The Savvy Caregiver Program: Impact of an Evidence-Based Intervention on the Well-Being of Ethnically Diverse Caregivers

This article reports on the impact of the Savvy Caregiver Program (SCP) on English-speaking caregivers of Hispanic, Black/African American, and Asian/Pacific Islander descent. Caregivers completed a questionnaire prior to study enrollment, at 6 and 12 months postenrollment. Caregivers in all 3 ethnic groups showed more caregiver competence, reduced depression, greater tolerance for care recipients’ memory problems, better management of their overall situation, and improved perception of that situation 6 months and 12 months post-enrollment. The study demonstrates that in the sample studied the SCP was as effective in helping ethnically diverse caregivers as it has shown to be with Caucasian caregivers.     

Power and perceptions in participatory monitoring and evaluation

This paper examines the assumptions that commonly underpin the design of participatory monitoring and evaluation (PM&E) within development programmes through the examination of a case study of a large rural development programme in Uganda. This case study reveals a mismatch between programme assumptions and participant perceptions, which stymied the implementation of PM&E. In this case, PM&E was based on the assumptions that programme and participant goals were compatible, participants were willing to volunteer and engage themselves for the greater good of their communities, and information sharing and communication was fairly free and open. However, farmers within the programme felt that the bureaucratic and accountability requirements of the programme were not their concern, and were acutely aware of power differences between farmers and programme officials, and between farmers of varying status. The key lesson to be drawn from this case is the need for a heightened awareness of power dynamics and political factors in the design of PM&E.     

Racial diversity in the suburbs: how race-neutral responses to demographic change perpetuate inequity in suburban school districts

Suburbs across the US are experiencing dramatic demographic shifts, yet there is little research available on how suburban school districts are dealing with these changes. In this article, we examine the discourses surrounding race and demographic change in three suburban school districts that have been undergoing rapid demographic changes and which contain demographically distinct areas within their district boundaries. Utilizing a critical discourse analysis (CDA) approach, we analyze how the policy context (federal and state) frames actors’ discourses and understandings of race, paying particular attention to the political and institutional factors affecting school policy. We illustrate how the discourse, in turn, is related to the actions (or inactions) taken by district and school leaders to respond to demographic change. We conclude the article by discussing policy implications and potential challenges districts may face in the future if efforts to purposively address racial changes continue to be avoided.     

A Multidisciplinary Cognitive Behavioural Framework of Impulse Buying: A Systematic Review of the Literature

Impulse buying (IB) is one of the most fragmented concepts in the marketing and consumer literature. This has resulted in some contradictory findings and a lack of an overarching theoretical framework for understanding the IB process and its outcomes. Based on a systematic review of the literature published over the past 60 years, the authors synthesize various research perspectives into a comprehensive multidisciplinary framework of IB – linking antecedents, triggers, the buying act and post‐purchase outcomes. The paper makes four specific contributions relevant to both academic researchers and practitioners. First, it provides a comprehensive understanding of IB as a process and outcome, by systematically reviewing the existing literature. Second, it specifically recognizes and discusses the triggers of IB, by drawing on literature related to the buying process, intentions and motivations. Third, this is the first meta‐analysis review in the area. Finally, it considers the potential consequences of IB that lead to subsequent IB, and provides a framework for future investigation. This paper also addresses a problem of relevance to both academics and practitioners, proposing further research and managerial implications.     

Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems

Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of society. To improve the performance of such systems, we often use risk and vulnerability analysis to find and address system weaknesses. A critical component of such analyses is the ability to accurately determine the negative consequences of various types of failures in the system. Numerous mathematical and simulation models exist that can be used to this end. However, there are relatively few studies comparing the implications of using different modeling approaches in the context of comprehensive risk analysis of critical infrastructures. In this article, we suggest a classification of these models, which span from simple topologically‐oriented models to advanced physical‐flow‐based models. Here, we focus on electric power systems and present a study aimed at understanding the tradeoffs between simplicity and fidelity in models used in the context of risk analysis. Specifically, the purpose of this article is to compare performance estimates achieved with a spectrum of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if more simplified topological measures can be combined using statistical methods to be used as a surrogate for physical flow models. The results of our work provide guidance as to appropriate models or combinations of models to use when analyzing large‐scale critical infrastructure systems, where simulation times quickly become insurmountable when using more advanced models, severely limiting the extent of analyses that can be performed.     

