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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This study aimed to identify the emotional/affective sources of discrepancies between physical activity behavior and a widely used self-perception measure of physical activity motivation. Overweight women (body mass index [BMI] ≥ 25 kg/m2, 18-64 years of age; N=37) were recruited from Arizona State University community through flyers and online newsletters.

This study aimed to identify the emotional/affective sources of discrepancies between physical activity behavior and a widely used self-perception measure of physical activity motivation. Overweight women (body mass index [BMI] ≥ 25 kg/m2, 18-64 years of age; N=37) were recruited from Arizona State University community through flyers and online newsletters. Participants wore a SenseWear accelerometer for 6 nights and 7 days and followed their normal patterns of daily living. Participants then completed a single lab visit and verbally responded to questions from the Behavorial Regulation Exercise Questionnaire (BREQ-2) while being video and audio recorded. Captured emotional responses were evaluated with facial recognition software (Noldus FaceReader). Discrepancies between BREQ-2 responses and physical activity behavior were associated with happiness and sadness emotional responses extracted from the facial recognition software using regression-based analyses. Results indicated an association between monitored physical activities and captured emotional response - specifically sadness - and that as intensity in physical activity increases, motivation increases. Associations between happiness/sadness and physical activity were not observed for all intensities of physical activity. A marginally significant association was observed for amotivation and sedentary, light-intensity physical activity, and moderate-vigorous physical activity in the sample. This study demonstrates a proof-of-concept for the integration of an empirical evaluation of happiness and sadness emotional states into the relationship between physical activity motivation and behavior.
ContributorsBryant, Sarah (Author) / Buman, Matthew P (Thesis advisor) / Chisum, Jack W (Committee member) / Hekler, Eric (Committee member) / Arizona State University (Publisher)
Created2016
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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