Matching Items (158)
Description
Prostate cancer is the second most common kind of cancer in men. Fortunately, it has a 99% survival rate. To achieve such a survival rate, a variety of aggressive therapies are used to treat prostate cancers that are caught early. Androgen deprivation therapy (ADT) is a therapy that is given in cycles to patients. This study attempted to analyze what factors in a group of 79 patients caused them to stick with or discontinue the treatment. This was done using naïve Bayes classification, a machine-learning algorithm. The usage of this algorithm identified high testosterone as an indicator of a patient persevering with the treatment, but failed to produce statistically significant high rates of prediction.
ContributorsMillea, Timothy Michael (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Sleep diaries and actigraphy are two common methods used to assess sleep subjectively and objectively, respectively. Compared to the gold standard of sleep assessment, polysomnography, sleep diaries and actigraphic methods are more cost-effective and simpler to use. This study aimed to compare the sleep parameters derived from actigraphy and sleep diaries (total sleep time, sleep onset latency, number of awakenings, wake after sleep onset, percentage of time awake, and sleep efficiency). Based on results from previous similar studies, it was hypothesized that the sleep diaries would overestimate the total sleep time parameter and underestimate wake parameters. Twenty healthy young adults without sleep problems volunteered to participate. The participants wore an Actiwatch 2 on their wrist and filled out a sleep diary every morning for the duration of six days. A high intraclass correlation coefficient value between subjective and objective sleep was found for the parameter total sleep time, even though total sleep time was found to be slightly overestimated by the sleep diaries. Sleep onset latency, wake after sleep onset, number of awakenings, percentage of time awake, and sleep efficiency were underestimated by the sleep diaries and did not have high correlation values. Based off of the ICC results, there does not seem to be a strong correlation between the Actiwatch 2 and the sleep diaries, but looking at the Bland Altman plots, there seems to be agreement between the methods.
ContributorsRameshkumar, Aarthi (Author) / Buman, Matthew (Thesis director) / Petrov, Megan (Committee member) / Diaz-Piedra, Carolina (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2016-12
Description
Recent research has confirmed and revealed many physical and mental benefits of yoga. The practice of yoga has spread throughout the western world, where it is widely used for the purpose of exercise and fitness. Due to its rise in popularity, there is a need for research regarding the energy expenditure required for different types of yoga. The majority of the literature cites yoga as being an effective exercise for light intensity activity, but there are not as many studies attempting to determine if there are postures and sequences that can meet the requirements for moderate physical activity. In addition, there is a need to validate mobile devices with which to measure energy expenditure (EE) that are compatible with the dynamic movements that occur during yoga. The purpose of this study was to measure energy expenditure of twenty-two yoga practitioners of varying experience during a 30-minute Vinyasa flow yoga practice and from this data collection determine: if an ashtanga-based vinyasa yoga class meets the criteria for moderate intensity physical activity, the reliability between the Actigraph and Oxycon Mobile and the validity of an Actigraph GT3X device worn on the hip in estimating energy expenditure for ashtanga-based vinyasa flow yoga. The Actigraph GT3X and the Oxycon mobile were used to measure energy expenditure. Mean values for energy expenditure recorded by the Oxycon and Actigraph were 3.19 ± 0.42 METs and 1.16 ± 0.23 METs respectively, exhibiting a significant difference in data collection. There was no correlation between the values recorded by the two devices, indicating that the Actigraph was not consistent with the Oxycon Mobile (previously validated for measurement of EE). Results of this study indicate that this Vinyasa flow yoga sequence does satisfy the criteria for moderate intensity physical activity as defined by ACSM with an average EE of 3.19 ± 0.42 METs, and that the Actigraph GT3X is not an accurate device for measurement of EE for yoga.
ContributorsHand, Lindsay Gabrielle (Author) / Huberty, Jennifer (Thesis director) / Buman, Matthew (Committee member) / School of Nutrition and Health Promotion (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Regional and geographical differences may explain variability in menopausal symptom occurrence due to development of climate-specific thermoneutral zones leading to population-specific hot flash frequencies. Limited information available regarding menopausal symptoms in underserved women living in extreme heat.
Understanding the perception of menopausal symptoms in underserved women living in extreme heat regions to identify if heat impacts perception of menopausal symptoms was the objective of this study. Women in free, low-income, and homeless clinics in Phoenix were surveyed during summer and winter months using a self-administered, written questionnaire including demographic, climate and menopause related questions, including the Green Climacteric Scale (GCS).
