Suchergebnisse

The past several decades have seen remarkable improvements in several major public health issues affecting young people: smoking rates are down, traffic crash fatalities have declined, and other unintentional injuries have declined in number. Yet, similar successes have not been replicated in mental health. Why are we, as a society, failing to make needed investments in children's mental health? How can we ensure that programs with the highest levels of evidence and economic returns reach a larger fraction of the young people and families who could benefit from them? This text investigates and addresses these questions.

Abstract
This study examines how exercise responds to plausibly exogenous "price shocks," in the form of weather conditions. Most notably, we find that within cold temperature ranges, a decrease in past-month temperature causes a significant decrease in past-month exercise, and this effect is generally larger for lower education and income groups. In large part this differential by socioeconomic group appears to be due to smaller increases in indoor activity during cold weather. These results suggest that interventions and policies aiming to increase exercise participation, particularly among lower socioeconomic populations, could do so in part by increasing the availability and attractiveness of indoor facilities and activities. Furthermore, to the extent that the higher elasticity of behavior for lower socioeconomic groups reflects a more general sensitivity to external factors, these results highlight the promise of interventions that address such factors more broadly.

Abstract
In United States presidential elections, the incumbent party's fortunes depend significantly on recent economic conditions, as numerous studies have shown. Many details of how economic voting takes place, however, are still not well understood. Here we present evidence on four issues. 1) Which is more important for determining people's votes, national or local economic conditions? 2) What time frame do people consider in economic voting? 3) Which demographic groups are most sensitive to the economy in their voting behavior? 4) How does economic voting depend on the political context—in particular, whether a candidate is running for re-election, and whether the incumbent party also controls Congress? Our study includes the first county-level analysis of economic voting in presidential elections. We find the answers to our four questions are: 1) national conditions, by far; 2) the most recent year; 3) blacks, females, and the non-elderly; and 4) no.

AbstractThe concept of "resilience analytics" has recently been proposed as a means to leverage the promise of big data to improve the resilience of interdependent critical infrastructure systems and the communities supported by them. Given recent advances in machine learning and other data‐driven analytic techniques, as well as the prevalence of high‐profile natural and man‐made disasters, the temptation to pursue resilience analytics without question is almost overwhelming. Indeed, we find big data analytics capable to support resilience to rare, situational surprises captured in analytic models. Nonetheless, this article examines the efficacy of resilience analytics by answering a single motivating question: Can big data analytics help cyber–physical–social (CPS) systems adapt to surprise? This article explains the limitations of resilience analytics when critical infrastructure systems are challenged by fundamental surprises never conceived during model development. In these cases, adoption of resilience analytics may prove either useless for decision support or harmful by increasing dangers during unprecedented events. We demonstrate that these dangers are not limited to a single CPS context by highlighting the limits of analytic models during hurricanes, dam failures, blackouts, and stock market crashes. We conclude that resilience analytics alone are not able to adapt to the very events that motivate their use and may, ironically, make CPS systems more vulnerable. We present avenues for future research to address this deficiency, with emphasis on improvisation to adapt CPS systems to fundamental surprise.

Abstract
Mental health problems represent a potentially important but relatively unexplored factor in explaining human capital accumulation during college. We conduct the first study, to our knowledge, of how mental health predicts academic success during college in a random longitudinal sample of students. We find that depression is a significant predictor of lower GPA and higher probability of dropping out, particularly among students who also have a positive screen for an anxiety disorder. In within-person estimates using our longitudinal sample, we find again that co-occurring depression and anxiety are associated with lower GPA, and we find that symptoms of eating disorders are also associated with lower GPA. This descriptive study suggests potentially large economic returns from programs to prevent and treat mental health problems among college students, and highlights the policy relevance of evaluating the impact of such programs on academic outcomes using randomized trials.

AbstractThe Mission Dependency Index (MDI) is a risk metric used by US military services and federal agencies for guiding operations, management, and funding decisions for facilities. Despite its broad adoption for guiding the expenditure of billions in federal funds, several studies on MDI suggest it may have flaws that limit its efficacy. We present a detailed technical analysis of MDI to show how its flaws impact infrastructure decisions. We present the MDI used by the US Navy and develop a critique of current methods. We identify six problems with MDI that stem from its interpretation, use, and mathematical formulation, and we provide examples demonstrating how these flaws can bias decisions. We provide recommendations to overcome flaws for infrastructure risk decision making but ultimately recommend the US government develop a new metric less susceptible to bias.

This study examined changes in the demand and role of student mental health services as reported by administrators from college counseling and mental health centers (CCMHCs). Ten CCMHC administrators from US institutions engaged in semi-structured interviews. Four themes characterized the changes in demand and role of student mental health services: 1) an increase in the severity of mental health concerns and demand for services; 2) overall psychosocial differences in today's college student population; 3) changes in the roles of counseling centers; and 4) institutional challenges and the response to those challenges. Administrators' responses provided an enriched understanding of the current mental health needs of college students, the potential psychosocial and societal causes of these needs, and the importance of dynamic and flexible responses by counseling centers and institutions more broadly as the mental health profile of students continues to evolve.

Mental illness stigma has been identified by national policy makers as an important barrier to help seeking for mental health. Using a random sample of 5,555 students from a diverse set of 13 universities, we conducted one of the first empirical studies of the association of help-seeking behavior with both perceived public stigma and people's own stigmatizing attitudes (personal stigma). There were three main findings: (a) Perceived public stigma was considerably higher than personal stigma; (b) personal stigma was higher among students with any of the following characteristics: male, younger, Asian, international, more religious, or from a poor family; and (c) personal stigma was significantly and negatively associated with measures of help seeking (perceived need and use of psychotropic medication, therapy, and nonclinical sources of support), whereas perceived stigma was not significantly associated with help seeking. These findings can help inform efforts to reduce the role of stigma as a barrier to help seeking.

Abstract
Despite Federal directives calling for an integrated approach to strengthening the resilience of critical infrastructure systems, little is known about the relationship between human behavior and infrastructure resilience. While it is well recognized that human response can either amplify or mitigate catastrophe, the role of human or psychological resilience when infrastructure systems are confronted with surprise remains an oversight in policy documents and resilience research. Existing research treats human resilience and technological resilience as separate capacities that may create stress conditions that act upon one another. There remains a knowledge gap regarding study of those attributes in each that build infrastructure resilience as an integrated system of humans and technologies. This work draws on concepts found in the resilience engineering and psychology literature to examine the dynamic relationships between human resilience and the resilience of complex, socio-technical critical infrastructure systems. We identify and organize 18 system capacities and 23 human capacities that influence infrastructure resilience. We then correlate individual human and system resilience capacities to determine how each influences four socio-technical processes for resilience: sensing, anticipating, adapting, and learning. Our analysis shows that the human and technical resilience capacities reviewed are interconnected, interrelated, and interdependent. Further, we find current literature is focused more on cognitive and behavioral dimensions of human resilience and we offer ways to better incorporate affective capacities. Together, we present a simple way to link the resilience of technological systems to the cognitive, behavioral, and affective dimensions of humans responsible for the system design, operation, and management.

Does college change students' political preferences? While existing research has documented associations between college education and political views, it remains unclear whether these associations reflect a causal relationship. We address this gap in previous research by analyzing a quasi-experiment in which university students are assigned to live together as roommates. While we find little evidence that college students as a whole become more liberal over time, we do find strong evidence of peer effects, in which students' political views become more in line with the views of their roommates over time. This effect is strongest for conservative students. These findings shed light on the role of higher education in an era of political polarization.