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Unaffordable housing is a growing problem for many households in the United States. In 2019, nearly half of all renter households experienced housing cost burden, defined as paying more than 30% of...

The intentional and sustained actions to advance diversity, equity, and inclusion (DEI) in school psychology science and scholarship, will have reciprocal and dynamic influences on graduate prepara...

The relationship between refugee investments in human capital and short-run economic outcomes may influence the extent to which refugees invest in human capital that is associated with positive future economic mobility. Using data from the Annual Survey of Refugees from 2016 and 2017 we assess the relationship between recent investments in human capital and hourly wages for employed refugees in the United States. Results suggest that recent job training has a positive effect on hourly wages. In contrast, enrollment in English classes and educational programmes have no short-term positive effects on hourly wages. When combined with the pressure resettled refugees experience to find employment quickly, these results suggest that the lack of short-term wage benefits from English language or educational courses may dissuade refugees from sufficiently investing in the amount of English language or education necessary to promote positive long-term economic mobility.

Background: Non-chromosomal birth defects are an important risk factor for several childhood cancers. However, these associations are less clear for Hodgkin lymphoma (HL). Therefore, we sought to more fully elucidate the association between non-chromosomal birth defects and HL risk. Procedure: Information on cases (n = 517) diagnosed with HL (ages of 0–14) at Children's Oncology Group Institutions for the period of 1989–2003 was obtained. Control children without a history of cancer (n = 784) were identified using random digit dialing and individually matched to cases on sex, race/ethnicity, age, and geographic location. Parents completed comprehensive interviews and answered questions including whether their child had been born with a non-chromosomal birth defect. To test the association between birth defects and HL risk, conditional logistic regression was applied to generate adjusted odds ratios (aORs) and 95% confidence intervals (CIs). Results: Children born with any non-chromosomal birth defect were not more likely to be diagnosed with HL at 0–14 years of age (aOR: 0.91; 95% CI: 0.69–1.21). No associations were detected between major or minor birth defects and HL (aOR: 1.34; 95% CI: 0.67–2.67 and aOR: 0.88; 95% CI: 0.57–1.34, respectively). Similarly, no association was observed for children born with any birth defect and EBV-positive HL (aOR: 0.57; 95% CI: 0.25–1.26). Conclusions: Previous assessments of HL in children with non-chromosomal birth defects have been limited. Using data from the largest case–control study of HL in those <15 years of age, we did not observe strong associations between being born with a birth defect and HL risk.

Emerging evidence suggests that the COVID-19 pandemic has extracted a substantial toll on immigrant communities in the United States, due in part to increased potential risk of exposure for immigra...

Contrary to the pervasive narrative of rural areas of the U.S. in decline, a close look at recent data suggests that many rural areas have experienced increased numbers of adults in their prime working years who may help to improve the vitality of their new communities. What factors “pull” new residents to rural parts of the U.S. and the experiences new residents have in these rural communities are underexplored, but may offer important lessons for rural community development. This chapter presents results of a 2019 survey of recent movers to rural Minnesota counties. Family connections and quality-of-life factors were important considerations for many rural migrants, but economic opportunities also prompted moves. Migrants expressed high levels of satisfaction with many facets of community life, including school quality, community safety, and healthcare, but also expressed notably lower levels of satisfaction with housing affordability and broadband access. These findings suggest that along with maintaining a healthy local economy, rural areas interested in attracting new residents should also expand housing options, make strategic investments in technological infrastructure and highlight the slower pace of life, smaller scale, and social intimacy that are important motivating factors for migrants moving to rural communities.

Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented worker performance. Reconciling these perspectives, we theorize that intermediate levels of domain experience are optimal for algorithm-augmented performance, due to the interplay between two countervailing forces-ability and aversion. Although domain experience can increase performance via increased ability to complement algorithmic advice (e.g., identifying inaccurate predictions), it can also decrease performance via increased aversion to accurate algorithmic advice. Because ability developed through learning by doing increases at a decreasing rate, and algorithmic aversion is more prevalent among experts, we theorize that algorithm-augmented performance will first rise with increasing domain experience, then fall. We test this by exploiting a within-subjects experiment in which corporate information technology support workers were assigned to resolve problems both manually and using an algorithmic tool. We confirm that the difference between performance with the algorithmic tool versus without the tool was characterized by an inverted U-shape over the range of domain experience. Only workers with moderate domain experience did significantly better using the algorithm than resolving tickets manually. These findings highlight that, even if greater domain experience increases workers' ability to complement algorithms, domain experience can also trigger other mechanisms that overcome the positive ability effect and inhibit performance. Additional analyses and participant interviews suggest that, even though the highest experience workers had the greatest ability to complement the algorithmic tool, they rejected its advice because they felt greater accountability for possible unintended consequences of accepting algorithmic advice.

The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults at risk for coronavirus disease 2019 (COVID-19) comprising 14 established United States (US) prospective cohort studies. For decades, C4R cohorts have collected extensive data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R will link this pre-COVID phenotyping to information on SARS-CoV-2 infection and acute and post-acute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and broadly reflects the racial, ethnic, socioeconomic, and geographic diversity of the US. C4R is ascertaining severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations, and high-quality events surveillance. Extensive pre-pandemic data minimize referral, survival, and recall bias. Data are being harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these will be pooled and shared widely to expedite collaboration and scientific findings. This unique resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including post-acute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term trajectories of health and aging.

Despite the ubiquity of global university rankings coverage in media and academia, a concerted attempt to investigate the role of social media in ranking entrepreneurship remains absent. By drawing on an affect lens, we critically examine the social media activities of two commercial rankers: Times Higher Education (THE) and Quacquarelli Symonds Ltd (QS). Based on an analysis of THE’s Twitter feed and QS’ Facebook page between January and June 2020, we illuminate how rankers use social media for affective storytelling to frame and sell their expertise within global HE. First, we demonstrate how THE uses Twitter to engage an audience of institutions, governments, and administrators, reinforcing universities’ increasingly aggressive behavior as market competitors. Next, we show how QS engages a student-oriented audience on Facebook, furthering the role of students as consumers. Before and during the COVID pandemic, we observed that both rankers amplified and mobilized precarity associated with performance and participation, selling hope to targeted audiences to market their expertise as solutions—a strategy that remained amidst the global pandemic. Based on our observation of the front stage of rankers’ social media activities, we argue that rankers’ deployment of social media as a form of affective infrastructure is conducive to further sustaining, diffusing, and normalizing rankings in HE globally.

Elected after espousing xenophobic rhetoric and policy proposals, President Donald Trump has pursued an anti-immigrant approach to governance that spans multiple areas of policy and practice in the...

This article uses the Panel Study of Income Dynamics to analyse Black–White differences in housing cost burden exposure among renter households in the USA from 1980 to 2017, expanding understanding of this phenomenon in two respects. Specifically, we document how much this racial disparity changed among renters over almost four decades and identify how much factors associated with income or housing costs explain Black–White inequality in exposure to housing cost burden. For White households, the net contribution of household, neighbourhood and metropolitan covariates accounts for much of the change in the probability of housing cost burden over time. For Black households, however, the probability of experiencing housing cost burden continued to rise throughout the period of this study, even after controlling for household, neighbourhood and metropolitan covariates. This suggests that unobserved variables like racial discrimination, social networks or employment quality might explain the increasing disparity in cost burden among for Black and White households in the USA.

<p>Between 1934 and the time of the 1940 Census, the US government built and leased 30,151 units of public housing, but we know little about the residents who benefited from this housing. We use a unique methodology that compares addresses of five public housing developments to complete-count data from the 1940 Census to identify residents of public housing in New York City at the time of the census. We compare these residents to the larger pool of residents living in New York City in 1940 who were eligible to apply for the housing to assess how closely housing authorities adhered to the intent of the National Industrial Recovery Act (1933) and the Housing Act of 1937. This comparison produces a picture of whom public housing administrators considered deserving of this public benefit at the dawn of the public housing program in the United States. Results indicate a shift toward serving households with lower incomes over time. All the developments had a consistent preference for households with a “nuclear family” structure, but policies favoring racial segregation and other discretion on the part of housing authorities for tenant selection created distinct populations across housing developments. Households headed by a naturalized citizen were favored over households headed by a native-born citizen in nearly all the public housing projects. This finding suggests a more nuanced understanding of who public housing administrators considered deserving of the first public housing than archival research accounts had previously indicated.</p>

