Now showing items 19746-19765 of 20330

    • Using Motivational Interviewing for Medication Adherence in Patients with Schizophrenia Spectrum Disorders

      Badger, Terry; Tellers, Ashlyn; Kahn-John, Michelle; Gallagher, Shawn (The University of Arizona., 2020)
      Schizophrenia spectrum disorders are psychiatric illnesses that have a high incidence of patients not adhering to their antipsychotic medications. There are multiple factors that contribute to medication nonadherence in patients with a schizophrenia spectrum disorders. Nonadherence with antipsychotic medications can cause poor patient outcomes for patients with these psychiatric illnesses. There is evidence to support that the therapeutic communication intervention, motivational interviewing, can improve medication adherence in patients with schizophrenia spectrum disorders. This quality improvement project used a pre- and post-test design to assess medication adherence pre- and post-intervention. The main outcome of this project was to improve the patient outcome, medication adherence. This project included a study sample of two participants that met inclusion criteria. Patient A’s pre-intervention medication adherence rating scale (MARS) score was 7 out of 10 and Patient B’s score was 4 out of 10. The higher the score on the MARS, the more favorable medication adherence. Patient A was unable to receive a therapeutic session of motivational interviewing because he was acutely psychotic and paranoid. Patient B received one face-to-face motivational interview session and behavioral changes were discussed on how to maintain medication adherence. The one-month follow up post- intervention could not be completed due to appointments being rescheduled by the patients and provider. The post-intervention MARS were not completed and motivational interviewing was unable to be evaluated for effectiveness. Despite the lack of result findings on medication adherence, administering the MARS and utilizing motivational interviewing offered insight about the patient’s beliefs and feelings about their antipsychotic medication. It is recommended for future projects to expand the PDSA cycle to recruit more participants and fully implement the study protocol. Keywords: motivational interviewing, medication adherence, schizophrenia spectrum disorders, and therapeutic communication.
    • Using Narrative Disclosures to Detect Financial Fraud

      Nunamaker, Jay F.; Spitzley, Lee; Burgoon, Judee K.; Mayew, William J.; Zhang, Bin (The University of Arizona., 2018)
      This dissertation measures the information content in narrative financial disclosures to identify linguistic differences in manager and analyst language when fraud versus when it is not. The first chapter describes the motivation for this research and an overview of the research domain. Next, I review the literature covering textual analysis of narrative disclosures and present a heuristic and classification scheme for studies in this context. In Chapter 3, I compare the language across two common narrative disclosure types: quarterly earnings calls and the Management’s Discussion & Analysis (MD&A) section of quarterly and annual financial statements and find evidence of restricted incremental information from the CFOs of fraudulent companies. Chapter 4 uses a quasi-experiment to compare analyst the frequency and topics of analysts’ question during earnings calls. I find that relative to nonfraudulent firms, analysts ask the managers of fraudulent firms more questions overall, and are more persistent in asking questions as a call progresses. Chapter 5 is an exploratory study of dominance and linguistic style matching from managers and analysts when interacting in the question-and-answer portion of an earnings call. The dissertation concludes with a discussion of the work, limitations, and avenues for future research.
    • Using Network Science to Estimate the Cost of Architectural Growth

      Valerdi, Ricardo; Dabkowski, Matthew Francis; Head, Kenneth L.; Furfaro, Roberto; Breiger, Ronald L.; Valerdi, Ricardo (The University of Arizona., 2016)
      Between 1997 and 2009, 47 major defense acquisition programs experienced cost overruns of at least 15% or 30% over their current or original baseline estimates, respectively (GAO, 2011, p. 1). Known formally as a Nunn-McCurdy breach (GAO, 2011, p. 1), the reasons for this excessive growth are myriad, although nearly 70% of the cases identified engineering and design issues as a contributing factor (GAO, 2011, p. 5). Accordingly, Congress legislatively acknowledged the need for change in 2009 with the passage of the Weapon Systems Acquisition Reform Act (WSARA, 2009), which mandated additional rigor and accountability in early life cycle (or Pre-Milestone A) cost estimation. Consistent with this effort, the Department of Defense has recently required more system specification earlier in the life cycle, notably the submission of detailed architectural models, and this has created opportunities for new approaches. In this dissertation, I describe my effort to transform one such model (or view), namely the SV-3, into computational knowledge that can be leveraged in Pre-Milestone A cost estimation and risk analysis. The principal contribution of my work is Algorithm 3-a novel, network science-based method for estimating the cost of unforeseen architectural growth in defense programs. Specifically, using number theory, network science, simulation, and statistical analysis, I simultaneously find the best fitting probability mass functions and strengths of preferential attachment for an incoming subsystem's interfaces, and I apply blockmodeling to find the SV-3's globally optimal macrostructure. Leveraging these inputs, I use Monte Carlo simulation and the Constructive Systems Engineering Cost Model to estimate the systems engineering effort required to connect a new subsystem to the existing architecture. This effort is chronicled by the five articles given in Appendices A through C, and it is summarized in Chapter 2.In addition to Algorithm 3, there are several important, tangential outcomes of this work, including: an explicit connection between Model Based System Engineering and parametric cost modeling, a general procedure for organizations to improve the measurement reliability of their early life cycle cost estimates, and several exact and heuristic methods for the blockmodeling of one-, two-, and mixed-mode networks. More generally, this research highlights the benefits of applying network science to systems engineering, and it reinforces the value of viewing architectural models as computational objects.
    • Using OASIS Data to Assess Moderator Effects of Patient Characteristics on Telemonitoring Outcomes in Heart Failure Patients

