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.

With the emergence of programs that focus on socio-emotional regulation through online intervention, our focus is to move beyond the current literature to look at how personality might help to identify those in need of such an intervention, while also assessing if personality may moderate the overall efficacy of the treatment in middle-aged adults. In particular, our focus is on the established improvements that similar programs have shown to have on positive affect (PA), negative affect (NA), and emotional reactivity (ER). Through a randomized controlled trial, this research examines whether an online social intelligence training (SIT) program improves socio-emotional regulation compared to an attention-control (AC) condition. During the pre- and post-test phases of the study, participants (N = 230) completed a questionnaire, along with online surveys for 14-days that included measures of social connectedness, emotional awareness, and perspective-taking. Our analysis, while lacking significant findings in the way of PA and NA, shed light on how SIT programs can improve ER, while personality can simultaneously predict baseline levels of ER and moderate the efficacy of the program.