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Through a standpoint feminist perspective (Harding 2009) I conducted a situational analysis (Clarke, 2015) that examined academic literature and cancer support discussion boards (DBs) to identify how Western biomedicine, specifically oncology, can integrate complementary and alternative medicine (CAM) to improve cancer treatment in children. The aims of this project were: 1) to identify the CAM treatments that are being used to alleviate the side effects from oncological treatments and/or treat pediatric cancers; 2) to compare the subjective experience of CAM to Western biomedicine of cancer patients who leave comments on Group Loop, Cancer Compass and Cancer Forums, which are online support groups (N=20). I used grounded theory and situational mapping to analyze discussion threads. The participants identified using the following CAM treatments: herbs, imagery, prayer, stinging nettle, meditation, mind-body therapies and supplements. The participants turned to CAM treatments when their cancer was late-stage or terminal, often as an integrative and not exclusively to treat their cancer. CAM was more "effective" than biomedical oncology treatment at improving their overall quality of life and functionality. We found that youth on discussion boards did not discuss CAM treatments like the adult participants, but all participants visited these sites for support and verification of their cancer treatments. My main integration recommendation is to combine mind-body CAM therapies with biomedical treatment. This project fills the gap in literature that ignores the ideas of vulnerable populations by providing the experiences of adult and pediatric cancer patients, and that of their families. It is applicable to areas of the social studies of medicine, patient care, and families suffering from cancer. KEYWORDS: Cancer; Complementary and Alternative Medicine; Situational Analysis; Standpoint Feminism
ContributorsEsposito, Sydney Maria (Author) / Martinez, AirÃÂn (Thesis director) / Hruschka, Daniel (Committee member) / School of Human Evolution and Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Background
The transition from the home to college is a phase in which emerging adults shift toward more unhealthy eating and physical activity patterns, higher body mass indices, thus increasing risk of overweight/obesity. Currently, little is understood about how changing friendship networks shape weight gain behaviors. This paper describes the recruitment, data collection, and data analytic protocols for the SPARC (Social impact of Physical Activity and nutRition in College) study, a longitudinal examination of the mechanisms by which friends and friendship networks influence nutrition and physical activity behaviors and weight gain in the transition to college life.
Methods
The SPARC study aims to follow 1450 university freshmen from a large university over an academic year, collecting data on multiple aspects of friends and friendship networks. Integrating multiple types of data related to student lives, ecological momentary assessments (EMAs) are administered via a cell phone application, devilSPARC. EMAs collected in four 1-week periods (a total of 4 EMA waves) are integrated with linked data from web-based surveys and anthropometric measurements conducted at four times points (for a total of eight data collection periods including EMAs, separated by ~1 month). University databases will provide student card data, allowing integration of both time-dated data on food purchasing, use of physical activity venues, and geographical information system (GIS) locations of these activities relative to other students in their social networks.
Discussion
Findings are intended to guide the development of more effective interventions to enhance behaviors among college students that protect against weight gain during college.
