Matching Items (147)
Description
Chronic diseases are the leading causes of death in the United States. Dietary behaviors influence the risk of developing multiple chronic diseases. The U.S. population consumes too few fruits and vegetables and too much sugar sweetened beverages (SSB) and fast food. The Social Ecological Model (SEM) was created as a framework for health promotion interventions. The SEM organizes factors that can influence health into five layers: intrapersonal factors, interpersonal processes, institutional/organizational factors, community factors, and public policy. Each layer can influence dietary behaviors and other layers.
This work aims to understand how the community layer, represented by the food environment, moderates the association of two other layers and dietary behaviors: the interpersonal layer, represented by receiving health care provider’s (HCP) advice to lose weight, and the policy layer, represented by participation in the Supplemental Nutrition Assistance Program (SNAP), and a policy change within the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC).
Participant data were obtained from a household telephone survey of 2,211 adults in four cities in New Jersey from two cross-sectional panels in 2009-10 and 2014. Community food data were purchased and classified according to previously established protocol. Interaction and stratified analyses determined the differences in the association between HCP advice, SNAP participation, and time (for WIC participants) and eating behaviors by the food environment.
Interaction and stratified analyses revealed that HCP advice was associated with a decrease in SSB consumption when participants lived near a small grocery store, or far from a supermarket, limited service restaurant (LSR), or convenience store. SNAP participation was associated with a higher SSB consumption when respondents lived close to a small grocery store, supermarket, and LSR. There were no differences in fruit and vegetable consumption between two time points among WIC participants, or by food outlet.
The food environment, part of the community layer of SEM, moderated the relationship between the interpersonal layer and dietary behaviors and the policy layer and dietary behaviors. The association between HCP advice and dietary behaviors and SNAP participation and dietary behaviors were both influenced by the food environment in which participants lived.
This work aims to understand how the community layer, represented by the food environment, moderates the association of two other layers and dietary behaviors: the interpersonal layer, represented by receiving health care provider’s (HCP) advice to lose weight, and the policy layer, represented by participation in the Supplemental Nutrition Assistance Program (SNAP), and a policy change within the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC).
Participant data were obtained from a household telephone survey of 2,211 adults in four cities in New Jersey from two cross-sectional panels in 2009-10 and 2014. Community food data were purchased and classified according to previously established protocol. Interaction and stratified analyses determined the differences in the association between HCP advice, SNAP participation, and time (for WIC participants) and eating behaviors by the food environment.
Interaction and stratified analyses revealed that HCP advice was associated with a decrease in SSB consumption when participants lived near a small grocery store, or far from a supermarket, limited service restaurant (LSR), or convenience store. SNAP participation was associated with a higher SSB consumption when respondents lived close to a small grocery store, supermarket, and LSR. There were no differences in fruit and vegetable consumption between two time points among WIC participants, or by food outlet.
The food environment, part of the community layer of SEM, moderated the relationship between the interpersonal layer and dietary behaviors and the policy layer and dietary behaviors. The association between HCP advice and dietary behaviors and SNAP participation and dietary behaviors were both influenced by the food environment in which participants lived.
ContributorsLorts, Cori Elizabeth (Author) / Ohri-Vachaspati, Punam (Thesis advisor) / Adams, Marc (Committee member) / Hooker, Steven (Committee member) / Roberto, Anthony (Committee member) / Tasevska, Natasha (Committee member) / Arizona State University (Publisher)
Created2017
Description
Online social media is popular due to its real-time nature, extensive connectivity and a large user base. This motivates users to employ social media for seeking information by reaching out to their large number of social connections. Information seeking can manifest in the form of requests for personal and time-critical information or gathering perspectives on important issues. Social media platforms are not designed for resource seeking and experience large volumes of messages, leading to requests not being fulfilled satisfactorily. Designing frameworks to facilitate efficient information seeking in social media will help users to obtain appropriate assistance for their needs
and help platforms to increase user satisfaction.
Several challenges exist in the way of facilitating information seeking in social media. First, the characteristics affecting the user’s response time for a question are not known, making it hard to identify prompt responders. Second, the social context in which the user has asked the question has to be determined to find personalized responders. Third, users employ rhetorical requests, which are statements having the
syntax of questions, and systems assisting information seeking might be hindered from focusing on genuine questions. Fouth, social media advocates of political campaigns employ nuanced strategies to prevent users from obtaining balanced perspectives on
issues of public importance.