      Effken, Judith; Vallina, Helen; Effken, Judith; Reed, Pamela; Vincent, Deborah (The University of Arizona., 2009)
      This study had two purposes: 1) to compare the difference between home health care only and home health care plus telemonitoring on heart failure patients' symptom burden, self-care of heart failure and re-hospitalization; and 2) to explore which patient characteristics might moderate telemonitoring's impact.Heart failure has emerged as a major public health burden. Like other chronic conditions, heart failure patients have an important role to play in the day-to-day management of their condition. One of the principal reasons for introducing telemonitoring in home health care was to increase heart failure patients' capacity to self-manage their conditions at home.This study used a prospective, non-experimental, comparative, descriptive design. A total of 68 participants were recruited with 34 in each group. Symptom burden and self-care of heart failure were measured on enrollment and 40 days later. Hospitalization was measured as an event that either occurred or did not occur.Although no between-group differences in symptom burden were found, both groups showed significant decreased symptom burden over the 40-day period. Of the three self-care measures, only self-care maintenance differed significantly between the two groups at the 40-day follow-up (p<.05). Only the participant's functional status had significant moderator effect on the relation between type of service received and self-care maintenance (p<.05).The addition of telemonitoring produced similar outcomes to regular home health care, except for self-care maintenance. Like most prior study, this study focused on evaluating the overall relationship between telemonitoring and outcomes without concern for the transformation process. Although these evaluation were able to provide an overall assessment of whether or not the telemonitoring program worked, they cannnot identify the underlying mechanisms that generate the effects. Without knowing what make the program work or not work, it is difficult to pinpoint what needs to be done for future improvement. A theory-oriented evaluation will be needed in future research. Theory-oriented evaluation not only allow reseachers to clarify the connection between a program's operation and its effect, but also to specify intermediate effects of a program that might become evident and measurable.
    • Using Patient Notification Reminders to Increase Diabetic Patient Participation in Follow up Hemoglobin A1CTesting

      Prettyman, Allen; Ben, Candice Lynn; Allison, Theresa E.; Pacheco, Christy L. (The University of Arizona., 2020)
      In 2014, the global estimate of those with diabetes was 422 million (World Health Organization [WHO], 2018). The costs associated with the complications of diabetes can be detrimental to individuals and whole healthcare systems. Therefore, achieving glycemic control in diabetic patients is essential to improve patient outcomes and reduce complications. Glycemic control is assessed by testing hemoglobin A1C (HbA1C). Diabetic patients are tested anywhere from twice a year to quarterly, depending on HbA1C goals. Patient reminders and general education provided through text messages, short message services (SMS), and secure messages through patient portals have demonstrated improvements in HbA1C. Patient reminders and education varies. It includes anything from reminding the patient to take their medications to proper insulin injection techniques. Project purpose: increase diabetic patient follow up testing for HbA1C testing utilizing patient reminders sent through the patient portal. The project was developed with assistance from the Banner University South Campus Quality Improvement team in Tucson, Arizona. The nurse practitioners in this clinic identified five patients each. Patients were between the ages of 18 to 75 years old with an HbA1C of 9% or greater and due for testing. The patients received a reminder message through the patient portal system to return for follow up testing. A survey was provided to the nurse practitioners to assess their perceived usefulness of the patient portal. Descriptive statistics were used to analyze the findings. This quality improvement project will help determine if patient notification reminders help improve follow up testing in diabetic patients and ultimately improve patient outcomes. Results: Twelve patients received a reminder, and two made follow up appointments. Survey findings suggest a somewhat favorable approach to the use of the patient portal reminders.
    • Using Peak Intensity and Fragmentation Patterns in Peptide SeQuence IDentification (SQID) - A Bayesian Learning Algorithm for Tandem Mass Spectra