ContributorsBruening, Meg (Author) / Ohri-Vachaspati, Punam (Author) / Brewis, Alexandra (Author) / Laska, Melissa (Author) / Todd, Michael (Author) / Hruschka, Daniel (Author) / Schaefer, David (Author) / Whisner, Corrie M (Author) / Dunton, Genevieve (Author)
Created2016-08-30
Description
Understanding why animals form social groups is a fundamental aim of sociobiology. To date, the field has been dominated by studies of kin groups, which have emphasized indirect fitness benefits as key drivers of grouping among relatives. Nevertheless, many animal groups are comprised of unrelated individuals. These cases provide unique opportunities to illuminate drivers of social evolution beyond indirect fitness, especially ecological factors. This dissertation combines behavioral, physiological, and ecological approaches to explore the conditions that favor group formation among non-kin, using as a model the facultatively social carpenter bee, Xylocopa sonorina. Using behavioral and genetic techniques, I found that nestmates in this species are often unrelated, and that non-kin groups form following extensive inter-nest migration.Group living may arise as a strategy to mitigate constraints on available breeding space. To test the hypothesis that nest construction is prohibitively costly for carpenter bees, I measured metabolic rates of excavating bees and used imaging techniques to quantify nest volumes. From these measurements, I found that nest construction is highly energetically costly, and that bees who inherit nests through social queuing experience substantial energetic savings. These costs are exacerbated by limitations on the reuse of existing nests. Using repeated CT scans of nesting logs, I examined changes in nest architecture over time and found that repeatedly inherited tunnels become indefensible to intruders, and are subsequently abandoned. Together, these factors underlie intense competition over available breeding space. The imaging analysis of nesting logs additionally revealed strong seasonal effects on social strategy, with social nesting dominating during winter. To test the hypothesis that winter social nesting arises from intrinsic physiological advantages of grouping, I experimentally manipulated social strategy in overwintering bees. I found that social bees conserve heat and body mass better than solitary bees, suggesting fitness benefits to grouping in cold, resource-scarce conditions. Together, these results suggest that grouping in X. sonorina arises from dynamic strategies to maximize direct fitness in response to harsh and/or competitive conditions. These studies provide empirical insights into the ecological conditions that favor non-kin grouping, and emphasize the importance of ecology in shaping sociality at its evolutionary origins.
ContributorsOstwald, Madeleine (Author) / Fewell, Jennifer H (Thesis advisor) / Amdam, Gro (Committee member) / Harrison, Jon (Committee member) / Pratt, Stephen (Committee member) / Kapheim, Karen (Committee member) / Arizona State University (Publisher)
Created2022
Description
High throughput transcriptome data analysis like Single-cell Ribonucleic Acid sequencing (scRNA-seq) and Circular Ribonucleic Acid (circRNA) data have made significant breakthroughs, especially in cancer genomics. Analysis of transcriptome time series data is core in identifying time point(s) where drastic changes in gene transcription are associated with homeostatic to non-homeostatic cellular transition (tipping points). In Chapter 2 of this dissertation, I present a novel cell-type specific and co-expression-based tipping point detection method to identify target gene (TG) versus transcription factor (TF) pairs whose differential co-expression across time points drive biological changes in different cell types and the time point when these changes are observed. This method was applied to scRNA-seq data sets from a SARS-CoV-2 study (18 time points), a human cerebellum development study (9 time points), and a lung injury study (18 time points). Similarly, leveraging transcriptome data across treatment time points, I developed methodologies to identify treatment-induced and cell-type specific differentially co-expressed pairs (DCEPs). In part one of Chapter 3, I presented a pipeline that used a series of statistical tests to detect DCEPs. This method was applied to scRNA-seq data of patients with non-small cell lung cancer (NSCLC) sequenced across cancer treatment times. However, this pipeline does not account for correlations among multiple single cells from the same sample and correlations among multiple samples from the same patient. In Part 2 of Chapter 3, I presented a solution to this problem using a mixed-effect model. In Chapter 4, I present a summary of my work that focused on the cross-species analysis of circRNA transcriptome time series data. I compared circRNA profiles in neonatal pig and mouse hearts, identified orthologous circRNAs, and discussed regulation mechanisms of cardiomyocyte proliferation and myocardial regeneration conserved between mouse and pig at different time points.
ContributorsNyarige, Verah Mocheche (Author) / Liu, Li (Thesis advisor) / Wang, Junwen (Thesis advisor) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2022
Description
Advancements in high-throughput biotechnologies have generated large-scale multi-omics datasets encompassing diverse dimensions such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics, and phenomics. Traditionally, statistical and machine learning-based approaches utilize single-omics data sources to uncover molecular signatures, dissect complicated cellular mechanisms, and predict clinical results. However, to capture the multifaceted pathological mechanisms, integrative multi-omics analysis is needed that can provide a comprehensive picture of the disease. Here, I present three novel approaches to multi-omics integrative analysis. I introduce a single-cell integrative clustering method, which leverages multi-omics to enhance the resolution of cell subpopulations. Applied to a Cellular Indexing of Transcriptomes and Epitopes (CITE-Seq) dataset from human Acute Myeloid Lymphoma (AML) and control samples, this approach unveiled nuanced cell populations that otherwise remain elusive. I then shift the focus to a computational framework to discover transcriptional regulatory trios in which a transcription factor binds to a regulatory element harboring a genetic variant and subsequently differentially regulates the transcription level of a target gene. Applied to whole-exome, whole-genome, and transcriptome data of multiple myeloma samples, this approach discovered synergetic cis-acting and trans-acting regulatory elements associated with tumorigenesis. The next part of this work introduces a novel methodology that leverages the transcriptome and surface protein data at the single-cell level produced by CITE-Seq to model the intracellular protein trafficking process. Applied to COVID-19 samples, this approach revealed dysregulated protein trafficking associated with the severity of the infection.
