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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
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
Description
Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of the predicted robustness of CD8+ T cell responses in 23 different populations. The robustness of CD8+ T cell responses in a given population was modeled by predicting the efficiency of endemic MHC-I protein variants to present peptides derived from SARS-CoV-2 proteins to circulating T cells. To accomplish this task, an algorithm, called EnsembleMHC, was developed to predict viral peptides with a high probability of being recognized by CD T cells. It was discovered that there was significant variation in the efficiency of different MHC-I protein variants to present SARS-CoV-2 derived peptides, and countries enriched with variants with high presentation efficiency had significantly lower mortality rates. Second, a biophysics-based MHC-I peptide prediction algorithm was developed. The MHC-I protein is the most polymorphic protein in the human genome with polymorphisms in the peptide binding causing striking changes in the amino acid compositions, or binding motifs, of peptide species capable of stable binding. A deep learning model, coined HLA-Inception, was trained to predict peptide binding using only biophysical properties, namely electrostatic potential. HLA-Inception was shown to be extremely accurate and efficient at predicting peptide binding motifs and was used to determine the peptide binding motifs of 5,821 MHC-I protein variants. Finally, the impact of stalk glycosylations on NL63 protein dynamics was investigated. Previous data has shown that coronavirus crown glycans play an important role in immune evasion and receptor binding, however, little is known about the role of the stalk glycans. Through the integration of computational biology, experimental data, and physics-based simulations, the stalk glycans were shown to heavily influence the bending angle of spike protein, with a particular emphasis on the glycan at position 1242. Further investigation revealed that removal of the N1242 glycan significantly reduced infectivity, highlighting a new potential therapeutic target. Overall, these investigations and associated innovations in integrative modeling.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis advisor) / Singharoy, Abhishek (Thesis advisor) / Woodbury, Neal (Committee member) / Sulc, Petr (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
Description
The relationship between sleep and physical activity is an area of growing scientific interest, particularly in the context of older adults. The importance of examining long sleep duration and its influence on physical activity in this demographic becomes increasingly relevant given rising healthcare costs. This dissertation aims to investigate this intricate relationship via secondary analysis by examining the effects of moderate time-in-bed (TIB) restriction (60 minutes per night)) on various intensities of physical activity (sedentary, light, moderate, vigorous, moderate-vigorous physical activity) in older adults classified as long sleepers and average duration sleepers. It was hypothesized that moderate TIB restriction would result in differential changes in physical activity levels across various intensities, with long sleepers exhibiting increased physical activity and average sleepers displaying decreased activity, potentially influenced by alterations in TST (total sleep time) and SE (sleep efficiency). Utilizing a randomized controlled trial design, this study examined the effect of treatment changes in objectively measures activity (waist actigraphy) and subjects physical activity levels as measured by the Godin Leisure-Time Exercise Questionnaire . Eligible participants were long sleepers (sleeping > 9 hours per night) and average sleepers (sleeping 7-9 hours per night). Both types of sleepers were either randomized to TIB restriction or asked to maintain their average sleep patterns. Mean TIB restriction compared with baseline was 39.5 minutes in average sleepers and 52.9 minutes in long sleepers randomized to TIB restriction . Contrary to the original hypothesis, no significant effect of TIB restriction was observed across all physical activity levels in either long sleepers or average sleepers. However, a notable association was found between increased sleep efficiency (+0.09% [SD = ± 4.64%]) and light physical activity (±31 minutes [SD = ± 104.81, R=0.445, P < 0.007]) in long sleepers undergoing TIB restriction. While this study presents several methodological limitations, including its nature as a secondary analysis and the less-than-intended achievement of TIB restriction, it adds a valuable layer to the existing body of research on sleep and physical activity in older adults. The findings suggest that moderate TIB restriction may not be sufficiently impactful to change behavior in physical activity levels, thus highlighting the need for more nuanced, targeted research in this domain.
