Community college leaders face challenges due to a lack of persistence data concerning 2-year colleges, especially in rural settings, prompting these leaders to turn to national data sets to drive local institutional changes. The purpose of this study was to identify variables associated with student place-frame and academic integration which are predictive of student persistence from the first to the second year in a small, residential community college in a rural frontier setting. Guided by Tinto's institutional departure theory, the theory of social representation, and Bassett's work in ruralism, a nonexperimental, correlational, quantitative research design was used to examine predictive relationships between student place-frame variables (age, sex, and intent to transfer), academic integration variables (student effort, collaborative learning, active learning, and academic challenge), and student persistence. Archival Community College Survey of Student Engagement data collected in 2013–2016 from 332 student participants were used for the study. Regression analysis showed a significant predictive relationship between student age and student intent to transfer with active learning. Additional binary logistical regression showed a significant positive relationship between active learning scores and student persistence. These findings informed development of evidence-based recommendations for programmatic changes to increase active learning practices, which could increase students' academic integration and persistence over time. By improving students' academic integration and persistence, positive social change may result through more students completing their degrees and their 2-year colleges gaining access to more substantial resources that are tied to student performance.

Teaching methods and styles at the collegiate level have not changed all that much: Professors still generally give lectures from the lectern or stand in the front of the class, while writing on the board or pointing to a slide projected on a screen. Some questions and answers can occur with the occasional group activity; however, the focus seems always to come back to the text. Students read the required textbook, listen to a lecture and take tests. There are however alternative methods that engage the students as well as the professor in the learning process. Active learning is one such method that is rooted in anything course-related that all students in a class session are asked to do other than simply watching, listening and taking notes. Active learning focuses on involving students in the learning process more directly compared to traditional methods. Another method which infuses both a performative background with an academic footing called performance pedagogy, emphasizes on the students bringing their ideologies, cultures, belief systems, and backgrounds into the classroom while incorporating their physical and metaphorical selves into the classroom space. The idea is that when students are exposed to these methods in a classroom setting, they can apply the subject content more effectively outside of the classroom, receive more frequent and immediate feedback, and provide students an opportunity to think about, talk about, and process course material. To demonstrate these methodologies, this teacher’s supplement has been created containing class activities for an undergraduate intercultural communication course using a standard sixteen-week semester.

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A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand, in partial fulfillment for the degree Masters of Medicine in Paediatrics (MMed) Johannesburg 2012 / Introduction: Highly active antiretroviral treatment (HAART) programs in heavily HIV-TB burdened countries may reduce the risk of TB in children directly by improving the immune system of HIV-infected children; and indirectly by reducing the force of transmission from the adult population. The incidence of childhood TB is a sentinel measure of the control of infectious adult TB cases in the community. Objective: We evaluated the impact that scaling-up of the HAART program in Soweto had on the incidence of hospitalization for culture-confirmed TB in children. Methods: The study was undertaken in Soweto, where the prevalence of HIV was 4-5% in children between 2005 and 2009. The estimated HAART coverage increased from 43% in 2005 to 84% by 2009 in children with HIV/AIDS. Hospitalized cases of culture-confirmed TB in children 3 months to 14 years of age were identified through laboratory and clinical electronic databases. Results: Overall, the incidence (per 100 000) of hospitalization for culture-confirmed TB declined by 58% (95%CI 49.3-65.2) from 2005 (71.4) compared to 2008-9 (30.0); p<0.0001. This included a 67% (95%CI 58.5-74.8) reduction in incidence among HIV-infected children from 2005 (1 601) compared to 2008-9 (517; p<0.0001). v In addition, a 33% reduction was observed in HIV-uninfected children (incidence 19.3 vs 12.9; p=0.016). Fifty-six percent of TB episodes, across all study periods, occurred in HIV-infected children who were mainly (76%) severely immunocompromised. Conclusions: Up-scaling of the HAART program in South Africa has been associated with decline in the incidence of culture-confirmed TB, more so in HIV-infected than HIV-uninfected children. Severely immunocompromised HIV-infected children, however, need to be identified and targeted with HAART and other strategies to further reduce the burden of TB in this group.

