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Financial stress has been found to contribute to mental health deterioration associated with job loss. This study examined whether specific types of income support programs (e.g., unemployment benefits and welfare) reduce the negative impacts of job loss on middle-aged women’s mental health in the United States. Two samples of women previously employed before their mental health assessments in their 40s and 50s were selected from the National Longitudinal Survey of Youth 1979 (NLSY79). We conducted regression analysis to predict their mental health scores using employment and income support program status. The model also controlled for baseline health before job loss, socioeconomic status, and demographic and family life characteristics. Compared to their continuously employed counterparts, 50 +  women who had job loss without unemployment benefits had significantly worse mental health. However, those receiving unemployment benefits did not have significantly worse mental health. Unemployment benefits’ ameliorating effect was not found in the 40 +  sample; and welfare programs did not have similar mental health effects. Our findings suggest that certain types of income support policies are beneficial to the mental health of certain cohorts of middle-aged women. For different groups of women, additional and alternative measures are needed to reduce the mental health damage of job loss.

This study examines how the structure of referent networks, or the social network defined by knowing others’ reward levels, affects perceptions of distributive justice. The homogeneity of rewards in the referent network, the amount of inequality in the referent network, and an individual’s reward level are all associated with distributive justice perceptions. Several moderating relationships are also examined.

We relied on data from a controlled laboratory experiment to test a series of theoretically derived hypotheses.

The study shows that several aspects about the structure of the referent network are important for shaping perceptions of distributive justice. Specifically, the reward heterogeneity and amount of inequality in the network are found to be negatively associated with distributive justice, while reward levels are found to be positively associated with distributive justice. Furthermore, the effect of reward levels on distributive justice is moderated by both (i) the presence of a referential standard for rewards and (ii) the amount of inequality in the network.

While being among the first studies to demonstrate effects of referent networks on perceptions of fairness, it is unclear how group memberships combine with referent network effects and which factors may blur these relationships in uncontrolled environments. Subsequent scholarship on the effect of referent networks on justice perceptions should leverage multiple data sources.

Research on the effects of referents on justice perceptions has focused on particular referent individuals. We recast this issue in terms of referent networks, which highlights the empirical reality that individuals have a variety of sources or alters which could operate as referents.

Since the development of the COVID-19 vaccinations, questions surrounding race have been prominent in the literature on vaccine uptake. Early in the vaccine rollout, public health officials were concerned with the relatively lower rates of uptake among certain racial/ethnic minority groups. We suggest that this may also be patterned by racial/ethnic residential segregation, which previous work has demonstrated to be an important factor for both health and access to health care.

In this study, we examine county-level vaccination rates, racial/ethnic composition, and residential segregation across the U.S. We compile data from several sources, including the American Community Survey (ACS) and Centers for Disease Control (CDC) measured at the county level.

We find that just looking at the associations between racial/ethnic composition and vaccination rates, both percent Black and percent White are significant and negative, meaning that higher percentages of these groups in a county are associated with lower vaccination rates, whereas the opposite is the case for percent Latino. When we factor in segregation, as measured by the index of dissimilarity, the patterns change somewhat. Dissimilarity itself was not significant in the models across all groups, but when interacted with race/ethnic composition, it moderates the association. For both percent Black and percent White, the interaction with the Black-White dissimilarity index is significant and negative, meaning that it deepens the negative association between composition and the vaccination rate.

The analysis is only limited to county-level measures of racial/ethnic composition and vaccination rates, so we are unable to see at the individual-level who is getting vaccinated.

We find that segregation moderates the association between racial/ethnic composition and vaccination rates, suggesting that local race relations in a county helps contextualize the compositional effects of race/ethnicity.