Sociological and linguistic studies on user behavior while making or responding to information seeking requests provides concepts drawing from which we can address these challenges. We propose methods to estimate the response time of the user for a given question to identify prompt responders. We compute the question specific social context an asker shares with his social connections to identify personalized responders. We draw from theories of political mobilization to model the behaviors arising from the strategies of people trying to skew perspectives. We identify rhetorical questions by modeling user motivations to post them.
and help platforms to increase user satisfaction.
Several challenges exist in the way of facilitating information seeking in social media. First, the characteristics affecting the user’s response time for a question are not known, making it hard to identify prompt responders. Second, the social context in which the user has asked the question has to be determined to find personalized responders. Third, users employ rhetorical requests, which are statements having the
syntax of questions, and systems assisting information seeking might be hindered from focusing on genuine questions. Fouth, social media advocates of political campaigns employ nuanced strategies to prevent users from obtaining balanced perspectives on
issues of public importance.
Sociological and linguistic studies on user behavior while making or responding to information seeking requests provides concepts drawing from which we can address these challenges. We propose methods to estimate the response time of the user for a given question to identify prompt responders. We compute the question specific social context an asker shares with his social connections to identify personalized responders. We draw from theories of political mobilization to model the behaviors arising from the strategies of people trying to skew perspectives. We identify rhetorical questions by modeling user motivations to post them.
ContributorsRanganath, Suhas (Author) / Liu, Huan (Thesis advisor) / Lai, Ying-Cheng (Thesis advisor) / Tong, Hanghang (Committee member) / Vaculin, Roman (Committee member) / Arizona State University (Publisher)
Created2017
Description
Resilience is emerging as the preferred way to improve the protection of infrastructure systems beyond established risk management practices. Massive damages experienced during tragedies like Hurricane Katrina showed that risk analysis is incapable to prevent unforeseen infrastructure failures and shifted expert focus towards resilience to absorb and recover from adverse events. Recent, exponential growth in research is now producing consensus on how to think about infrastructure resilience centered on definitions and models from influential organizations like the US National Academy of Sciences. Despite widespread efforts, massive infrastructure failures in 2017 demonstrate that resilience is still not working, raising the question: Are the ways people think about resilience producing resilient infrastructure systems?
This dissertation argues that established thinking harbors misconceptions about infrastructure systems that diminish attempts to improve their resilience. Widespread efforts based on the current canon focus on improving data analytics, establishing resilience goals, reducing failure probabilities, and measuring cascading losses. Unfortunately, none of these pursuits change the resilience of an infrastructure system, because none of them result in knowledge about how data is used, goals are set, or failures occur. Through the examination of each misconception, this dissertation results in practical, new approaches for infrastructure systems to respond to unforeseen failures via sensing, adapting, and anticipating processes. Specifically, infrastructure resilience is improved by sensing when data analytics include the modeler-in-the-loop, adapting to stress contexts by switching between multiple resilience strategies, and anticipating crisis coordination activities prior to experiencing a failure.
Overall, results demonstrate that current resilience thinking needs to change because it does not differentiate resilience from risk. The majority of research thinks resilience is a property that a system has, like a noun, when resilience is really an action a system does, like a verb. Treating resilience as a noun only strengthens commitment to risk-based practices that do not protect infrastructure from unknown events. Instead, switching to thinking about resilience as a verb overcomes prevalent misconceptions about data, goals, systems, and failures, and may bring a necessary, radical change to the way infrastructure is protected in the future.
This dissertation argues that established thinking harbors misconceptions about infrastructure systems that diminish attempts to improve their resilience. Widespread efforts based on the current canon focus on improving data analytics, establishing resilience goals, reducing failure probabilities, and measuring cascading losses. Unfortunately, none of these pursuits change the resilience of an infrastructure system, because none of them result in knowledge about how data is used, goals are set, or failures occur. Through the examination of each misconception, this dissertation results in practical, new approaches for infrastructure systems to respond to unforeseen failures via sensing, adapting, and anticipating processes. Specifically, infrastructure resilience is improved by sensing when data analytics include the modeler-in-the-loop, adapting to stress contexts by switching between multiple resilience strategies, and anticipating crisis coordination activities prior to experiencing a failure.