ContributorsPerry, Christopher (Author) / Youngstedt, Shawn D (Thesis advisor) / Petrov, Megan (Committee member) / Swan, Pamela (Committee member) / Buman, Matthew (Committee member) / Ringenbach, Shannon (Committee member) / Arizona State University (Publisher)
Created2023
Description
The purpose of this investigation was to evaluate the influence of tap water safety perceptions on plain water intake (PWI) and hydration status in US Latinx adults. Participants (n=492; age, 28±7 y; 37.4% female) completed an Adapted Survey of Water Issues in Arizona and household watersecurity experience-based scales. A sub-sample (n=55; age, 33±14 y; body mass index, 27.77±6.60 kg·m2) completed dietary recalls on two weekdays and one weekend day via Automated Self-Administered 24-hour Dietary Assessment Tool to determine average PWI and total water intake (TWI). A 24-h urine sample was collected on one recall day and analyzed for urine osmolality (UOsm). Binary logistic regression determined odds ratios (OR) for the odds of perceiving tap water to be unsafe. Hierarchical linear regression was employed with 24-h UOsm and PWI as primary outcomes for the sub-sample. Overall, 51.2% of all participants and 52.7% of the sub-sample mistrust their tap water safety. The odds of mistrusting tap water were significantly greater (P<0.05) for each additional favorable perception of bottled over tap water (OR=1.94, 95% CI=1.50, 2.50), each additional negative home tap water experience (OR=1.32, 95% CI=1.12, 1.56), each additional use of alternatives and/or modifications to home tap water (OR=1.25, 95% CI=1.04, 1.51), and decreased water quality and acceptability (OR=1.21, 95% CI=1.01, 1.45). The odds of mistrusting tap water were significantly lower (P<0.05) for those whose primary source of drinking water is the public supply (municipal) (OR=0.07, 95% CI=0.01, 0.63) and for those with decreased water access (OR=0.56, 95% CI=0.48, 0.66). There were no differences (n=55, P>0.05) in TWI (2,678±1,139 mL), PWI (1,357±971), or 24-h UOsm (460±234 mosm·kg-1). Tap water safety perceptions did not significantly explain variance in PWI or 24-h UOsm (P > 0.05). In conclusion, Latinx mistrust in tap water safety is prevalent. Mistrust appears to be influenced by organoleptic perceptions and to lead to reliance on alternatives to the home drinking water system. Perceptions of tap water safety do not appear to be related to PWI, TWI, or hydration status in Latinx adults.
ContributorsColburn, Abigail (Author) / Kavouras, Stavros (Thesis advisor) / Buman, Matthew (Committee member) / Ohri-Vachaspati, Punam (Committee member) / Vega-Lopez, Sonia (Committee member) / Wutich, Amber (Committee member) / Arizona State University (Publisher)
Created2022
Description
Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT and digital technologies is particularly emphasized. This article presents a critical review of the design and implementation framework of this new urban renewal program across selected case‐study cities. The article examines the claims of the so‐called “smart cities” against actual urban transformation on‐ground and evaluates how “inclusive” and “sustainable” these developments are. We quantify the scale and coverage of the smart city urban renewal projects in the cities to highlight who the program includes and excludes. The article also presents a statistical analysis of the sectoral focus and budgetary allocations of the projects under the Smart Cities Mission to find an inherent bias in these smart city initiatives in terms of which types of development they promote and the ones it ignores. The findings indicate that a predominant emphasis on digital urban renewal of selected precincts and enclaves, branded as “smart cities,” leads to deepening social polarization and gentrification. The article offers crucial urban planning lessons for designing ICT‐driven urban renewal projects, while addressing critical questions around inclusion and sustainability in smart city ventures.`
ContributorsPraharaj, Sarbeswar (Author)
Created2021-05-07
Description
The research shows that existing interventions that attempt to reduce sedentary behavior are effective. The purposes of this review were to examine: (1) how adherent individuals are to workplace sedentary behavior interventions in the short and long term and (2) how the use of incentives impact adherence in the short and long term. It was found that short-term studies showed higher rates of adherence than medium-term studies. Studies that used incentives showed lower rates of adherence than studies that did not use incentives. Medium-term studies that used incentives showed the same rates of adherence as short-term studies that used incentives, indicating that incentives can benefit adherence in longer term interventions.
