Unemployment insurance claims and COVID-19.

We explore the effect of various factors on interstate differences in weekly unemployment insurance claims, focusing specifically on the determinants over the initial period of the pandemic in the U.S. We consider the effects of COVID-19 cases, state policies enacted in response to COVID-19, relevant provisions of Federal Coronavirus Aid, Relief and Economic Security (CARES) legislation, and the nature of state economies. We find that during the initial weeks of the pandemic, unemployment claims were driven by consumer reactions to the coronavirus. We find that over the March 21-April 25 period states with greater employment in industries most affected by the virus and which issued orders closing nonessential businesses experienced greater weekly unemployment claims. We find mixed evidence that unemployment benefits affect the number of unemployment claims. However, we find no evidence that the ability to work at home mitigated the increase in unemployment rates during this period, nor evidence that the CARES Act's Payroll Protection Program influenced the level of new unemployment claims.

Development of the U.S. Army's Suicide Prevention Leadership Tool: The Behavioral Health Readiness and Suicide Risk Reduction Review (R4).

INTRODUCTION: Although numerous efforts have aimed to reduce suicides in the U.S. Army, completion rates have remained elevated. Army leaders play an important role in supporting soldiers at risk of suicide, but existing suicide-prevention tools tailored to leaders are limited and not empirically validated. The purpose of this article is to describe the process used to develop the Behavioral Health Readiness and Suicide Risk Reduction Review (R4) tools for Army leaders that are currently undergoing empirical validation with two U.S. Army divisions. MATERIALS AND METHODS: Consistent with a Secretary of the Army directive, approximately 76 interviews and focus groups were conducted with Army leaders and subject matter experts (SMEs) to obtain feedback regarding existing practices for suicide risk management, leader tools, and institutional considerations. In addition, reviews of the empirical literature regarding predictors of suicide and best practices for the development of practice guidelines were conducted. Qualitative feedback, empirical predictors of suicide, and design considerations were integrated to develop the R4 tools. A second series of 11 interviews and focus groups with Army leaders and SMEs was also conducted to validate the design and obtain feedback regarding the R4 tools. RESULTS: Leaders described preferences for tool processes (eg, incorporating engaged leadership, including multiple risk identification methods), formatting (eg, one page), organization (eg, low-intermediate-high risk scoring system), content (eg, excluding other considerations related to vehicle safety, including readiness implications), and implementation (eg, accounting for leadership judgment, tailoring process to specific leadership echelons, consideration of institutional barriers). Evidence-based predictors of suicide risk and practice guideline considerations (eg, design) were integrated with leadership feedback to develop the R4 tools that were tailored to specific leadership echelons. Leaders provided positive feedback regarding the R4 tools and described the importance of accounting for potential institutional barriers to implementation. This feedback was addressed by including recommendations regarding the implementation of standardized support meetings between different echelons of leadership. CONCLUSIONS: The R4 development process entailed the simultaneous integration of leadership feedback with evidence-based predictors of suicide risk and design considerations. Thus, the development of these tools builds upon previous Army leadership tools by specifically tailoring elements of those tools to accommodate leader preferences, accounting for potential implementation barriers (eg, institutional factors), and empirically evaluating the implementation of those tools. Future studies should consider utilizing a similar process to develop empirically based resources that are more likely to be incorporated into the routine practice of leaders supporting soldiers at risk of suicide, very often located at the company level and below.

Alcohol-impaired driving: average quantity consumed and frequency of drinking do matter.

OBJECTIVE: The objective of this article is to estimate and validate a logistic model of alcohol-impaired driving using previously ignored alcohol consumption behaviors, other risky behaviors, and demographic characteristics as independent variables. METHODS: The determinants of impaired driving are estimated using the US Centers for Disease Control and Prevention's (CDC) Behavioral Risk Factor Surveillance System (BRFSS) surveys. Variables used in a logistic model to explain alcohol-impaired driving are not only standard sociodemographic variables and bingeing but also frequency of drinking and average quantity consumed, as well as other risky behaviors. We use interactions to understand how being female and being young affect impaired driving. Having estimated our model using the 1997 survey, we validated our model using the BRFSS data for 1999. RESULTS: Drinking 9 or more times in the past month doubled the odds of impaired driving. The greater average consumption of alcohol per session, the greater the odds of driving impaired, especially for persons in the highest quartile of alcohol consumed. Bingeing has the greatest effect on impaired driving. Seat belt use is the one risky behavior found to be related to such driving. Sociodemographic effects are consistent with earlier research. Being young (18-30) interacts with two of the alcohol consumption variables and being a woman interacts with always wearing a seat belt. Our model was robust in the validation analysis. CONCLUSIONS: All 3 dimensions of drinking behavior are important determinants of alcohol-impaired driving, including frequency and average quantity consumed. Including these factors in regressions improves the estimates of the effects of all variables.

Social engagement and its relationship to health.

Older age is a time of life when major life tasks such as work and raising children have typically been completed. As a consequence, the daily demands for involvement in their social environment have lessened for older adults. It is believed that, because of their many possible benefits, social activities ultimately promote physical and mental health in older age. These propositions have captured the imagination of gerontologists and geriatricians for decades. Surprisingly, the body of relevant research is not plentiful. In this article we selectively review the theory and empirical support surrounding social engagement and its health consequences in older age.