Anti-smoking norms and educational aspirations are established tobacco prevention targets for general United States (U.S.) adolescent populations but protective factors remain poorly characterized for Somali-American youth. Here we describe patterns of past 30-day tobacco use and associated protective factors among eighth, ninth, and eleventh grade Somali adolescent respondents (n = 2009) to the 2016 Minnesota Student Survey using multivariate logistic regressions. E-cigarette (5.7%) and hookah (5.0%) use were most prevalent. Male youth reported higher levels of tobacco use across products. Adjusted odds ratios showed that internal developmental assets (e.g., e-cigarettes aOR 0.37, 95% CI 0.37, 0.79) and parental anti-smoking norms (e.g., e-cigarettes aOR 0.19, 95% CI 0.09, 0.38) protected against use of all tobacco products. E-cigarettes and hookah are prevalent among U.S. Somali youth, highlighting the need for prevention efforts that address emerging tobacco products and leverage protective factors such as internal assets and parental anti-smoking norms.

In recent decades, the number of unauthorized immigrants in the United States has increased substantially, while simultaneously housing affordability has become a crisis. Despite these trends and t...

CONTEXT This article examines factors related to earnings in the context of the governmental public health system's urgent need to recruit and retain trained public health workers as many in the existing workforce move toward retirement. METHODS This article characterizes annualized earnings from state and local public health practitioners in 2017, using data from the 2017 Public Health Workforce Interests and Needs Survey (PH WINS), which was fielded in fall/winter 2017 to more than 100 000 state and local public health practitioners in the United States. The response consisted of 47 604 public health workers for a response rate of 48%.We performed descriptive statistics, bivariate analyses, and interval-based regression techniques to explore relationships between annualized earnings, supervisory status, gender, years of experience, highest degree (and whether it was a public health degree), job classification, race/ethnicity, union/bargaining unit, paid as salary or hourly wage, setting, and region. RESULTS Higher supervisory status, higher educational attainment, white non-Hispanic race/ethnicity, male gender, salaried employment, bargaining unit (labor union) position, certain geographic regions, having a clinical/laboratory/other scientific position, and working in either a state health agency (SHA) or a large local health department (LHD) setting are all associated with higher salary. Having a public health degree versus a degree in another area did not appear to increase earnings. Being a person of color was associated with earning $4000 less annually than white peers (P < .001), all else being equal. The overall regression model showed a gender wage gap of about $3000 for women (P = .018). Supervisors, clinical and laboratory staff, public health sciences staff, and union staff also earned more than their counterparts. DISCUSSION As multiple factors continue to shape the public health workforce, including increasing racial/ethnic diversity, continued retirements of baby boomers, and the growth of bachelor's-level public health education, researchers should continue to monitor the gender and racial/ethnic pay gaps. This information should help the field of governmental public health as it endeavors to rebuild its capacity while current workers, many at the highest level of leadership, move on to retirement or other jobs. Public health leaders must prioritize equitable pay across gender and race/ethnicity within their own departments as they build their organizations' capacity to achieve health equity.

<p>This paper estimates the benefits of eliminating racial disparities in mortality rates and work weeks lost due to illness. Using data from the American Community Survey (2005–2007) and Minnesota vital statistics (2011–2015), we explore economic methodologies for estimating the costs of health disparities. The data reveal large racial disparities in both mortality and labor market non-participation arising from preventable diseases and illnesses. Estimates show that if racial disparities in preventable deaths were eliminated, the annualized number of lives saved ranges from 475 to 812, which translates into $1.2 billion to $2.9 billion per year in economic savings (in 2017 medical care inflation-adjusted dollars). After eliminating the unexplained racial disparities in labor market participation, an additional 4,217 to 9185 Minnesota residents would have worked each year, which equals $247.43 million to $538.85 million in yearly net benefits to Minnesota.</p>