      Wysocki, Vicki H.; Ji, Li; Wysocki, Vicki H.; Aspinwall, Craig A.; Pemberton, Jeanne E. (The University of Arizona., 2006)
      As DNA sequence information becomes increasingly available, researchers are now tackling the great challenge of characterizing and identifying peptides and proteins from complex mixtures. Automatic database searching algorithms have been developed to meet this challenge. This dissertation is aimed at improving these algorithms to achieve more accurate and efficient peptide and protein identification with greater confidence by incorporating peak intensity information and peptide cleavage patterns obtained in gas-phase ion dissociation research. The underlying hypothesis is that these algorithms can benefit from knowledge about molecular level fragmentation behavior of particular amino acid residues or residue combinations.SeQuence IDentification (SQID), developed in this dissertation research, is a novel Bayesian learning-based method that attempts to incorporate intensity information from peptide cleavage patterns in a database searching algorithm. It directly makes use of the estimated peak intensity distributions for cleavage at amino acid pairs, derived from probability histograms generated from experimental MS/MS spectra. Rather than assuming amino acid cleavage patterns artificially or disregarding intensity information, SQID aims to take advantage of knowledge of observed fragmentation intensity behavior. In addition, SQID avoids the generation of a theoretical spectrum predication for each candidate sequence, needed by other sequencing methods including SEQUEST. As a result, computational efficiency is significantly improved.Extensive testing has been performed to evaluate SQID, by using datasets from the Pacific Northwest National Laboratory, University of Colorado, and the Institute for Systems Biology. The computational results show that by incorporating peak intensity distribution information, the program's ability to distinguish the correct peptides from incorrect matches is greatly enhanced. This observation is consistent with experiments involving various peptides and searches against larger databases with distraction proteins, which indirectly verifies that peptide dissociation behaviors determine the peptide sequencing and protein identification in MS/MS. Furthermore, testing SQID by using previously identified clusters of spectra associated with unique chemical structure motifs leads to the following conclusions: (1) the improvement in identification confidence is observed with a range of peptides displaying different fragmentation behaviors; (2) the magnitude of improvement is in agreement with the peptide cleavage selectivity, that is, more significant improvements are observed with more selective peptide cleavages.
    • Using Phylogenetically Conserved Stress Responses to Discover Natural Products with Anticancer Activity

      Gunatilaka, Leslie; Whitesell, Luke; Turbyville, Thomas Jefferson; Gunatilaka, Leslie; Whitesell, Luke; Bowden, Tim; Canfield, Louise; Briehl, Margaret (The University of Arizona., 2005)
      One unique feature of cancer cells that can be exploited for anticancer drug discovery is their dependence on their own cellular stress responses to survive the stressful acidotic, hypoxic and nutrient-deprived conditions within the tumor. Reasoning that desert organisms surviving under stressful conditions may have evolved to produce small molecule metabolites capable of modulating heat shock protein 90 (Hsp90) function, and/or other cell stress responses, we employed the cellular heat shock response in a moderate-throughput phenotypic assay. This strategy has resulted in the isolation and characterization of a number of small molecule natural products with heat shock induction activity from these organisms. Three such natural products are the subject of this study.In a limited structure-activity relationship (SAR) study, a previously known Hsp90 inhibitor radicicol (RAD), and several structurally related molecules including the fungal metabolite monocillin 1 (MON) were found to interact with Hsp90. In addition, RAD and MON were shown to lead to the degradation of Hsp90 client proteins involved in the cancer cell survival the estrogen receptor (ER) and the insulin-like growth factor receptor 1 (IGF-1R).We further characterized MON and showed that by targeting the molecular chaperone Hsp90, this compound induces components of the heat shock response at the transcriptional and translational levels, and leads to the acquisition of a thermotolerant phenotype in seedlings of the plant Arabidopsis thaliana. These findings support our hypothesis that there is ecological significance to the elaboration of small molecules that target stress responses.A number of extracts active in our phenotypic assay contained small molecules with no apparent Hsp90 activity. One such extract afforded terrecyclic acid A (TCA) with significant anti-tumor activity against a panel of human cancer cell lines. To characterize the biological activities of TCA we examined three key stress responsesthe heat shock, oxidative, and inflammatory responsesand show that TCA destabilizes these pathways associated with cancer cell survival through induction of oxidative stress (ROS), and inhibition of NF-kappaB transactivation.The isolation of RAD, MON and TCA from Sonoran desert organisms provides proof of principle that we have developed an effective strategy for the discovery of small molecule modulators of cellular stress responses that can serve as leads for the development of new anticancer drugs with novel mechanisms of action.
    • Using PROC GLIMMIX to Analyze the Animal Watch, a Web-Based Tutoring System for Algebra Readiness

