Theses and dissertations

This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Does Sleep Predict Children's Academic Success?

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Academic success in childhood is crucial for later academic, occupational, and life success (Heckman, 2006; Kuncel, Hezlett, & Ones, 2004; Spengler, Brunner, Damian, Lüdtke, Martin, & Roberts, 2015). Recent research suggests sleep is important for academic success but lacks objective measures of sleep (Buckhalt, El-Sheikh, Keller, & Kelly, 2009; Curcio,…

Academic success in childhood is crucial for later academic, occupational, and life success (Heckman, 2006; Kuncel, Hezlett, & Ones, 2004; Spengler, Brunner, Damian, Lüdtke, Martin, & Roberts, 2015). Recent research suggests sleep is important for academic success but lacks objective measures of sleep (Buckhalt, El-Sheikh, Keller, & Kelly, 2009; Curcio, Ferrara, & De Gennaro, 2006; Dewald, Meijer, Oort, Kerkhof, & Bögels, 2010; Philbrook, Hinnant, Elmore-Staton, Buckhalt, & El-Sheikh, 2017). The purpose of this study was to examine the relations between sleep and academic success among children through objective measures of sleep in order to expand on the literature. Our sample consisted of 381 twins (50.4% male; 56% Caucasian; 36.5% same sex dizygotic) participating in an 8-year assessment from a longitudinal twin study. Actigraphy was used to assess sleep while various measures were used to assess academic success. A series of mixed model regressions were used to test the main predictions, with family entered as a random effect. Sex, age, Hispanic, SES, and zygosity were controlled for. Significant negative relations were revealed between sleep latency and reading and sleep latency and school liking. Additionally, SES was the most consistent significant positive predictor of our measures of academic success. These results suggest sleep and effects of SES should be considered when developing ways to help children’s school performance.
ContributorsAlvarez, Rachel Marie (Author) / Valiente, Carlos (Thesis director) / Doane, Leah (Committee member) / School of Criminology and Criminal Justice (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Ethnic Discrimination, Socioeconomic Status, and Health in India

Description

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…

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.
ContributorsClauss, Colleen (Author) / Hruschka, Daniel (Thesis director) / Davis, Mary (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor) / Department of Psychology (Contributor)
Created2022-05