ContributorsMudappathi, Rekha (Author) / Liu, Li (Thesis advisor) / Dinu, Valentin (Committee member) / Sun, Zhifu (Committee member) / Arizona State University (Publisher)
Created2023
Description
Speciation, or the process by which one population diverges into multiple populations that can no longer interbreed with each other, has brought about the incredible diversity of life. Mechanisms underlying this process can be more visible in the early stages of the speciation process. The mechanisms that restrict gene flow in highly mobile species with no absolute barriers to dispersal, especially marine species, are understudied. Similarly, human impacts are reshaping ecosystems globally, and we are only just beginning to understand the implications of these rapid changes on evolutionary processes. In this dissertation, I investigate patterns of speciation and evolution in two avian clades: a genus of widespread tropical seabirds (boobies, genus Sula), and two congeneric passerine species in an urban environment (cardinals, genus Cardinalis). First, I explore the prevalence of gene flow across land barriers within species and between sympatric species in boobies. I found widespread evidence of gene flow over all land barriers and between 3 species pairs. Next, I compared the effects of urbanization on the spatial distributions of two cardinal species, pyrrhuloxia (Cardinalis sinuatus) and northern cardinals (Cardinalis cardinalis), in Tucson, Arizona. I found that urbanization has different effects on the spatial distributions of two closely related species that share a similar environmental niche, and I identified environmental variables that might be driving this difference. Then I tested for effects of urbanization on color and size traits of these two cardinal species. In both of these species, urbanization has altered traits involved in signaling, heat tolerance, foraging, and maneuverability. Finally, I tested for evidence of selection on the urban populations of both cardinal species and found evidence of both parallel selection and introgression between the species, as well as selection on different genes in each species. The functions of the genes that experienced positive selection suggest that light at night, energetics, and air pollution may have acted as strong selective pressures on these species in the past. Overall, my dissertation emphasizes the role of introgression in the speciation process, identifies environmental stressors faced by wildlife in urban environments, and characterizes their evolutionary responses to those stressors.
ContributorsJackson, Daniel Nelson (Author) / McGraw, Kevin J (Thesis advisor) / Amdam, Gro (Committee member) / Sweazea, Karen (Committee member) / Taylor, Scott (Committee member) / Arizona State University (Publisher)
Created2023
Description
Social norms are unwritten behavioral codes. They direct individual behaviors, facilitate interpersonal coordination and cooperation, and lead to variation among human populations. Understanding how norms are maintained and how they change is critical for understanding human evolutionary psychology, social organization, and cultural change. This dissertation uses a mathematical model and a field study to answer two questions: First, what factors determine the content and dynamics of a social norm? Second, how do people make decisions in a normative context? The mathematical model finds that contrary to the popular belief that even arbitrary or deleterious social norms can be maintained once established because deviants suffer coordination failures and social sanctions, norms with continuously varying options cannot be maintained by the pressure to do what others do. Instead, continuous norms evolve to the optimum determined by environmental pressure, individual preferences, or cognitive processes. Therefore, the content of norms across human societies may be less historically constrained than previously assumed. The field study shows that unlike what rational choice theory predicts, people in a small-scale subsistence society do not calculate the ecological and social payoffs of different behaviors in a normative context, even when they have the information to do so. Instead, they rely heavily on social information about what others do. This decision-making algorithm, together with mental categorization that ignores small deviations, and cognitive biases that favor the division prescribed by the norm, maintain an ecologically inefficient and widely disliked cooperative surplus division norm in a Derung village, Dizhengdang, in Yunnan, China.
