Theses and Dissertations

Graduating from college is an important time of life transitions and career development for undergraduates and their future. Future self-identification, the connection between an individual’s current and future self, can negatively predict depression and utilize self-control as a mechanism to achieve later academic goals. Investigating an individual’s future self- identification, depression scores, and behavioral outcomes in the face of the COVID-19 pandemic can help optimize college graduate success in an uncertain world. The present study aimed to (1) determine if earlier future self-identification moderated the changes between later outcomes (e.g., depression, perceived alcohol consumption, and academic and career goals) from pre-COVID-19 to during COVID-19, (2) investigate if psychological resources (e.g., self-control and emotion regulation) had any intermediary effects between earlier future self-identification and later depression and behavioral outcomes during the pandemic, and (3) test for any moderation effects of future self-identification on the relationship between available psychological resources before COVID-19 and during COVID-19. The present research demonstrated that students with greater earlier future self-identification were less likely to change their academic and career goals and were less likely to experience symptoms of depression during the pandemic. Additionally, self-control was demonstrated as an intermediary factor between earlier future self-identification and later academic and career goal changes. These findings may help college graduates develop resilience in other stressful situations.

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other Backward Classes.” This method obscures the diversity of experiences, indicators of well-being, and health outcomes between castes, tribes, and other communities in the “scheduled” category. This study analyzes data on 699,686 women from 4,260 castes, tribes and communities in the 2015-2016 Demographic and Health Survey of India to: (1) examine the diversity within and overlap between general, government-defined community categories in both wealth, infant mortality, and education, and (2) analyze how infant mortality is related to community category membership and socioeconomic status (measured using highest level of education and household wealth). While there are significant differences between general, government-defined community categories (e.g., scheduled caste, backward class) in both wealth and infant mortality, the vast majority of variation between communities occurs within these categories. Moreover, when other socioeconomic factors like wealth and education are taken into account, the difference between general, government-defined categories reduces or disappears. These findings suggest that focusing on measures of education and wealth at the household level, rather than general caste categories, may more accurately target those individuals and households most at risk for poor health outcomes. Further research is needed to explain the mechanisms by which discrimination affects health in these populations, and to identify sources of resilience, which may inform more effective policies.