A total of 139 predominantly Hispanic (56 %), uninsured (53 %), menopausal (56 %), mid-aged (mean 49.9, SD 10.3) women were surveyed— 36% were homeless or in shelters. Most women were not on menopausal hormone therapy (98 %). Twenty-two percent reported hot flashes and 26% night sweats. Twenty-five percent of women reported previously becoming ill from heat. More women thought season influenced menopausal symptoms during summer than winter (41 % vs. 14 %, p = 0.0009). However, majority of women did not think temperature outside influenced their menopausal symptoms and that did not differ by season (73 % in winter vs. 60% in summer, p=0.1094). No statistically significant differences seen for vasomotor symptoms between winter and summer months.
Regional and geographical differences may be key in understanding the variability in menopausal symptoms. Regardless of season, the menopausal, underserved and homeless women living in Arizona reported few vasomotor symptoms. In the summer, they were more likely to report that the season influenced their menopausal symptoms rather than temperature suggesting an influence of the season on symptom perception.
ContributorsMukarram, Mahnoor (Author) / Hondula, David M. (Thesis director) / Kling, Juliana (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods and at varying times across days and/or months over the course of one year (July 15, 2020–July 14, 2021), allowing the team to study the impacts of the surface treatment under various weather conditions.
ContributorsMiddel, Ariane (Author) / Vanos, Jennifer K. (Author) / Hondula, David M. (Author) / Kaloush, Kamil (Author) / Sailor, David (Author) / Medina, Jose R. (Jose Roberto) (Author) / Schneider, Florian (Author) / Ortiz, Johny Cordova (Author) / Campbell, Bill (Author) / Epel, Erin (Contributor) / Rice, Brendan (Contributor) / Garcia, Ruth (Contributor) / Phoenix (Ariz.). Street Transportation Department (Contributor) / City of Phoenix (Funder) / Industrial Development Authority of the County of Maricopa (Funder) / Julie Ann Wrigley Global Institute of Sustainability (Funder) / Arizona State University. Healthy Urban Environments Program (Contributor)
Created2021-09
Description
Meditation app usage is associated with decreases in stress, anxiety, and depression symptoms. Many meditation app subscribers, however, quickly abandon or reduce their app usage. This dissertation presents three manuscripts which 1) determined the behavioral, demographic, and socioeconomic factors associated with the abandonment of a meditation app, Calm, during the COVID-19 pandemic, 2) determined which participant characteristics predicted meditation app usage in the first eight weeks after subscribing, and 3) determined if changes in stress, anxiety, and depressive symptoms from baseline to Week 8 predicted meditation app usage from Weeks 8-16. In Manuscript 1, a survey was distributed to Calm subscribers in March 2020 that assessed meditation app behavior and meditation habit strength, and demographic information. Cox proportional hazards regression models were estimated to assess time to app abandonment. In Manuscript 2, new Calm subscribers completed a baseline survey on participants’ demographic and baseline mental health information and app usage data were collected over 8 weeks. In Manuscript 3, new Calm subscribers completed a baseline and Week 8 survey on demographic and mental health information. App usage data were collected over 16 weeks. Regression models were used to assess app usage for Manuscripts 2 and 3. Findings from Manuscript 1 suggest meditating after an existing routine decreased risk of app abandonment for pre-pandemic subscribers and for pandemic subscribers. Additionally, meditating “whenever I can” decreased risk of abandonment among pandemic subscribers. No behavioral factors were significant predictors of app abandonment among the long-term subscribers. Findings from Manuscript 2 suggest men had more days of meditation than women. Mental health diagnosis increased average daily meditation minutes. Intrinsic motivation for meditation increased the likelihood of completing any meditation session, more days with meditation sessions, and more average daily meditation minutes. Findings from Manuscript 3 suggest improvements in stress increased average daily meditation minutes. Improvements in depressive symptoms decreased daily meditation minutes. Evidence from this three-manuscript dissertation suggests meditation cue, time of day, motivation, symptom changes, and demographic and socioeconomic variables may be used to predict meditation app usage.