ContributorsLitevsky, Gabriella (Author) / Buman, Matthew (Thesis director) / Leonard, Krista (Committee member) / Barrett, The Honors College (Contributor) / College of Health Solutions (Contributor)
Created2022-05
Description
High fiber diets have been associated with improved cardiometabolic health with specific efforts to lower circulating levels of low-density lipoprotein (LDL cholesterol). Whole grain and grain-based foods are major contributors of dietary fiber in the American diet, of which wheat has been extensively studied. Corn, however, has not been well studied for its cholesterol-lowering properties. Further, the mechanisms by which grains improve cardiometabolic health require further exploration with regard to the human microbiome. The objective of this single-blind randomized controlled, crossover trial was to assess the impact of three different corn flours (whole grain, refined, and bran-enhanced refined flour mixture) on serum LDL cholesterol and the gut microbiota diversity and composition. Twenty-three participants were recruited, between the ages of 18-70 with hypercholesterolemia (Male = 10, Female = 13, LDL >120 mg/dL) who were not taking any cholesterol-lowering medications. Participants consumed each flour mixture for 4 weeks prepared as muffins and pita breads. At the beginning and end of each 4-week period serum for cholesterol assessment, anthropometrics, and stool samples were obtained. Serum cholesterol was assessed using a clinical analyzer. Stool samples were processed, and microbial DNA extracted and sequenced based on the 16S rRNA gene. A generalized linear model demonstrated a significant treatment effect (p=0.016) on LDL cholesterol and explained a majority of the variance (R-squared= 0.89). Post hoc tests revealed bran-enhanced refined flour had a significant effect on cholesterol in comparison to whole grain flour (p=0.001). No statistically significant differences were observed for gut microbial community composition (Jaccard and weighted Unifrac) after corn consumption. However, relative abundance analysis (LEfSE) identified Mycobacterium celatum (p=0.048 FDR=0.975) as a potential marker of post-corn consumption with this microbe being differentially less abundant following bran-enhanced flour treatment. These data suggest that corn flour consumption may be beneficial for individuals with hypercholesterolemia but the role of gut microbiota in this relationship requires further exploration, especially given the small sample size. Further research and analysis of a fully powered cohort is needed to more accurately describe the associations and potential mechanisms of corn-derived dietary fiber on circulating LDL cholesterol and the gut microbiota.
ContributorsWilson, Shannon L (Author) / Whisner, Corrie M (Thesis advisor) / Sears, Dorothy (Committee member) / Buman, Matthew (Committee member) / Dickinson, Jared (Committee member) / Zhu, Qiyun (Committee member) / Arizona State University (Publisher)
Created2022
Description
Attitudes and habits are extremely resistant to change, but a disruption of the magnitude of the COVID-19 pandemic has the potential to bring long-term, massive societal changes. During the pandemic, people are being compelled to experience new ways of interacting, working, learning, shopping, traveling, and eating meals. Going forward, a critical question is whether these experiences will result in changed behaviors and preferences in the long term. This paper presents initial findings on the likelihood of long-term changes in telework, daily travel, restaurant patronage, and air travel based on survey data collected from adults in the United States in Spring 2020. These data suggest that a sizable fraction of the increase in telework and decreases in both business air travel and restaurant patronage are likely here to stay. As for daily travel modes, public transit may not fully recover its pre-pandemic ridership levels, but many of our respondents are planning to bike and walk more than they used to. These data reflect the responses of a sample that is higher income and more highly educated than the US population. The response of these particular groups to the COVID-19 pandemic is perhaps especially important to understand, however, because their consumption patterns give them a large influence on many sectors of the economy.
ContributorsConway, Matthew Wigginton (Author) / Salon, Deborah (Author) / da Silva, Denise Capasso (Author) / Mirtich, Laura Christine (Author)
Created2020-09-03