Mental health status of the Hmong Americans in 2011: three decades revisited

This article provides a comprehensive overview of the Hmong in America and encompasses their mental health status for the past 35 years. Since their mass arrival to the United States in 1975, limited research has been compiled to track the specific mental health issues that affect this collective community alone. Major chronological research findings were compiled for this article and specific findings concerning the Hmong and their mental health issues were compared to findings for other Southeast Asian groups. In conclusion, the findings of this article indicate that the Hmong still have higher rates of being diagnosed with depression, the lowest help-seeking behaviors in utilizing Western medicine, and the lowest arithmetic average of "happiness" scaled on an assessment tool. The purpose of this article is to better steer future research projects that entail tracking and differentiating the specific mental health domains of the Hmong.     

Epistemic modesty,ostentatiousness and the uncertainties of epigenetics: on the knowledge machinery of (social) science

Epigenetic processes are garnering attention in the social sciences, where some scholars assert their importance for theorizing social life. I engage with such ideas here by drawing on interviews with leading bioscientists. To begin with, I underscore the (productive) uncertainties of those working in and around epigenetics; I describe these as a manifestation of ‘epistemic modesty’, and suggest that dissensus helps to propel biomedical innovation. Then, drawing on the concept of ‘alien science’, I detail some researchers’ ambivalences regarding the notion of ‘transgenerational inheritance’; their dissatisfaction with the (public) communication practices of other scientists (situated in what I term a regime of ‘epistemic ostentatiousness’); and the challenges faced when moderating societal discussion of epigenetics in ways that expand excitement whilst deflating (what researchers regard as) unrealistic expectations. The paper concludes with reflections on the knowledge machinery of the (social) sciences, and employs the study data to interrogate sociological engagements with epigenetics.     

Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management

Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies.     

Toward General Principles for Resilience Engineering

Maintaining the performance of infrastructure-dependent systems in the face of surprises and unknowable risks is a grand challenge. Addressing this issue requires a better understanding of enabling conditions or principles that promote system resilience in a universal way. In this study, a set of such principles is interpreted as a group of interrelated conditions or organizational qualities that, taken together, engender system resilience. The field of resilience engineering identifies basic system or organizational qualities (e.g., abilities for learning) that are associated with enhanced general resilience and has packaged them into a set of principles that should be fostered. However, supporting conditions that give rise to such first-order system qualities remain elusive in the field. An integrative understanding of how such conditions co-occur and fit together to bring about resilience, therefore, has been less clear. This article contributes to addressing this gap by identifying a potentially more comprehensive set of principles for building general resilience in infrastructure-dependent systems. In approaching this aim, we organize scattered notions from across the literature. To reflect the partly self-organizing nature of infrastructure-dependent systems, we compare and synthesize two lines of research on resilience: resilience engineering and social-ecological system resilience. Although some of the principles discussed within the two fields overlap, there are some nuanced differences. By comparing and synthesizing the knowledge developed in them, we recommend an updated set of resilience-enhancing principles for infrastructure-dependent systems. In addition to proposing an expanded list of principles, we illustrate how these principles can co-occur and their interdependencies.     

DESPERATE TIMES CALL FOR DESPERATE MEASURES: GOVERNMENT SPENDING MULTIPLIERS IN HARD TIMES

We investigate state-dependent effects of fiscal multipliers and allow for endogenous sample splitting to determine whether the U.S. economy is in a slack state. When the endogenized slack state is estimated as the period of the unemployment rate higher than about 12%, the estimated cumulative multipliers are significantly larger during slack periods than nonslack periods and are above unity. We also examine the possibility of time-varying regimes of slackness and find that our empirical results are robust under a more flexible framework. Our estimation results point out the importance of the heterogenous effects of fiscal policy and shed light on the prospect of fiscal policy in response to economic shocks from the current COVID-19 pandemic. (JEL C32, E62, H20, H62)     

Pressure to Attend Therapy,Dyadic Adjustment,and Adverse Childhood Experiences: Direct and Indirect Effects on the Therapeutic Alliance in Couples Therapy

In this study we examine the role that pressure to attend therapy, dyadic adjustment, and adverse childhood experiences (ACEs) play in developing the therapeutic alliance. A total of 351 couples received treatment as usual at three family therapy training clinics. Participants rated predictor variables at intake and alliance at the fourth session. Results of a path analysis indicate that each partner's dyadic adjustment is directly associated with the quality of her or his own alliance. In addition, when male partners report more ACEs and pressure to attend treatment, their own alliance scores decrease. Additionally, when one partner reports feeling pressure to attend therapy, the other partner's alliance decreases. Finally, for males, there is an indirect effect of dyadic adjustment on alliance through pressure to attend therapy. These results suggest that clinicians should routinely assess relationship adjustment, how pressured each partner is feeling to attend treatment, and ACEs; as these may impact alliance quality.     

An Introduction and Illustration of Bayesian Modeling in Couple and Family Therapy Research

Bayesian modeling is becoming increasing popular as a method for data analyses in the social sciences and can move couple, marriage, and family therapy (C/MFT) research forward. Bayesian modeling helps researchers better understand the uncertainty of findings and incorporate previous research into analyses. Other benefits of Bayesian modeling are the straightforward interpretation of findings, high-quality inferences even with small samples (in combination with an informative prior), and the ability to work with complex data structures (observations nested in relationships and time points) which are common in C/MFT research. This article introduces the benefits of Bayesian modeling and provides an example of an Actor–Partner Interdependence Model using R. Information on how to conduct the same analyses using Stata and MPlus is provided in the Supplemental Information.     

The intergenerational transmission of income mobility between mothers and their young adult daughters: The mediating role of their daughters' educational attainment

This study examines whether the daughters' educational attainment mediates the intergenerational transmission of economic mobility between mothers and their young adult daughters. To create mother–daughter dyads, two data sets were combined: The National Longitudinal Survey of Youth 1979 (NLSY79) and the National Longitudinal Survey of Youth 79 for Children and Young Adults (NLSY79 CY). A total of 2,456 dyads were included for analysis. We used a mediation model to explore the relationship between mothers' income and their young adult daughters' income. Mothers' income was associated with their young adult daughters' educational attainment and income. The mediation model indicated partial mediation of the relationship between mothers' income and their young adult daughters' income via their young adult daughters' educational attainment. Addressing issues of income inequality among mothers may serve as a buffer against the low upward mobility across generations for their young adult daughters raised by low-income mothers. It is imperative to provide programs and financial assistance for mothers to bolster their income and thereby their daughters' educational attainment and income in young adulthood and therefore improve economic mobility from mothers to daughters.     

Using Fairness Models to Improve Equity in Health Delivery Fleet Management

Inefficiency and inequity are two challenges that plague humanitarian operations and health delivery in resource‐limited regions. Increasing capacity in humanitarian and health delivery supply chains is one option that has the potential to improve equity while maintaining efficiency. For example, the nonprofit organization Riders for Health has worked to increase capacity by providing reliable transportation to health workers in rural parts of sub‐Saharan Africa; with more motorcycle hours at their disposal, health workers can perform more outreach to outlying communities. We develop a model using a family of fairness function to quantify the efficiency and equity of health delivery as capacity is increased via development programs. We present optimal resource allocations under utilitarian, proportionally fair, and egalitarian objectives and extend the model to include dual modes of transport and diminishing returns of subsequent outreach visits. Finally, we demonstrate how to apply our model at a regional level to provide support for humanitarian decision makers such as Riders for Health. We use data from the baseline phase of our evaluation trial of Riders for Health in Zambia to quantify efficiency and equity for one real‐world scenario.