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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The primary objective of this study was to develop the Perceived Control of the Attribution Process Scale (PCAPS), a measure of metacognitive beliefs of causality, or a perceived control of the attribution process. The PCAPS included two subscales: perceived control of attributions (PCA), and awareness of the motivational consequences of

The primary objective of this study was to develop the Perceived Control of the Attribution Process Scale (PCAPS), a measure of metacognitive beliefs of causality, or a perceived control of the attribution process. The PCAPS included two subscales: perceived control of attributions (PCA), and awareness of the motivational consequences of attributions (AMC). Study 1 (a pilot study) generated scale items, explored suitable measurement formats, and provided initial evidence for the validity of an event-specific version of the scale. Study 2 achieved several outcomes; Study 2a provided strong evidence for the validity and reliability of the PCA and AMC subscales, and showed that they represent separate constructs. Study 2b demonstrated the predictive validity of the scale and provided support for the perceived control of the attribution process model. This study revealed that those who adopt these beliefs are significantly more likely to experience autonomy and well-being. Study 2c revealed that these constructs are influenced by context, yet they lead to adaptive outcomes regardless of this contextual-specificity. These findings suggest that there are individual differences in metacognitive beliefs of causality and that these differences have measurable motivational implications.
ContributorsFishman, Evan Jacob (Author) / Nakagawa, Kathryn (Committee member) / Husman, Jenefer (Committee member) / Graham, Steve (Committee member) / Moore, Elsie (Committee member) / Arizona State University (Publisher)
Created2014
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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