      Levine-Donnerstein, Deborah; Barbu, Otilia C.; Marx, Ronald; Good, Thomas; McGraw, Rebecca; Levine-Donnerstein, Deborah (The University of Arizona., 2012)
      In this study, I investigated how proficiently seventh-grade students enrolled in two Southwestern schools solve algebra word problems. I analyzed various factors that could affect this proficiency and explored the differences between English Learners (ELs) and native English Primary students (EPs). I collected the data as part of the Animal Watch project, a computer-based initiative designed to improve the mathematical skills of children from grades 5-8 in the Southwest. A sample of 86 students (26 ELs and 60 EPs), clustered in four different classes, was used for this project. A Generalized Linear Mixed Model (GLMM) approach with the GLIMMIX procedure in SAS 9.3 showed that students from the classes that had a higher percentage of EL students performed better than those in the classes where the EL concentration was lower. Classes with more EL males were better at learning mathematics than classes with more EP females. The results also indicated: (a) a positive correlation between the students' ability to solve algebra word problems on their first attempt and their success ratio in solving all problems, and (b) a negative correlation between the percentage of problems solved correctly and those considered too hard from the very beginning. I conclude my dissertation by making specific recommendations for further research.
    • Using Pulsatile and Multi-Channel Electrocardiographic Waveforms to Identify and Evaluate False ICU Crisis Alarms

      Wung, Shu Fen; Chow, Jennifer L.; Rothers, Janet; DeBoe, Joseph (The University of Arizona., 2021)
      Background: A single bedside monitor in the intensive care unit (ICU) can alarm greater than 187 times per shift. Approximately 88% of these alarms in the ICU are false or require no intervention. These high rates of alarms can have deleterious effects on patients and staff members leading to a phenomenon called alarm fatigue. The purpose of this project was to explore the use of multichannel electrocardiographic and pulsatile waveforms to identify and evaluate false crisis alarms in the ICU.Methods: This project involved a secondary data analysis of 469 crisis alarms, with multichannel electrocardiographic and pulsatile waveforms, from a medical-surgical ICU. The frequency and percentages of false alarms were calculated using the statistical software STATA15.1 by StataCorp. Results: The majority (93.4%, 436/467) of these crisis alarms were false. Multichannel electrocardiographic waveforms were available in 93.1% of crisis alarms. Pulsatile waveforms, arterial blood pressure and photoplethysmography, were available in 19.7% and 95.4% of crisis alarms, respectively. Multichannel electrocardiographic waveforms were useful for identifying 90.4% (367/406) of false alarms. Pulsatile waveforms (ABP, PPG, or both) were found to be useful in identifying 83.6% (348/416) of false alarms. Conclusions: Both multichannel electrocardiographic and pulsatile waveforms demonstrate a high percentage of usefulness and availability in the identification and evaluation of false crisis alarms in the ICU.
    • Using Real-Time Physiological and Behavioral Data to Predict Students' Engagement during Problem Solving: A Machine Learning Approach

      Beal, Carole R.; Cirett Galan, Federico M.; Cohen, Paul; Barnard, Kobus; Morrison, Clayton; Beal, Carole R. (The University of Arizona., 2012)
      The goal of this study was to evaluate whether Electroencephalography (EEG) estimates of attention and cognitive workload captured as students solved math problems could be used to predict success or failure at solving the problems. Students solved a series of SAT math problems while wearing an EEG headset that generated estimates of sustained attention and cognitive workload each second. Students also reported on their level of frustration and the perceived difficulty of each problem. Results from a Support Vector Machine (SVM) training indicated that problem outcomes could be correctly predicted from the combination of attention and workload signals at rates better than chance. The EEG data was also correlated with students' self-report of problem difficulty. Findings suggest that relatively non-intrusive EEG technologies could be used to improve the efficacy of tutoring systems.
    • Using Recreation Specialization and Sense of Place to Measure Recreational Users' Motivations Within Boulder's Open Space and Mountain Parks