Thesis (M.Sc. in Epidemiology)--University of the Witwatersrand, Faculty of Health Sciences, 2014. / Introduction: The prevalence of the Human Immunodeficiency Virus (HIV) in South Africa was 17.8% among 15 to 49 year olds in 2010. Antiretroviral therapy (ART) has thus played a crucial role in mitigating the impact of the HIV epidemic. Themba Lethu Clinic is one of the largest single clinics providing ART in South Africa. One of the challenges of ART provision is ensuring adherence to taking the medication. To date there has been no clear consensus on the ideal way to measure adherence in resource limited settings (RLS). Viral load is perhaps the best and most reliable indicator of poor adherence but is expensive and not easily accessible or available in many RLS. Surrogate markers such as mean cell volume (MCV), CD4 cell count, self-reported adherence and missed visits have been shown to be useful to measure adherence but their reliability remains unclear. The aim of the study was to identify other markers that can be used to measure adherence using viral load as the gold standard. Materials and methods: The study was a retrospective analysis of HIV-positive ART-naïve adults (≥ 18 years) initiating standard first-line ART at the Themba Lethu Clinic in Johannesburg, South Africa between April 2004 and January 2012. The association between the last self-reported adherence, change in MCV calculated from baseline to 6 months, change in CD4 count calculated from baseline to 6 months (≥ or < the expected increase of 50 cells/mm3 at 6 months) and missed visits (defined as a scheduled appointment that had been missed by ≥ 7 days but not by more than 3 months) and poor adherence (defined as a viral load ≥ 400copies/ml after 6 months on ART) was tested using Poisson regression models with robust error variance to estimate incidence rate ratio (IRR) and 95% confidence interval (CI). The IRR was used to approximate the relative risk (RR) of poor adherence. Interacting variables were stratified by each other, to create a new variable. The diagnostic accuracy of each identified marker of adherence was also tested using sensitivity, specificity, positive predictive values and negative predictive values. Results: 7160 patients were eligible for the study and of these 63.2% were female. The median age was 36.7 years. The median CD4 count was 101 cells/mm3 at baseline and 18.9% of the patients had poor adherence at 6 months. Variables associated with poor adherence at 6 months were change in CD4 count stratified by change in MCV at 6 months (change in CD4 count ≥ expected and change in MCV ≥ 14.5fL; adjusted relative risk (aRR) 1, change in CD4 count ≥ expected and change in MCV < 14.5fL; aRR 3.11 95% CI 2.41 – 4.02, change in CD4 < expected and change in MCV ≥ 14.5fL; aRR 1.23 95% CI 0.76 – 2.00 and change in CD4 count < expected and change in MCV < 14.5fL; aRR 6.98 95% CI 5.35 – 9.09), CD4 count at baseline (> 200 cells/mm3; aRR 1, 101 – 200 cells/mm3; aRR 1.05 95% CI 0.80 – 1.38, 51 – 100 cells/mm3; aRR 1.08 95% CI 0.80 – 1.47 and ≤ 50cells/mm3; aRR 1.34 95% CI 1.02 – 1.76) , WHO stage at baseline (stage I; aRR 1, stage II; aRR 1.16 95% CI 0.90 – 1.48, stage III; aRR 1.27 95% CI 1.04 – 1.55 and stage IV; aRR 1.44 95% CI 1.12 – 1.84) and MCV at baseline (< 80fL; aRR 1, 80 – 100fL; aRR 1.33 95% CI 1.01 – 1.75 and > 100fL aRR 0.98 95% CI 0.62 – 1.55). Sensitivity and specificity of the change in CD4 stratified by change in MCV at 6 months to predict poor adherence were 86.5% and 37.3% respectively for all eligible patients. For patients on AZT-based regimens the variables associated with poor adherence at 6 months were change in CD4 count at 6 months (≥ expected; aRR 1 and < expected; aRR 7.66 95% CI 0.98 – 59.91) and pregnancy during the first 6 months on ART (Never pregnant; aRR 1 and pregnant during follow up; aRR 9.11 95% CI 2.17 – 38.25). Sensitivity and specificity of the change in CD4 count at 6 months to predict poor adherence were 64.7% and 75.2% respectively for all eligible patients on AZT-based regimens. Sensitivity and specificity of pregnancy during the first 6 months on ART to predict poor adherence were 20% and 97.6% respectively for all eligible patients on AZT-based regimens. Discussion: Change in CD4 count stratified by change in MCV at 6 months was an expected marker of adherence as CD4 count is expected to rise in adherent patients on ART and since most patients (62.9%) were on d4T or AZT-based regimens. Pregnancy during the first 6 months on ART appeared as a marker of adherence for patients on AZT-based regimens before multiple imputation possibly due to missing data hence results for this variable should be interpreted with caution. Contrary to previous studies, self-reported adherence was not associated with poor adherence at 6 months before multiple imputation. This could have been due to the fact that that > 50% of patients had missing data for this variable. The variable is also vulnerable to recall and reporting bias so even after multiple imputation, the area under the receiver operating characteristic (ROC) curve remained < 0.55. The number of missed medical visits and regimen change were also markers of adherence in a few of the models after multiple imputation and require further investigation. In conclusion, the markers of adherence to ART are change in CD4 count stratified by change in MCV at 6 months and pregnancy during the first 6 months on ART for patients on AZT-based regimens. These could help health workers identify poor adherence in the absence of viral load testing and target patients for adherence interventions to prevent virological failure.