Overall, results demonstrate that current resilience thinking needs to change because it does not differentiate resilience from risk. The majority of research thinks resilience is a property that a system has, like a noun, when resilience is really an action a system does, like a verb. Treating resilience as a noun only strengthens commitment to risk-based practices that do not protect infrastructure from unknown events. Instead, switching to thinking about resilience as a verb overcomes prevalent misconceptions about data, goals, systems, and failures, and may bring a necessary, radical change to the way infrastructure is protected in the future.
ContributorsEisenberg, Daniel Alexander (Author) / Seager, Thomas P. (Thesis advisor) / Park, Jeryang (Thesis advisor) / Alderson, David L. (Committee member) / Lai, Ying-Cheng (Committee member) / Arizona State University (Publisher)
Created2018
Description
This dissertation aims to study and understand the effect of nonlinear dynamics and quantum chaos in graphene, optomechanics, photonics and spintronics systems.
First, in graphene quantum dot systems, conductance fluctuations are investigated from the respects of Fano resonances and quantum chaos. The conventional semi-classical theory of quantum chaotic scattering used in this field depends on an invariant classical phase-space structure. I show that for systems without an invariant classical phase-space structure, the quantum pointer states can still be used to explain the conductance fluctuations. Another finding is that the chaotic geometry is demonstrated to have similar effects as the disorders in transportations.
Second, in optomechanics systems, I find rich nonlinear dynamics. Using the semi-classical Langevin equations, I demonstrate a quasi-periodic motion is favorable for the quantum entanglement between the optical mode and mechanical mode. Then I use the quantum trajectory theory to provide a new resolution for the breakdown of the classical-quantum correspondences in the chaotic regions.
Third, I investigate the analogs of the electrical band structures and effects in the non-electrical systems. In the photonic systems, I use an array of waveguides to simulate the transport of the massive relativistic particle in a non-Hermitian scenario. A new form of Zitterbewegung is discovered as well as its analytical explanation. In mechanical systems, I use springs and mass points systems to achieve a three band degenerate band structure with a new pair of spatially separated edge states in the Dice lattice. A new semi-metal phase with the intrinsic valley-Hall effect is found.
At last, I investigate the nonlinear dynamics in the spintronics systems, in which the topological insulator couples with a magnetization. Rich nonlinear dynamics are discovered in this systems, especially the multi-stability states.
First, in graphene quantum dot systems, conductance fluctuations are investigated from the respects of Fano resonances and quantum chaos. The conventional semi-classical theory of quantum chaotic scattering used in this field depends on an invariant classical phase-space structure. I show that for systems without an invariant classical phase-space structure, the quantum pointer states can still be used to explain the conductance fluctuations. Another finding is that the chaotic geometry is demonstrated to have similar effects as the disorders in transportations.
Second, in optomechanics systems, I find rich nonlinear dynamics. Using the semi-classical Langevin equations, I demonstrate a quasi-periodic motion is favorable for the quantum entanglement between the optical mode and mechanical mode. Then I use the quantum trajectory theory to provide a new resolution for the breakdown of the classical-quantum correspondences in the chaotic regions.
Third, I investigate the analogs of the electrical band structures and effects in the non-electrical systems. In the photonic systems, I use an array of waveguides to simulate the transport of the massive relativistic particle in a non-Hermitian scenario. A new form of Zitterbewegung is discovered as well as its analytical explanation. In mechanical systems, I use springs and mass points systems to achieve a three band degenerate band structure with a new pair of spatially separated edge states in the Dice lattice. A new semi-metal phase with the intrinsic valley-Hall effect is found.
At last, I investigate the nonlinear dynamics in the spintronics systems, in which the topological insulator couples with a magnetization. Rich nonlinear dynamics are discovered in this systems, especially the multi-stability states.
ContributorsWang, Guanglei (Author) / Lai, Ying-Cheng (Thesis advisor) / Vasileska, Dragica (Committee member) / Ning, Cun-Zheng (Committee member) / Zhao, Yuji (Committee member) / Arizona State University (Publisher)
Created2017
Description
This dissertation aims to study and understand relevant issues related to the electronic, spin and valley transport in two-dimensional Dirac systems for different given physical settings. In summary, four key findings are achieved.
First, studying persistent currents in confined chaotic Dirac fermion systems with a ring geometry and an applied Aharonov-Bohm flux, unusual whispering-gallery modes with edge-dependent currents and spin polarization are identified. They can survive for highly asymmetric rings that host fully developed classical chaos. By sustaining robust persistent currents, these modes can be utilized to form a robust relativistic quantum two-level system.
