Programs and Communities

Falls are prevalent among those aged 65 years and older and may result in minor to debilitating injuries in this vulnerable population. Frailty, unsteady gait, and medication side effects all contribute to fall risk as well as dementia, a type of cognitive impairment that disrupts memory and judgment leading to an underestimation of fall risk. Fall prevention evidence suggests that interventions aimed at decreasing fall rates begin with a fall risk assessment and tailored fall prevention measures that promote safety.

To examine the effectiveness of a fall prevention program in dementia care, an evidence-based pilot was conducted in a long-term care facility focused on dementia care. A convenience sample of 16 nurses received a fall prevention education intervention. A fall prevention knowledge instrument measured pre and post-fall prevention knowledge. There was a significant increase in fall risk knowledge from the pre-test (p < .001). The participants then conducted a fall risk assessment of 50 dementia patients using the Morse Fall Scale.

Of the 50 dementia patients, 28 were identified as high risk for falls. The nurses then instituted tailored fall risk prevention measures for those high risk for falls. As a result of the pilot, 40 fall events were noted within a three-month time period, reflecting a significant reduction in falls (p < .001) from the previous year. The institution of a fall prevention program in dementia care incorporating nursing education, a fall risk scale, and measures to promote safety can reduce fall risk in dementia patients.

Ineffective transitional care programs for ensuring the continuation of care from acute settings to the home settings post discharge can result in rehospitalization of elderly patients with chronic diseases. Usually, transitional care should be time-sensitive, patient-centered services intended to ensure continuity of care and an efficient transition between health care settings or home. A patient centered transitional care program was implemented at an outpatient primary care facility to reduce readmission rates. Institutional Review Board approval was obtained.

Twenty adult patients with chronic diseases discharged from an acute setting were identified. A follow up phone call and/or a home visit within 24-72 hours post discharge was employed. The Care Transitions Measure (CTM®) and Medication Discrepancy Tool (MDT®) were utilized to identify quality of care of transition and medication discrepancies. A chart audit collected data on the age of participant, diagnosis for initial hospitalization, CTM score, home visit, and ED visits or re-hospitalizations after 30 days of discharge. The outcome indicated that transitional care within primary care utilizing evidence-based practices is beneficial in reducing readmission rates. A logistic regression showed model significance, p = .002, suggesting that the CTM score was effective for both telephone support (TS) and home visit (HV).

A correlation analysis showed that as age of participants increased, the CTM score decreased, indicating that older adults required more support. A significance p <.001, of a proportional test indicated that readmission rates after the intervention was lower. It is evident that providing a timely and effective transitional care intervention in a primary care setting can reduce hospital readmissions, improve symptom management and quality of life of adult patients with chronic diseases.

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.

To investigate the impacts of an energy efficiency retrofit, indoor air quality and resident health were evaluated at a low‐income senior housing apartment complex in Phoenix, Arizona, before and after a green energy building renovation. Indoor and outdoor air quality sampling was carried out simultaneously with a questionnaire to characterize personal habits and general health of residents. Measured indoor formaldehyde levels before the building retrofit routinely exceeded reference exposure limits, but in the long‐term follow‐up sampling, indoor formaldehyde decreased for the entire study population by a statistically significant margin. Indoor PM levels were dominated by fine particles and showed a statistically significant decrease in the long‐term follow‐up sampling within certain resident subpopulations (i.e. residents who report smoking and residents who had lived longer at the apartment complex).

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.

Purpose: To examine the implementation of a web-based depression care management training program to increase home health nurses’ knowledge and attitudes regarding depression.

Background and Significance: The Centers for Disease Control and Prevention reported in 2015 that the incidence of major depression in elderly receiving home health service rose to 13.5% compared to less than 5% with those not receiving care in the community.

Materials and Methods: An intervention program was offered to a convenience sample of home health nurses caring for elderly in the community. The Depression CARE for Patients AT Home (depression CAREPATH), which is an evidenced-based online training program consisting of didactic resources about depression screening and depression care management and e-learning modules. Participants were given a pre and post survey to assess their knowledge of the material. Additionally demographic information was obtained via self-report.

Results: A total of 8 out of 18 home health nurses participated in the study. All were females; 13% Caucasian and 88% were Asian. There’s an average of 37 years old (SD 14.7, range 23-58) and had 3 years of experience (SD 2.07, range <1-6). The mean depression CAREPATH knowledge total pre-test score was 15 (SD 1.85, range 13-18), while the mean total post-test score was 18.13 (SD 0.99, range 17-19). There was a difference in the depression knowledge test scores at baseline. All the participants obtained a passing score for the post-test (80%). The mean R-DAQ total pre-test score was 71 (SD 13.37, range 53-71) and mean total post-test score was 68, (SD 3.48, range 62-70). The professional confidence in depression attitude indicated agreement post intervention, except with the feeling comfortable in working with physical illness than mental illness (pre intervention 62.5%, post intervention 100%). Participants agreed that home health nurses are well placed and more confident in assisting patients with depression (pre Depression Care Management 3 3 intervention 75%, post intervention 100%). In addition, participants felt more confident in assessing suicide risk post intervention in patient s presenting with depression. Based from Wilcoxon Signed-ranks test, there was a statistical difference, z = -2.536, p= .01, between the depression knowledge pre and post-test scores, which indicates that there is an increase in depression knowledge after the intervention. However, there was no significant difference, z = -.846, p = .397 between the depression attitude, which indicate that there is no change in depression attitude after the intervention.

Conclusion: For this sample, depression knowledge was increased post intervention, however, increase in knowledge did not significantly alter the depression attitude. Further study in a larger more diverse sample is needed for this intervention.