      Gimblett, Randy; Smith, Garrett Ryan; Bott, Suzanne; Livingston, Margaret; Molnar, Istvan (The University of Arizona., 2019)
      This study expands upon the research that has been conducted in regard to place attachment, recreation specialization, and motivation between recreation groups. Onsite surveys (n=989) were collected at nine multi-use trailheads managed by the City of Boulder’s Open Space and Mountain Parks (OSMP) department. A Kruskal-Wallis test followed by a Tukey Honesty Significant Difference Test (Tukey HSD) was used to identify differences in place attachment and recreation specialization between four recreation groups. Results showed that trail runners showed a statistically significant difference in place attachment when compared to hikers, mountain bikers, and other recreation groups. Hikers showed a statistically significant difference in recreation specialization when compared to mountain bikers, trail runners, and other recreation groups. One-way ANOVA tests showed that City of Boulder and Non-Boulder residents showed a statistically significant difference in place attachment but not recreation specialization. The top two motivations for all recreation groups was “For physical fitness” and “To enjoy nature”. With the third highest motivation being “To be close to nature” for hikers, trail runners, and mountain bikers and “For relaxation” for other recreation groups. A Multinomial Logistic Regression found that recreation activity and gender were significant predictors for choosing level of control or catharsis over the physical setting motivational dimension. Additionally, the multinomial model showed that recreation specialization was a significant predictor for choosing level of control over the physical setting motivational dimension. This research can be used to inform OSMP land managers on how to develop management plans that incorporate a better understanding of the differences between recreation groups and their motivations to recreation on OSMP landscapes.
    • Using RNA-Sequencing, In Vitro Calcium Imaging, and Proteomics to Investigate Novel Axon Degeneration Mediator, TMEM184B

      Bhattacharya, Martha RC; Larsen, Erik; Zinsmaier, Konrad; Koshy, Anita; Zarnescu, Daniela (The University of Arizona., 2021)
      TMEM184B is a novel mediator of axon degeneration with unknown molecular function. Previous work has shown Tmem184b loss delays axon degeneration in somatosensory neurons. This thesis involves a multi-faceted approach to gain insight into TMEM184B’s molecular and cellular function: I have analyzed the transcriptome of Tmem184b-mutant somatosensory ganglia to determine how Tmem184b loss affects neuronal gene expression, and I employed immunoprecipitation coupled with tandem mass spectrometry (proteomics) to determine with which proteins TMEM184B directly interacts. I aimed to integrate these results to determine a cellular and molecular function of TMEM184B, and to determine how TMEM184B impacts axon degeneration. Interestingly, I found that Tmem184b loss did not transcriptionally alter key axon degeneration mediators, but it strongly downregulated Il31ra, a receptor with well-known roles in eczema and asthma. I also found that TMEM184B interacts with 2nd and 3rd order mitogen-activated protein kinases (MAPKs), including MAP3K4 (also known as MEKK4), a known upstream regulator of the SARM1 and MAPK axon degeneration cascade. More generically, however, TMEM184B interacts with key proteins involved in the endo-lysosomal pathway, including multiple subunits of the vesicular/vacuolar H+-ATPase complex. This interaction may dictate vesicular dynamics that affect the delivery of molecular signals from distal parts of sensorimotor neurons to the soma.
    • Using Secure Messaging to Improve Patient-to-Provider Communication Among Active Duty Service Members

      Carrington, Jane M.; Burleson, Stephanie; Edmund, Sara; Stanley, Angela (The University of Arizona., 2020)
      Problem Statement: Secure messaging has the ability to improve patient-to-provider communication and patient self-management skills; however, low usage rates among Active Duty Service Members decreases its potential to initiate self-care management behavior and increase access to timely healthcare. Little is known about the barriers of secure messaging use in this population. Purpose: Identify barriers to secure messaging adoption and use among Active Duty Service Members. Methods: In this system assessment project, ten individual interviews with Active Duty Service Members and three interviews with providers will be conducted in a primary care clinic in Sigonella, Italy to assess behavior, attitudes and perception of secure messaging. Significance: Barriers reported by Active Duty Service Members were difficulty accessing website and lack of patient knowledge of secure messaging features. It is unclear if Active Duty Service Members receive formal education on how to navigate secure messaging prior to their use at the primary clinic. Therefore, employing educational and skill-based interventions to address these barriers, prior to use at the primary care clinic, should improve secure messaging utilization among Active Duty Service Members and, ultimately, increase patient-to-provider communication.
    • Using Social Media Intelligence to Support Business Knowledge Discovery and Decision Making