Second, the quantized topological edge states in confined massive Dirac fermion systems exhibiting a remarkable reverse Stark effect in response to an applied electric field, and an electrically or optically controllable spin switching behavior are uncovered.
Third, novel wave scattering and transport in Dirac-like pseudospin-1 systems are reported. (a), for small scatterer size, a surprising revival resonant scattering with a peculiar boundary trapping by forming unusual vortices is uncovered. Intriguingly, it can persist in arbitrarily weak scatterer strength regime, which underlies a superscattering behavior beyond the conventional scenario. (b), for larger size, a perfect caustic phenomenon arises as a manifestation of the super-Klein tunneling effect. (c), in the far-field, an unexpected isotropic transport emerges at low energies.
Fourth, a geometric valley Hall effect (gVHE) originated from fractional singular Berry flux is revealed. It is shown that gVHE possesses a nonlinear dependence on the Berry flux with asymmetrical resonance features and can be considerably enhanced by electrically controllable resonant valley skew scattering. With the gVHE, efficient valley filtering can arise and these phenomena are robust against thermal fluctuations and disorder averaging.
First, studying persistent currents in confined chaotic Dirac fermion systems with a ring geometry and an applied Aharonov-Bohm flux, unusual whispering-gallery modes with edge-dependent currents and spin polarization are identified. They can survive for highly asymmetric rings that host fully developed classical chaos. By sustaining robust persistent currents, these modes can be utilized to form a robust relativistic quantum two-level system.
Second, the quantized topological edge states in confined massive Dirac fermion systems exhibiting a remarkable reverse Stark effect in response to an applied electric field, and an electrically or optically controllable spin switching behavior are uncovered.
Third, novel wave scattering and transport in Dirac-like pseudospin-1 systems are reported. (a), for small scatterer size, a surprising revival resonant scattering with a peculiar boundary trapping by forming unusual vortices is uncovered. Intriguingly, it can persist in arbitrarily weak scatterer strength regime, which underlies a superscattering behavior beyond the conventional scenario. (b), for larger size, a perfect caustic phenomenon arises as a manifestation of the super-Klein tunneling effect. (c), in the far-field, an unexpected isotropic transport emerges at low energies.
Fourth, a geometric valley Hall effect (gVHE) originated from fractional singular Berry flux is revealed. It is shown that gVHE possesses a nonlinear dependence on the Berry flux with asymmetrical resonance features and can be considerably enhanced by electrically controllable resonant valley skew scattering. With the gVHE, efficient valley filtering can arise and these phenomena are robust against thermal fluctuations and disorder averaging.
ContributorsXu, Hongya (Author) / Lai, Ying-Cheng (Thesis advisor) / Bliss, Daniel (Committee member) / Yu, Hongbin (Committee member) / Chen, Tingyong (Committee member) / Arizona State University (Publisher)
Created2017
Description
Background: Children’s fruit and vegetable consumption in the United States is lower than recommended. School lunch is an opportunity for students to be exposed to fruits and vegetables and potentially increase their daily intake. The purpose of this study is to examine the relationship between tray color and fruit and vegetable selection, consumption, and waste at lunch.
Methods: Study participants (n=1469) were elementary and middle school students who ate school lunch on the day of data collection. Photographs and weights (to nearest 2 g) were taken of fruits and vegetables on students’ trays before and after lunch. Trained research assistants viewed photographs and sorted trays into variable categories: color of main tray, presence/absence of secondary fruit/vegetable container, and color of secondary fruit/vegetable container. Fruit and vegetable selection, consumption, and waste were calculated using tray weights. Negative binomial regression models adjusted for gender, grade level, race/ethnicity, free/reduced price lunch status, and within-school similarities were used to examine relationships between tray color and fruit and vegetable selection, consumption, and waste.
Results: Findings indicated that students with a light tray selected (IRR= 0.44), consumed (IRR=0.73) and wasted (IRR=0.81) less fruit and vegetables. Students without a secondary fruit/vegetable container selected (IRR=0.66) and consumed (IRR=0.49) less fruit and vegetables compared to those with a secondary container. Light or clear secondary fruit and vegetable containers were related to increased selection (IRR=2.06 light, 2.30 clear) and consumption (IRR=1.95 light, 2.78 clear) compared to dark secondary containers, while light secondary containers were related to decreased waste (IRR= 0.57).
