income Dynamics (PSID) to estimate what happens to job‐losers' incomes. The comparative analysis suggests conclusions more nuanced than found in much of the literature. The PSID analysis shows how the income effects of job‐loss vary across job‐losers and suggests that the role of unemployment compensation programmes in supporting incomes may be overstated.     

Coming Full Circle: Reoccurring Career Development Trends in Schools

Current state and national mandates focusing on academic achievement have drawn critical counseling resources away from career development. As the world of work radically changes and economic situations remain uncertain, the call for a return to school counseling roots based in career guidance has never been louder. The authors explore reoccurring career guidance trends throughout the history of school counseling to expand awareness of the basis of today's career and technical education discussions and increase understanding of the interconnectedness of career guidance and counseling and educational reform.