      Zeng, Daniel; Sun, Runpu; Zhang, Zhu; Goes, Paulo (The University of Arizona., 2011)
      The new social media sites - blogs, micro-blogs, and social networking sites, among others - are gaining considerable momentum to facilitate collaboration and social interactions in general. These sites provide a tremendous asset for understanding social phenomena by providing a wide availability of novel data sources. Recent estimates suggest that social media sites are responsible for as much as one third of new Web content, in the forms of social networks, comments, trackbacks, advertisements, tags, etc. One critical and immediate challenge facing the MIS researchers then becomes - how to effectively utilize this huge wealth of social media data, to facilitate business knowledge discovery and decision making.Among these available data sources, social networks constitute the backbone of almost all social media sites. These network structures provide a rich description of the social scenes and contexts, which is helpful for us to address the above challenge. In this dissertation, I have primarily employed the probabilistic network models, to study various social network related problems arose from the use of social media services. In Chapter 2 and Chapter 3, I studied how information overload can affect the efficiency of information diffusion in online social networks ( and Novel diffusion model were proposed to model the observed information overload. The models and their extensions are thoroughly evaluated by solving the Influence Maximization problem related to information diffusion and viral marketing applications. In Chapter 4, I studied the information overload in a micro-blogging application ( using a design science methodology. A content recommendation framework was proposed to help micro-blogging users to efficiently identify quality emergency news feeds. Chapter 5 presents a novel burst detection algorithm concerning identifying and analyzing correlated burst patterns by considering multiple inputs (data streams) that co-evolve over time. The algorithm was later used for discovering burst keywords/tag pairs from online social communities, which are strong indicators of emerging or changing user interests.Chapter 6 concludes this dissertation by highlighting major research contributions and future directions.
    • Using Social Theory to Guide Rural Public Health Policy and Environmental Change Initiatives

      Schachter, Kenneth; Kizer, Elizabeth A.; Schachter, Kenneth; Nichter, Mark; Reinschmidt, Kerstin M.; Thomson, Cynthia A. (The University of Arizona., 2017)
      The study of health disparities and the social determinants of health has resulted in the call for public health researchers to investigate the mid- and upstream factors that influence the incidence of chronic diseases (Adler & Rehkopf, 2008; Berkman, 2009; Braveman P. , 2006; Braveman & Gottlieb, 2014; Krieger, 2011; Rose, 1985). Social ecological models (SEMs) provide important conceptual tools to inform this research and practice (Krieger, 2011; Golden & Earp, 2012; Story, Kaphingst, Robinson O'Brien, & Glanz, 2008; Glanz, Rimer, & Lewis, 2002). These models can help us look at the social and physical environments in rural Arizona communities and consider how health policies and environmental interventions address mediating factors, such as disparities in access to fresh food, that contribute to ill health in marginalized, rural, populations. Rural residents are at greater risk for obesity than their urban counterparts (Jackson, Doescher, Jerant, & Hart, 2006; Story, Kaphingst, Robinson O'Brien, & Glanz, 2008). And while human life expectancy has steadily increased over the past thousand years, current projections indicate that the rise in obesity-related illnesses will soon result in its decline (Olshansky, et al., 2005). One reason for this decline, may be the reduced availability of healthy food – an important predictor of positive health outcomes including reduced obesity and chronic disease - in many parts of the United States (Brownson, Haire-Joshu, & Luke, 2006; Ahen, Brown, & Dukas, 2011; Braveman & Gottlieb, 2014; Braveman, Egerter, & Williams, 2011). The United States Department of Agriculture (USDA) defines food deserts as geographic areas in which there is limited access to grocery stores and whose populations have a high rate of poverty. In Arizona, 24% of the rural census tracts are considered food deserts; compared to an average of eight percent of rural census tracts across the nation (United States Department of Agriculture, 2013). Food deserts are one example of the upstream factors influencing the health of rural populations. Local health departments have been encouraged through the National Association for City and County Health Officials (NACCHO) and through the Public Health Accreditation Board (PHAB) to conduct community health assessments (CHAs) in order to identify unique contexts and community resources, health disparities, and the social determinants of health as well as potential areas for advocacy, policy change, environmental interventions, and health promotion interventions. Public health challenges like chronic diseases, which have multiple causes, can be explored in-depth through CHAs. CHAs often contain recommendations for action and/or are followed by community health improvement plans (CHIPs) which help local health departments prioritize resources and set measurable goals. In Florence, AZ recommendations made in a CHA are being acted upon by a non-profit agency, the Future Forward Foundation (3F). This investigation explores two interrelated issues regarding the use of CHAs and CHIPs as practical tools to set public health priorities. First, what makes a CHA useful to rural public health practitioners? What methods of conducting a CHA and subsequently analyzing the data results in actionable policy recommendations and/or environmental level interventions? Second, to what extent can public health agencies engage nontraditional partners to work in partnership to address the social determinants of health? As an example, I will look at the impact of a volunteer-based non-profit agency, located in a rural food desert on improving the social and physical nutrition environment as recommended by a local CHA. This inquiry will provide insights to public health practitioners seeking to identify and implement policy and environmental change addressing complex, multi-causal, public health issues, and provide insights regarding engaging nontraditional partners who may not self-identify as public health agencies.
    • Using standardized performance observations and interviews to assess the impact of teacher education

