Programs and Communities

Diabetes, a common chronic condition, effects many individuals causing poor quality of life, expensive medical bills, and devastating medical complications. While health care providers try to manage diabetes during short office visits, many patients still struggle to control their diabetes at home. Lack of diabetes self-management (DSM) is a potential barrier for people with diabetes having to maintain healthy hemoglobin A1cs (HgA1c).

In hopes of addressing this concern, an evidenced-based intervention; diabetic education and phone calls, using the chronic care model as its framework was implemented. The intervention targeted people with type II diabetes at a transitional care setting. Measured variables included HgA1c and DSM. Statistically significant improvements were seen in reported physical activity. Average improvements were seen in HgA1c and DSM after three months of diabetes self-management education (DSME). Attrition, cultural sensitivity, and increasing DSME hours should be further evaluated for future projects.

Background: The global prevalence of all types of diabetes increased from 108 million in 1980 to 422 million in 2014 (Nazir et al., 2018). The Centers for Disease Control and Prevention (2017) ranks diabetes as the 7th leading cause of death in the United States with an estimated annual expense of $327 billion. Within the rural setting, patients typically have less resources available for the treatment and self-management of their diseases. It is important to explore self-management techniques that can be utilized by patients with type 2 diabetes living in rural areas. Research demonstrating the importance of education, exercise, diet, glucose monitoring, medications, and supportive measures is prominent throughout the literature.

Objective: The purpose of this Doctor of Nursing Practice (DNP) applied project is to investigate the effects of delivering biweekly text messages containing diabetes self-management education (DSME) materials to patients in an effort to support successful self-care.

Methods: During an 8 week period, DSME was provided via text messaging, bi-weekly (Sunday and Wednesday), to 23 rural participants with type 2 diabetes, in a family clinic in Payson, Arizona. Participants were asked to complete the Skills, Confidence, and Preparedness Index both pre- and post-intervention to evaluate their knowledge of diabetes self-management.

Results: Twenty-three adults aged 52 to 78 years (M = 64.91) participated in the project. Of the participants, 57% (13/23) were female. The majority of participants had T2DM diagnosis less than 10 years (M=13.8 years). There was a statistical difference between the pre- and post-Skills, Confidence and Preparedness Index questionnaire (p < .001) indicating an improvement in self-efficacy scores post- intervention.

Conclusion: DSME delivered via text message is a cost-effective way to increase patients' self-efficacy and potentially improve their ability to successfully self-manage their disease.

There is an estimated 6.2 million people Americans over the age of 20 suffering from Heart Failure (HF) (Bejamin et. al., 2019). It is essential that HF patients have sufficient knowledge about the disease and self-management (Abbasi, Ghezeljeh, & Farahani, 2018; Dinh, Bonner, Ramsbotham & Clark, 2018). Lack of self-management is largely to blame for many HF exacerbations. Current evidence supports utilizing both verbal and written education with an emphasis on self-care and education delivered in a group setting or individual setting showed equal impact on self-care and HF knowledge ( Hoover, et. al., 2017; Ross et. al., 2015; Tawalbeh, 2018).

An outpatient VA clinic located in a suburb of the large metropolitan identified there was no consistency on how a HF patient was educated, managed, or tracked and the registered nurses (RNs) lacked knowledge of HF. As a results of these findings this Evidence Based Project (EBP) was implemented. RNs were educated on HF and completed a self-assessment questionnaire evaluating their knowledge pre and post education. The RNs, as part of a multidisciplinary team, educated HF patients on signs and symptoms of HF as well as on how to manage the disease. Patients completed, the Kansas City Cardiomyopathy Questionnaire (KCCQ) to assess quality of life and the Self Care Heart Failure Index (SCHFI) to assess knowledge of HF and self-management skills.

These questionnaires were completed initially and at 30 and 60 day intervals. The RNs self-assessment of their knowledge and ability to educate patients increased in all areas. The patient’s KCCQ and SCHFI score improved at 30 days and 60 days when compared to their initial score. Larger EBPs are needed over a longer period of time to assess the impact on hospital readmissions and same day clinic visits for HF exhibitions.

Phoenix is the sixth most populated city in the United States and the 12th largest metropolitan area by population, with about 4.4 million people. As the region continues to grow, the demand for housing and jobs within the metropolitan area is projected to rise under uncertain climate conditions.

Undergraduate and graduate students from Engineering, Sustainability, and Urban Planning in ASU’s Urban Infrastructure Anatomy and Sustainable Development course evaluated the water, energy, and infrastructure changes that result from smart growth in Phoenix, Arizona. The Maricopa Association of Government's Sustainable Transportation and Land Use Integration Study identified a market for 485,000 residential dwelling units in the urban core. Household water and energy use changes, changes in infrastructure needs, and financial and economic savings are assessed along with associated energy use and greenhouse gas emissions.

The course project has produced data on sustainable development in Phoenix and the findings will be made available through ASU’s Urban Sustainability Lab.

Hybrid system models - those devised from two or more disparate sub-system models - provide a number of benefits in terms of conceptualization, development, and assessment of dynamical systems. The decomposition approach helps to formulate complex interactions that are otherwise difficult or impractical to express. However, hybrid model development and usage can introduce complexity that emerges from the composition itself.

To improve assurance of model correctness, sub-systems using disparate modeling formalisms must be integrated above and beyond just the data and control level; their composition must have model specification and simulation execution aspects as well. Poly-formalism composition is one approach to composing models in this manner.

This dissertation describes a poly-formalism composition between a Discrete EVent System specification (DEVS) model and a Cellular Automata (CA) model types. These model specifications have been chosen for their broad applicability in important and emerging domains. An agent-environment domain exemplifies the composition approach. The inherent spatial relations within a CA make it well-suited for environmental representations. Similarly, the component-based nature of agents fits well within the hierarchical component structure of DEVS.

This composition employs the use of a third model, called an interaction model, that includes methods for integrating the two model types at a formalism level, at a systems architecture level, and at a model execution level. A prototype framework using DEVS for the agent model and GRASS for the environment has been developed and is described. Furthermore, this dissertation explains how the concepts of this composition approach are being applied to a real-world research project.

This dissertation expands the tool set modelers in computer science and other disciplines have in order to build hybrid system models, and provides an interaction model for an on-going research project. The concepts and models presented in this dissertation demonstrate the feasibility of composition between discrete-event agents and discrete-time cellular automata. Furthermore, it provides concepts and models that may be applied directly, or used by a modeler to devise compositions for other research efforts.