ContributorsYan, Minhua (Author) / Boyd, Robert (Thesis advisor) / Mathew, Sarah (Thesis advisor) / Hruschka, Daniel (Committee member) / Arizona State University (Publisher)
Created2023
Description
Contact tracing was deployed widely during the COVID-19 pandemic to attempt to stop the spread of SARS Co-V-2. This dissertation investigates the research on contact tracing from a scientometric perspective and looks qualitatively at how case investigators and contact tracers conducted public health practice during the pandemic. Through approaching the public health practice of contact tracing from both a broad, top-down angle, and an on the ground experiential approach, this dissertation provides insight into the issues facing contact tracing as a public health tool.
ContributorsWhite, Alexandra C. (Author) / Jehn, Megan (Thesis advisor) / Hruschka, Daniel (Committee member) / Gaughan, Monica (Committee member) / Arizona State University (Publisher)
Created2022
Description
Latest estimates show that roughly 188 individuals in the United States die everyday due to an opioid-related overdose. This dissertation explores three avenues for
mitigating opioid use disorder (OUD) and the opioid epidemic in the United States (1.)
How can researchers and public health professionals identify areas most in need of
treatment for OUD in an easy-to-use and publicly accessible interface?; (2.) What do
practitioners see as opportunities for reducing barriers to treatment?; and (3.) Why do
differences in opioid mortality exist between demographic groups? To address question
one, I developed an interactive web-based to assist in identifying those counties with the
greatest unmet need of medically assisted treatment (MAT). To answer question two, I
conducted a study of stakeholders (medical providers, peer support specialists, public
health practitioners, etc.) in four New Mexico counties with high unmet need of MAT. to
identify cultural and structural barriers to MAT provision in underserved areas as well as
opportunities for improving access. To answer the third question. I conducted a
systematic review of peer-reviewed literature and government reports to identify how
previous research accounts for race/ethnic and sex disparities in opioid-related
mortality. While many opioid mortality studies show demographic differences, little is
known about why they exist. According to the findings of this systematic review, research
needs to go beyond identifying demographic differences in opioid-related mortality to
understand the reasons for those differences to reduce these inequities.
ContributorsDrake, Alexandria (Author) / Hruschka, Daniel (Thesis advisor) / Jehn, Megan (Committee member) / Scott, Mary Alice (Committee member) / Arizona State University (Publisher)
Created2023
Description
Previous work suggests that lower-income individuals are more likely to engage in mutual aid as a means to manage risk, giving rise to a psychology that is other-oriented, including an empathetic disposition and a proclivity to help people in need. While no study has directly investigated whether helping in times of need increases dispositional empathic concern over time, this assumption is deep-seated among social psychologists. Employing a two-year longitudinal survey of US adults (N = 915), I show that people who experience more needs report helping others when in need a greater number of times, in turn leading to a small but positive increase in their empathetic disposition. This study also identifies the types of needs that elicit empathic concern (i.e., those that arise from unpredictable sources of risk), and shows why cultivating an empathetic disposition is likely to pay off in the long run: those who provide help are more likely to receive help during future times of need. Moreover, this study identifies the types of targets for whom providing help might cultivate an empathetic disposition: those with whom people are likely to share lower interdependence. While previous theoretical frameworks posit that empathic concern selectively directs investment towards interdependent others, providing help to non-interdependent targets might allow people to build positive interdependence with prospective risk pooling partners. Cultivating an empathetic disposition and building interdependence with prospective risk pooling partners can allow people to manage needs that arise from unpredictable sources of risk.
ContributorsGuevara Beltran, Diego (Author) / Aktipis, Athena (Thesis advisor) / Hruschka, Daniel (Committee member) / Kenrick, Douglas (Committee member) / Shiota, Michelle (Committee member) / Arizona State University (Publisher)
Created2023