A Factor Analysis Approach Toward Reconciling Community Vulnerability and Resilience Indices for Natural Hazards

The concepts of vulnerability and resilience help explain why natural hazards of similar type and magnitude can have disparate impacts on varying communities. Numerous frameworks have been developed to measure these concepts, but a clear and consistent method of comparing them is lacking. Here, we develop a data-driven approach for reconciling a popular class of frameworks known as vulnerability and resilience indices. In particular, we conduct an exploratory factor analysis on a comprehensive set of variables from established indices measuring community vulnerability and resilience at the U.S. county level. The resulting factor model suggests that 50 of the 130 analyzed variables effectively load onto five dimensions: wealth, poverty, agencies per capita, elderly populations, and non–English-speaking populations. Additionally, the factor structure establishes an objective and intuitive schema for relating the constituent elements of vulnerability and resilience indices, in turn affording researchers a flexible yet robust baseline for validating and expanding upon current approaches.     

Clinically Significant Effects of Group Cognitive Behavioral Therapy on Spouse Caregivers' Mental Health and Cognitive Functioning: A Pilot Study

The objective of this pilot study was to investigate whether group cognitive behavioral therapy (CBT) resulted in clinically meaningful improvements in caregiver mood, burden, and cognition. We screened 97 caregivers in Toronto, Canada, of whom 25 with DSM-IV disorders began the 13-week CBT intervention, and 12 completed therapy and the 3-month follow-up. Each caregiver experienced clinically significant improvement on at least 2 of the following outcomes: diagnostic criteria, mood, attention, memory, and caregiver burden. Despite effectiveness, the challenges of recruiting distressed caregivers for therapy suggest that CBT might be most useful as part of a stepped care model of treatment.     

An Application of Bayesian Methods to Small Area Poverty Rate Estimates

Efforts to estimate various sociodemographic variables in small geographic areas are proving difficult with the replacement of the Census long-form with the American Community Survey (ACS). Researchers interested in subnational demographic processes have previously relied on Census 2000 long-form data products in order to answer research questions. ACS data products promise to begin providing up-to-date profiles of the nation’s population and economy; however, unit- and item-level nonresponse in the ACS have left researchers with gaps in subnational coverage resulting in unstable and unreliable estimates for basic demographic measures. Borrowing information from neighboring areas and across time with a spatiotemporal smoothing process based on Bayesian statistical methods, it is possible to generate more stable and accurate estimates of rates for geographic areas not represented in the ACS. This research evaluates this spatiotemporal smoothing process in its ability to derive estimates of poverty rates at the county level for the contiguous United States. These estimates are then compared to more traditional estimates produced by the US Census Bureau, and comparisons between the two methods of estimation are carried out to evaluate the practical application of this smoothing method. Our findings suggest that by using available data from the ACS only, we are able to recreate temporal and spatial patterns of poverty in US counties even in years where data are sparse. Results show that the Bayesian methodology strongly agrees with the estimates produced by the SAIPE program, even in years with little data. This methodology can be expanded to other demographic and socioeconomic data with ease.     

Neuroticism,Negative Thinking,and Coping With Respect to Career Decision State

Using structural equation modeling, the present study investigated relationships between neuroticism, coping strategies, and negative career thoughts within the context of attaining a positive career decision state. Results from the initial model, based on a sample of college students (119 women, 113 men; M = 20.3 years) enrolled in a career development course, revealed that coping strategies were not a significant contribution to the model. The final model, without coping strategies, showed that neuroticism had a significant indirect effect on career decision state through negative thinking and that the relationship between neuroticism and career decision state was also significant. Findings also indicate that in the presence of negative career thoughts, neuroticism becomes associated with a more positive career decision state. Practical implications include suggestions that counselors intervene on clients' negative career thoughts to potentially render their neurotic tendencies more productive in reaching a desired career decision state.     

What is new with old? What old age teaches us about inequality and stratification

Aging is remarkably unequal. Who survives to grow old in America and the circumstances they face once there reflect durable racial, socioeconomic, and gender inequalities that structure our lives from birth. Yet within the field of social stratification and mainstream sociology proper, examinations of the rapidly growing population of older Americans are often relegated to a “gerontological” periphery. This essay posits that the failure to place aging as a core concern in stratification and inequality is a missed opportunity. We argue for the importance of reintegrating studies on the stratification of aging and explain why such a move is necessary. Specifically, we posit that (a) examining the aging population is necessary for understanding American inequality because aging is an outcome that is ubiquitous yet highly stratified; (b) aging and being seen as “old” in a youth‐focused society are stratifying processes in their own right; and (c) later life provides for analytical comparisons that are illustrative of how key mechanisms of inequality structure and stratify. After examining insights provided by a new wave of research on the aging U.S. population, we revisit the implications for understanding inequality and stratification in a graying and unequal America.     

Case-based methods and agent-based modelling: bridging the divide to leverage their combined strengths

Two leading camps for studying social complexity are case-based methods (CBM) and agent-based modelling (ABM). Despite the potential epistemological links between ‘cases’ and ‘agents,’ neither camp has leveraged their combined strengths. A bridge can be built, however, by drawing on Abbott’s insight that ‘agents are cases doing things’, Byrne’s suggestion that ‘cases are complex systems with agency’, and by viewing CBM and ABM within the broader trend towards computational modelling of cases. To demonstrate the utility of this bridge, we describe how CBM can utilise ABM to identify case-based trends; explore the interactions and collective behaviour of cases; and study different scenarios. We also describe how ABM can utilise CBM to identify agent types; construct agent behaviour rules; and link these to outcomes to calibrate and validate model results. To further demonstrate the bridge, we review a public health study that made initial steps in combining CBM and ABM.     

Social Participation, Sense of Community and Social Well Being: A Study on American, Italian and Iranian University Students

Aim of the study was to assess the relationship between social participation and Sense of Community in a sample of University students and the impact of such variables on Social well being. A further aim was to assess the generality of the relationships between these constructs across different countries, and specifically, the USA, Italy and Iran. The sample includes 200 Italian, 125 American and 214 Iranian University students, male and female. Results show higher levels of social participation, Sense of Community and Social well being among American students. Sense of Community is positively correlated with social participation in all three samples; however, only among Italian students social participation positively predicts Social well being. Implications of results will be discussed.     

Marital Status and Social Well-Being: Are the Married Always Better Off?

This study uses pooled cross-section time-series data, over the years 1982, 1992 and 2000, to estimate the impact of various restrictive abortion laws on the demand for abortion. This study complements and extends prior research by explicitly including the price of obtaining an abortion in the estimation. The empirical results show that the real price of an abortion has a statistically and numerically significant negative impact on abortion demand. Over the period 1982–2000 approximately 20% of the decline in the incidence of abortion was due solely to the increase in the real price of obtaining an abortion. A state Medicaid funding restriction of abortion and a parental involvement law reduce the abortion demand, but a state waiting period and a mandatory counseling law have no statistically significant impact on the abortion demand. The empirical results also provide support for the hypothesis that increases in abortion costs not only reduce the number of abortions, but also reduce the number of pregnancies by altering women’s sexual/contraceptive practices.