Conclusion: Tray color may influence fruit and vegetable selection, consumption, and waste among students eating school lunch. Further research is needed to determine if there is a cause and effect relationship. If so, adjusting container colors may be a practical intervention for schools hoping to increase fruit and vegetable intake among students.
Methods: Study participants (n=1469) were elementary and middle school students who ate school lunch on the day of data collection. Photographs and weights (to nearest 2 g) were taken of fruits and vegetables on students’ trays before and after lunch. Trained research assistants viewed photographs and sorted trays into variable categories: color of main tray, presence/absence of secondary fruit/vegetable container, and color of secondary fruit/vegetable container. Fruit and vegetable selection, consumption, and waste were calculated using tray weights. Negative binomial regression models adjusted for gender, grade level, race/ethnicity, free/reduced price lunch status, and within-school similarities were used to examine relationships between tray color and fruit and vegetable selection, consumption, and waste.
Results: Findings indicated that students with a light tray selected (IRR= 0.44), consumed (IRR=0.73) and wasted (IRR=0.81) less fruit and vegetables. Students without a secondary fruit/vegetable container selected (IRR=0.66) and consumed (IRR=0.49) less fruit and vegetables compared to those with a secondary container. Light or clear secondary fruit and vegetable containers were related to increased selection (IRR=2.06 light, 2.30 clear) and consumption (IRR=1.95 light, 2.78 clear) compared to dark secondary containers, while light secondary containers were related to decreased waste (IRR= 0.57).
Conclusion: Tray color may influence fruit and vegetable selection, consumption, and waste among students eating school lunch. Further research is needed to determine if there is a cause and effect relationship. If so, adjusting container colors may be a practical intervention for schools hoping to increase fruit and vegetable intake among students.
ContributorsWeight, Raquelle (Author) / Bruening, Meg (Thesis advisor) / Adams, Marc (Committee member) / Martinelli, Sarah (Committee member) / Arizona State University (Publisher)
Created2020
Description
Complex dynamical systems are the kind of systems with many interacting components that usually have nonlinear dynamics. Those systems exist in a wide range of disciplines, such as physical, biological, and social fields. Those systems, due to a large amount of interacting components, tend to possess very high dimensionality. Additionally, due to the intrinsic nonlinear dynamics, they have tremendous rich system behavior, such as bifurcation, synchronization, chaos, solitons. To develop methods to predict and control those systems has always been a challenge and an active research area.
My research mainly concentrates on predicting and controlling tipping points (saddle-node bifurcation) in complex ecological systems, comparing linear and nonlinear control methods in complex dynamical systems. Moreover, I use advanced artificial neural networks to predict chaotic spatiotemporal dynamical systems. Complex networked systems can exhibit a tipping point (a “point of no return”) at which a total collapse occurs. Using complex mutualistic networks in ecology as a prototype class of systems, I carry out a dimension reduction process to arrive at an effective two-dimensional (2D) system with the two dynamical variables corresponding to the average pollinator and plant abundances, respectively. I demonstrate that, using 59 empirical mutualistic networks extracted from real data, our 2D model can accurately predict the occurrence of a tipping point even in the presence of stochastic disturbances. I also develop an ecologically feasible strategy to manage/control the tipping point by maintaining the abundance of a particular pollinator species at a constant level, which essentially removes the hysteresis associated with tipping points.
Besides, I also find that the nodal importance ranking for nonlinear and linear control exhibits opposite trends: for the former, large degree nodes are more important but for the latter, the importance scale is tilted towards the small-degree nodes, suggesting strongly irrelevance of linear controllability to these systems. Focusing on a class of recurrent neural networks - reservoir computing systems that have recently been exploited for model-free prediction of nonlinear dynamical systems, I uncover a surprising phenomenon: the emergence of an interval in the spectral radius of the neural network in which the prediction error is minimized.
My research mainly concentrates on predicting and controlling tipping points (saddle-node bifurcation) in complex ecological systems, comparing linear and nonlinear control methods in complex dynamical systems. Moreover, I use advanced artificial neural networks to predict chaotic spatiotemporal dynamical systems. Complex networked systems can exhibit a tipping point (a “point of no return”) at which a total collapse occurs. Using complex mutualistic networks in ecology as a prototype class of systems, I carry out a dimension reduction process to arrive at an effective two-dimensional (2D) system with the two dynamical variables corresponding to the average pollinator and plant abundances, respectively. I demonstrate that, using 59 empirical mutualistic networks extracted from real data, our 2D model can accurately predict the occurrence of a tipping point even in the presence of stochastic disturbances. I also develop an ecologically feasible strategy to manage/control the tipping point by maintaining the abundance of a particular pollinator species at a constant level, which essentially removes the hysteresis associated with tipping points.