      Good, Thomas L.; Tsang, Henry Yen-Chang (The University of Arizona., 2003)
      This study used a standardized teacher observation rubric and procedures to evaluate the performance of 63 new teachers with various preparation backgrounds. Observers rated teachers from seven different school districts on 29 separate criteria of teaching effectiveness. New teachers were assessed on their lesson planning, assessment practices, classroom management, and implementing instruction during interviews and observations. Results show significant differences in the performance of new teachers depending on the model of the teacher education program they attended. Traditional undergraduate program graduates were rated higher than teachers who received their preparation from post-baccalaureate or master's degree certification programs (particularly in the area of classroom management and at the middle school level). Follow-up interviews were conducted with a stratified random sample of 15 of 63 participants. New teachers reported difficulty setting up classroom management procedures at the beginning of the semester especially small group instruction and would have preferred more classroom experiences during their teacher education program. Teachers strongly affirmed the importance of teacher education for their ability own to teach.
    • Using Structure to Study the Function of Proteins Involved in Antibiotic Resistance and Viral Infection

      Page, Rebecca; Schwartz, Jacob; Schoenle, Marta; Montfort, William; Tomasiak, Thomas (The University of Arizona., 2021)
      Understanding the mechanisms that underpin antibiotic resistance is an important first step towards the development of therapeutics for the treatment of resistant bacterial infections. Bacteria have evolved diverse mechanisms to evade antibiotic induced cell death, one example being antibiotic target modification, such as the expression of low affinity class B penicillin binding proteins. X-ray crystallography is the primary approach for studying this family of proteins. Mutations that affect antibiotic adduct formation result in minimal structural changes; however, failing to explain how sequence variations lead to resistance. Our initial experiments on penicillin binding protein 5 (PBP5) identified residues that inhibit β-lactam adduct formation, yet the structural implications of these mutations were minimal, similar to what has been observed with other PBPs. In response, we developed a method for studying PBP5, a large (70 kDa), multi-domain protein, in solution, using NMR spectroscopy. We demonstrated that a serine insertion at position 466 works synergistically with an alanine mutation at position 485 to increase resistance to penicillin G (0.73-fold relative to wild type PBP5) and that this causes minimal structural changes (RMSDs of 0.1 and 0.2 Å when main chain atoms were aligned with apo- and PenG-acylated PBP5 WT, respectively). We then refolded PBP5 and characterized the quality of the protein using NMR, which showed an increased number of peaks and uniform peak intensity, and by using X-ray crystallography, which demonstrated that the refolded protein has the same structure as the protein before refolding (0.2 Å RMSD when main chain atoms were aligned with PBP5 before refolding). The second project described in this dissertation examines mechanisms of SARS-CoV-2 spike protein receptor binding domain (RBD) neutralization by antibodies. Many antibody-RBD structures fail to crystalize, necessitating the use of an alternative technique to characterize these interactions. NMR spectroscopy allows for the rapid determination of antibody epitopes, thus eliminating the need for the protein to be crystallized. We demonstrate that 39 residues experience chemical shift perturbation upon titration with the CR3022 fab. When mapped onto the structure, the most significantly perturbed residues correspond well with residues known to be located at the CR3022-RBD interface. Taken together, these findings demonstrate that NMR spectroscopy can be used to gain atomic-resolution structural data on drug targets that require complicated protein refolding protocols. The refolding methods used to study PBP5 will allow for the characterization of interactions between PBP5 and variants with inhibitors and peptide substrates in solution. Finally, selective labeling, refolding, and purification of the SARS-CoV-2 RBD has allowed for the completion of the sequence specific backbone assignment, which can be used to rapidly determine antibody epitopes for RBD-antibody complexes that fail to crystalize.  
    • Using task-based e-mail activities in developing academic writing skills in English as a Second Language