Path to “Stardom” in Globally Distributed Hybrid Teams: An Examination of a Knowledge‐Centered Perspective using Social Network Analysis

Although distributed teams have been researched extensively in information systems and decision science disciplines, a review of the literature suggests that the dominant focus has been on understanding the factors affecting performance at the team level. There has however been an increasing recognition that specific individuals within such teams are often critical to the team's performance. Consequently, existing knowledge about such teams may be enhanced by examining the factors that affect the performance of individual team members. This study attempts to address this need by identifying individuals who emerge as “stars” in globally distributed teams involved in knowledge work such as information systems development (ISD). Specifically, the study takes a knowledge‐centered view in explaining which factors lead to “stardom” in such teams. Further, it adopts a social network approach consistent with the core principles of structural/relational analysis in developing and empirically validating the research model. Data from U.S.–Scandinavia self‐managed “hybrid” teams engaged in systems development were used to deductively test the proposed model. The overall study has several implications for group decision making: (i) the study focuses on stars within distributed teams, who play an important role in shaping group decision making, and emerge as a result of a negotiated/consensual decision making within egalitarian teams; (ii) an examination of emergent stars from the team members’ point of view reflects the collective acceptance and support dimension decision‐making contexts identified in prior literature; (iii) finally, the study suggests that the social network analysis technique using relational data can be a tool for a democratic decision‐making technique within groups.     

Combining Occurrence and Toxicity Information to Identify Priorities for Drinking-Water Mixture Research

Characterizing all possible chemical mixtures in drinking water is a potentially overwhelming project, and the task of assessing each mixture's net toxicity even more daunting. We propose that analyzing occurrence information on mixtures in drinking water may help to narrow the priorities and inform the approaches taken by researchers in mixture toxicology. To illustrate the utility of environmental data for refining the mixtures problem, we use a recent compilation of national ground-water-quality data to examine proposed U.S. Environmental Protection Agency (EPA) and Agency for Toxic Substances and Disease Registry (ATSDR) models of noncancer mixture toxicity. We use data on the occurrence of binary and ternary mixtures of arsenic, cadmium, and manganese to parameterize an additive model and compute hazard index scores for each drinking-water source in the data set. We also use partially parameterized interaction models to perform a bounding analysis estimating the interaction potential of several binary and ternary mixtures for which the toxicological literature is limited. From these results, we estimate a relative value of additional toxicological information for each mixture. For example, we find that according to the U.S. EPA's interaction model, the levels of arsenic and cadmium found in U.S. drinking water are unlikely to have synergistic cardiovascular effects, but the same mixture's potential for synergistic neurological effects merits further study. Similar analysis could in future be used to prioritize toxicological studies based on their potential to reduce scientific and regulatory uncertainty. Environmental data may also provide a means to explore the implications of alternative risk models for the toxicity and interaction of complex mixtures.     

The Continued Importance of Quality Parent–Adolescent Relationships During Late Adolescence

The quality of adolescents' relationships with residential parents has been found to predict many different health and behavioral youth outcomes; strong associations have also been found between these outcomes and family processes, and between relationship quality and family processes. Data from Rounds 1–5 of the National Longitudinal Survey of Youth, 1997 were used to examine hypotheses about the influence of the parent–adolescent relationship on subsequent adolescent mental well‐being and delinquency, as mediated by family processes. Using structural equation modeling, we found that the influence of a positive residential parent–adolescent relationship on better mental well‐being and fewer delinquency was entirely mediated by family routines, parental monitoring, and parental supportiveness, net of sociodemographic controls.     

Delayed Adulthood,Delayed Desistance? Trends in the Age Distribution of Problem Behaviors

As the transition to adulthood becomes more protracted and less orderly, fewer young people occupy adult roles and experience the social control associated with these roles. One might therefore expect behaviors associated with the teenage years to spill over into older age groups, reflecting postponed entrance into full social adulthood. We test this hypothesis by examining trends over time in the age distribution of crime, substance use, and violent death. We find little evidence that behaviors typical of adolescence are moving upward to older ages. Although the achievement of adult roles is being pushed to older ages, this stretching of the transition to adulthood is not reflected in the observed patterns of substance use, violent death, and arrests.