Besides, I also find that the nodal importance ranking for nonlinear and linear control exhibits opposite trends: for the former, large degree nodes are more important but for the latter, the importance scale is tilted towards the small-degree nodes, suggesting strongly irrelevance of linear controllability to these systems. Focusing on a class of recurrent neural networks - reservoir computing systems that have recently been exploited for model-free prediction of nonlinear dynamical systems, I uncover a surprising phenomenon: the emergence of an interval in the spectral radius of the neural network in which the prediction error is minimized.
ContributorsJiang, Junjie (Author) / Lai, Ying-Cheng (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Wang, Xiao (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2020
Description
Background: Exercise is Medicine (EIM) is a health promotion strategy for addressing physical inactivity in healthcare. However, it is unknown how to successfully implement the processes.
Purpose: The purpose of this study was to understand how implementing EIM influenced provider behaviors in a university-based healthcare system, using a process evaluation.
Methods: A multiple baseline, time series design was used. Providers were allocated to three groups. Group 1 (n=11) was exposed to an electronic medical record (EMR) systems change, EIM-related resources, and EIM training session. Group 2 (n=5) received the EMR change and resources but no training. Group 3 (n=6) was only exposed to the systems change. The study was conducted across three phases. Outcomes included asking about patient physical activity (PA) as a vital sign (PAVS), prescribing PA (ExRx), and providing PA resources or referrals. Patient surveys and EMR data were examined. Time series analysis, chi-square, and logistic regression were used.
Results: Patient survey data revealed the systems change increased patient reports of being asked about PA, χ2(4) = 95.47, p < .001 for all groups. There was a significant effect of training and resource dissemination on patients receiving PA advice, χ2(4) = 36.25, p < .001. Patients receiving PA advice was greater during phase 2 (OR = 4.7, 95% CI = 2.0-11.0) and phase 3 (OR = 2.9, 95% CI = 1.2-7.4). Increases were also observed in EMR data for PAVS, χ2(2) = 29.27, p <. 001 during implementation for all groups. Increases in PA advice χ2(2) = 140.90, p < .001 occurred among trained providers only. No statistically significant change was observed for ExRx, PA resources or PA referrals. However, visual analysis showed an upwards trend among trained providers.
Conclusions: An EMR systems change is effective for increasing the collection of the PAVS. Training and resources may influence provider behavior but training alone increased provider documentation. The low levels of documented outcomes for PA advice, ExRx, resources, or referrals may be due to the limitations of the EMR system. This approach was effective for examining the EIM Solution and scaled-up, longer trials may yield more robust results.
Purpose: The purpose of this study was to understand how implementing EIM influenced provider behaviors in a university-based healthcare system, using a process evaluation.
Methods: A multiple baseline, time series design was used. Providers were allocated to three groups. Group 1 (n=11) was exposed to an electronic medical record (EMR) systems change, EIM-related resources, and EIM training session. Group 2 (n=5) received the EMR change and resources but no training. Group 3 (n=6) was only exposed to the systems change. The study was conducted across three phases. Outcomes included asking about patient physical activity (PA) as a vital sign (PAVS), prescribing PA (ExRx), and providing PA resources or referrals. Patient surveys and EMR data were examined. Time series analysis, chi-square, and logistic regression were used.
Results: Patient survey data revealed the systems change increased patient reports of being asked about PA, χ2(4) = 95.47, p < .001 for all groups. There was a significant effect of training and resource dissemination on patients receiving PA advice, χ2(4) = 36.25, p < .001. Patients receiving PA advice was greater during phase 2 (OR = 4.7, 95% CI = 2.0-11.0) and phase 3 (OR = 2.9, 95% CI = 1.2-7.4). Increases were also observed in EMR data for PAVS, χ2(2) = 29.27, p <. 001 during implementation for all groups. Increases in PA advice χ2(2) = 140.90, p < .001 occurred among trained providers only. No statistically significant change was observed for ExRx, PA resources or PA referrals. However, visual analysis showed an upwards trend among trained providers.