      Ariew, Robert; Li, YiLi, 1964- (The University of Arizona., 1998)
      This study investigated the efficacy of using e-mail in the form of a class mailing list to help ESL students practice and develop academic writing skills beyond the spatial and time limits of a writing classroom. In this study, e-mail writing tasks of different purposes, audiences and task structures were integrated into a process-oriented freshman ESL writing class. The subjects of this study were 22 ESL students in a freshman composition course. In an ex post facto design (Hatch & Lazaraton, 1991), this study involved within-subject repeated measures of data collected from different e-mail writing tasks over the course of a semester. Data analysis included (1) computerized text analysis focusing on the linguistic and textual features of written discourses at the levels of syntactic complexity, lexical richness, textual cohesion and grammatical accuracy; (2) holistic and analytical assessments by ESL raters focusing on the overall rhetorical features and quality of writing. The results indicated that there were syntactic, lexical, textual and grammatical differences in ESL students' writing performance on e-mail writing tasks of different rhetorical purposes, and there was also variation between e-mail tasks involving an interactive audience and those involving an non-interactive audience, and between structured versus non-structured e-mail tasks. In particular, in e-mail tasks in which an interactive audience was present, students tended to produce texts that were linguistically more complex. Besides, students wrote with a higher level of syntactic and lexical complexity in the non-structured e-mail tasks than in the structured ones, indicating more sophisticated use of language when the student were given more freedom and control of the learning activities. The results also showed obvious tradeoff effects between linguistic complexity and accuracy, i.e. while students produced texts that were linguistically more complex, there was less attention to grammatical accuracy. Furthermore, the results suggested that motivation, attitude, and anxiety had some significant contributions to the variation in ESL students' writing performance while they composed in an electronic mode.
    • Using Telehealth to Educate Geriatrics on the Risk of Depression during COVID-19

      Buchner, Brian; Lomibao, Chanie; Rainbow, Jessica; Kuo, Bradley (The University of Arizona., 2020)
      Purpose: The purpose of this quality improvement project was to present a 10-minute online presentation to a geriatric population aged 65 years old and older about the clinical manifestations of depression, biological and other known risk factors of depression, provide resource options that are available, and when to contact a healthcare provider. Background: The COVID-19 pandemic is a global public health crisis. At the greatest risk of the pandemic is the geriatric population due to their age and chronic health care morbidities. The COVID-19 pandemic has suspended social interactions, enforced statewide lockdowns, and implemented social distancing. Although social isolation can potentially be lifesaving in older adults, the feelings of loneliness can negatively affect the older adult’s mental health. Methods: This quality improvement project included a group of nine volunteer participants from the University of Arizona’s Telehealth Learning Center, who were 65 years old or older. The theoretical framework that drove this project was Lewin’s change model. A Zoom session was held in which the participants were asked to complete a pre-test survey, view the educational video, and complete a post-test survey. Results: Data collection took place prior to the educational presentation, and immediately after, with all nine participants completing both, the pre-test survey and post-test survey. There was a 11.1% increase in the knowledge of risk factors for depression, 77.8% of participants were able to identify clinical manifestations of depression which resulted in no change, and an increase in the ability of participants to identify when to seek help for depression and an improved self-perceived likelihood of seeking help Conclusion: This quality improvement project helped to improve the participant’s knowledge of depression at a basic level. Educating older adults on the risk of depression during the COVID-19 pandemic is key to the likelihood of seeking help.
    • Using texture to predict diagnosis and disease from nuclear medicine lung perfusion scans: A comparison of nuclear medicine physicians to the slope of the power spectrum.

      Ittelson, William; Ker, Mary Virginia.; Daniel, Terry; Sechrest, Lee (The University of Arizona., 1991)
      The lung has been satisfactorily modelled as a fractal, and change in lung structure due to disease is assumed to change the fractal dimensionality of the lung. It is hypothesized that those changes in fractal dimension affect perceptually relevant elements (perceived texture) of the lung, and therefore the fractal dimension may prove to be a predictor of diagnosis. If the fractal dimensionality reflects structure in ways more accurately reflecting changes in lung structure than can be achieved by nuclear medicine physicians, then it may also prove useful as a diagnostic tool. Fractal dimension is linearly related to the slope of the power spectrum (SPS) as plotted on log-log paper, and the SPS was used as the metric reflecting the fractal dimension. Seventy-two cases were selected that were either normal, had congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), or pulmonary embolism (PE). Five of the cases had both CHF and COPD. The lung scans from these cases were digitized, with appropriate corrections for linearization, edge artifacts, target nonuniformities and film gamma. Fast Fourier Transforms provided the power spectrum from which the SPS was calculated. Four nuclear medicine physicians read the original lung scans and rated their certainty about the presence of two texture elements, the extensiveness of disease involvement, and presence of the three diseases used (CHF, COPD, and PE). The results found the SPS to be significantly related to both texture ratings and diagnostic certainty, but inferior as a predictor of disease to either texture rating or diagnostic certainty. This study reveals the SPS to be a promising but incomplete candidate for machine-algorithm generated diagnosis.