ContributorsSullivan, Mariah (Author) / Stecher, Chad (Thesis advisor) / Huberty, Jennifer (Committee member) / Buman, Matthew (Committee member) / Larkey, Linda (Committee member) / Chung, Yunro (Committee member) / Arizona State University (Publisher)
Created2022
Description
How is knowledge created at the intersections between basic science, biotechnology, and industry? Gene drives are an interesting example, as they combine a long-standing interest with a recent technological breakthrough and a new set of commercial applications. Gene drives are genes engineered such that they are preferentially inherited at a frequency greater than the typical Mendelian fifty percent ratio. During the historical and conceptual evolution of gene drives beginning in the 1960s, there have been many innovations and publications. Along with that, gene drive science developed considerable public attention, explosion of new scientists, and variation in the way the topic is discussed. It is now time to look at this new organization of science using a systematic approach to characterize the system that has enabled knowledge to grow in this scientific field. This project breaks new ground in how knowledge advances in genetic engineering science, and how scientists understand what a “gene drive” is through analysis of language, communities, and other social factors. In effect, this research will advance multiple fields and enable a deeper understanding of knowledge and complexity. This project documents patterns of publication, collaborative relationships, linguistic variation, innovation, and knowledge expansion. The results of computational analysis provide an in-depth and complete characterization of the structure, dynamics, and evolution of scientific knowledge found in the gene drive technology. Further, time series analysis of the multiple layers of discourse enabled a diachronic connective mapping of collaborative relationships and tracked linguistic variation and change, highlighting where ambiguous language may appear, improving and creating more cohesive scientific language.
Overall, depicting the structure, dynamics, and evolution of scientific knowledge during a novel eruption of scientific complexity can shed light on the factors that can lead to: (1) improved scientific communication, (2) reduction of scientific progress, (3) new knowledge, and (4) novel collaborative relationships. Therefore, characterizing the current technological, methodological, and social contexts that can influence scientific knowledge.
ContributorsOToole, Cody Lane (Author) / Laubichler, Manfred (Thesis advisor) / Collins, James P (Committee member) / Simeone, Michael (Committee member) / Evans, James (Committee member) / Arizona State University (Publisher)
Created2021
Description
Infrastructure systems are facing non-stationary challenges that stem from climate change and the increasingly complex interactions between the social, ecological, and technological systems (SETSs). It is crucial for transportation infrastructures—which enable residents to access opportunities and foster prosperity, quality of life, and social connections—to be resilient under these non-stationary challenges. Vulnerability assessment (VA) examines the potential consequences a system is likely to experience due to exposure to perturbation or stressors and lack of the capacity to adapt. Post-fire debris flow and heat represent particularly challenging problems for infrastructure and users in the arid U.S. West. Post-fire debris flow, which is manifested with heat and drought, produces powerful runoff threatening physical transportation infrastructures. And heat waves have devastating health effects on transportation infrastructure users, including increased mortality rates. VA anticipates the potential consequences of these perturbations and enables infrastructure stakeholders to improve the system's resilience. The current transportation climate VA—which only considers a single direct climate stressor on the infrastructure—falls short of addressing the wildfire and heat challenges. This work proposes advanced transportation climate VA methods to address the complex and multiple climate stressors and the vulnerability of infrastructure users. Two specific regions were chosen to carry out the progressive transportation climate VA: 1) the California transportation networks’ vulnerability to post-fire debris flows, and 2) the transportation infrastructure user’s vulnerability to heat exposure in Phoenix.
ContributorsLi, Rui (Author) / Chester, Mikhail V. (Thesis advisor) / Middel, Ariane (Committee member) / Hondula, David M. (Committee member) / Pendyala, Ram (Committee member) / Arizona State University (Publisher)
Created2022
Description
This dissertation research project developed as an urgent response to physical inactivity, which has resulted in increased rates of obesity, diabetes, and metabolic disease worldwide. Incorporating enough daily physical activity (PA) is challenging for most people. This research aims to modulate the brain's reward systems to increase motivation for PA and, thus, slow the rapid increase in sedentary lifestyles. Transcranial direct current stimulation (tDCS) involves brain neuromodulation by facilitating or inhibiting spontaneous neural activity. tDCS applied to the dorsolateral prefrontal cortex (DLPFC) increases dopamine release in the striatum, an area of the brain involved in the reward–motivation pathways. I propose that a repeated intervention, consisting of tDCS applied to the DLPFC followed by a short walking exercise stimulus, enhances motivation for PA and daily PA levels in healthy adults. Results showed that using tDCS followed by short-duration walking exercise may enhance daily PA levels in low-physically active participants but may not have similar effects on those with higher levels of daily PA. Moreover, there was a significant effect on increasing intrinsic motivation for PA in males, but there were no sex-related differences in PA. These effects were not observed during a 2-week follow-up period of the study after the intervention was discontinued. Further research is needed to confirm and continue exploring the effects of tDCS on motivation for PA in larger cohorts of sedentary populations. This novel research will lead to a cascade of new evidence-based technological applications that increase PA by employing approaches rooted in biology.
ContributorsRuiz Tejada, Anaissa (Author) / Katsanos, Christos (Thesis advisor) / Neisewander, Janet (Committee member) / Sadleir, Rosalind (Committee member) / Buman, Matthew (Committee member) / Arizona State University (Publisher)
Created2023