Conclusions: An EMR systems change is effective for increasing the collection of the PAVS. Training and resources may influence provider behavior but training alone increased provider documentation. The low levels of documented outcomes for PA advice, ExRx, resources, or referrals may be due to the limitations of the EMR system. This approach was effective for examining the EIM Solution and scaled-up, longer trials may yield more robust results.
ContributorsBirchfield, Natasha R (Author) / Der Ananian, Cheryl (Thesis advisor) / Krasnow, Aaron (Committee member) / Doebbeling, Bradley (Committee member) / Adams, Marc (Committee member) / Swan, Pamela (Committee member) / Arizona State University (Publisher)
Created2019
Description
This dissertation aims to study the electron and spin transport, scattering in two dimensional pseudospin-1 lattice systems, hybrid systems of topological insulator and magnetic insulators, and molecule chain systems. For pseudospin-1 systems, the energy band consists of a pair of Dirac cones and a flat band through the connecting point of the cones. First, contrary to the conditional wisdom that flatband can localize electrons, I find that in a non-equilibrium situation where a constant electric field is suddenly switched on, the flat band can enhance the resulting current in both the linear and nonlinear response regimes compared to spin-1/2 system. Second, in the setup of massive pseudospin-1 electron scattering over a gate potential scatterer, I discover the large resonant skew scattering called super skew scattering, which does not arise in the corresponding spin-1/2 system and massless pseudospin-1 system. Third, by applying an appropriate gate voltage to generate a cavity in an alpha-T3 lattice, I find the exponential decay of the quasiparticles from a chaotic cavity, with a one-to-one correspondence between the exponential decay rate and the Berry phase for the entire family of alpha-T3 materials. Based on the hybrid system of a ferromagnetic insulator on top of a topological insulator, I first investigate the magnetization dynamics of a pair of ferromagnetic insulators deposited on the surface of a topological insulator. The spin polarized current on the surface of topological insulator can affect the magnetization of the two ferromagnetic insulators through proximity effect, which in turn modulates the electron transport, giving rise to the robust phase locking between the two magnetization dynamics. Second, by putting a skyrmion structure on top of a topological insulator, I find robust electron skew scattering against skyrmion structure even with deformation, due to the emergence of resonant modes. The chirality of molecule can lead to spin polarized transport due to the spin orbit interaction. I investigate spin transport through a chiral polyacetylene molecule and uncover the emergence of spin Fano resonances as a manifestation of the chiral induced spin selectivity effect.
ContributorsWang, Chengzhen (Author) / Lai, Ying-Cheng (Thesis advisor) / Yu, Hongbin (Committee member) / Wang, Chao (Committee member) / Zhao, Yuji (Committee member) / Arizona State University (Publisher)
Created2021
Description
Background: Studies show that rural schools may be less supportive of student fruit/vegetable (FV) consumption, but few studies have investigated the relationship between school locale and FVs. The aim of this research is to analyze the relationship between school locale (rural vs. urban) and students’ FV selection, consumption, and waste in elementary, middle, and high schools. Methods: A cross-sectional analysis of 37 Arizona schools evaluated differences in the selection, consumption, and waste of fresh FVs from students (n=2525; 45.7% female; 41% non-white; mean age=11.6±3.3; 23.5% rural) using objective plate waste measures. Zero-inflated negative binomial regressions examined differences in FV grams selected, consumed, and wasted by urban vs. rural locale, adjusted for sociodemographics and school.
Results: The percent of students who selected, consumed, and wasted zero grams of FVs were 14%, 21%, 20%, respectively. Among students with some (non-zero amounts), the average selected, consumed, and wasted FVs were 115.0±81.4g, 51.7.5±65.1g, 65.2±66.7g, respectively. Rural students (versus urban) had lower odds of selecting (OR=0.75), consuming (OR=0.78), and wasting (OR=0.71) any FVs, after adjusting for covariates. However, among students with some FVs on their plates, rural students selected (IRR=1.40), consumed (IRR=1.18) and wasted (IRR=1.62) more grams of FVs.
Conclusions: Rural students had reduced odds of selecting and consuming any FVs, but with lower odds of waste, perhaps due to reduced selection. Once some FVs were on the tray, likelihood of consumption and waste by rural students were greater. Results support interventions targeting rural students’ FV intake to reduce waste.
ContributorsJepson, Molly Eilish (Author) / Bruening, Meg (Thesis advisor) / Adams, Marc (Committee member) / Grgich, Traci (Committee member) / Arizona State University (Publisher)
Created2021