Currently, the Low Earth Orbit (LEO) space environment contains a growing number of orbital debris objects. This growing orbital debris population increases collision probabilities between both orbital debris and functioning satellites. A phenomenon known as Kessler Syndrome can be induced if these collisions occur. Kessler Syndrome states that these collisions can lead to an exponential increase in the orbital debris population, which could dangerously impede future space missions. Current literature outlines the necessity of stabilizing the near-Earth environment debris population and introduces the concept of active debris removal (ADR). The use of ADR on five orbital debris objects per year was found to be a requirement to achieve stability within the orbital debris population. A viable mission architecture is henceforth explored to utilize ADR for near-future execution to further develop research for orbital debris mitigation missions. The larger orbital debris objects are found in many different orbital regimes and are primarily composed of spent rocket bodies and retired satellites. Different orbital debris ranking schemes have been developed based on the population density in these different regimes, which are linked to higher collision probabilities. Using these ranking schemes, a set of target objects are selected to be investigated for this mission design that was composed of target objects with similar orbital characteristics that were not launched by the Commonwealth of Independent States (CIS) to minimize legal barriers. Different ADR capture and removal methods are inspected to find the optimal methods for this mission. An Analytical Hierarchy Process (AHP) has been used to assess these different methods, which utilizes comparisons of the different methods among a set of weighted criteria. A net capture method with a low thrust chemical engine for removal is identified as the optimal ADR method. The use of a laser detumbling system is also selected to stabilize target objects with a high rotation rate. A rendezvous and deorbit orbital analysis are conducted using both a low fidelity tool (for preliminary results) and a high fidelity tool (for more precise results). The rendezvous analysis is used to select a mission architecture that was composed of two different chaser satellites which rendezvous with the five different target objects by taking advantage of nodal precession. The deorbit analysis investigates different decay timelines and found the delta-v estimates that would be required to deorbit the target objects within the same year that they were captured in. These two orbital analyses provide valuable insight to the mission timeline, delta-v estimates, and approximate mass requirement for the chaser satellite and deorbit kits. The results of the target selection process, ADR selection process, and the rendezvous and deorbit analyses are meant to provide an initial concept and analysis for a near-future ADR mission. These approximate results provide insight and information to further develop orbital debris mitigation research to help solve the orbital debris population growth challenge for future space missions. / Master of Science / Currently, the near Earth space environment contains a growing number of space debris. This growth in the orbital debris population increases the likelihood of collisions with orbital debris, functioning satellites, and launch vehicles. These collisions can generate a chain of events that could exponentially increase the population of orbital debris, which at some scale could become a major obstacle for future space missions. Researchers have introduced the concept of active debris removal (ADR), which in simulations has been shown to help stabilize the growth of orbital debris. The use of ADR to remove as low as five orbital debris objects per year has been found to be sufficient to stabilize debris growth. A viable mission architecture using ADR technologies that can be implemented in the near future is henceforth explored to further develop research for orbital debris missions. The larger orbital debris objects are found in many different areas in space and are primarily made up of used rocket bodies and retired satellites. Different ranking schemes have been developed by researchers for these larger orbital debris objects based on the population density within these areas in space, which are linked to the chance of a collision. Using these ranking schemes, a set of orbital debris objects are selected to be targeted for this mission design. This set of selected target objects have similar orbital characteristics and the political/legal barriers that could be present during removal are minimal. An ADR mission is composed of two primary components, a capture method and a removal method, which are inspected to find the optimal methods for this mission. A decision-making technique, called an Analytical Hierarchy Process (AHP), has been used to assess these different methods. The AHP compares different capture and removal methods using a set of weighted criteria. A net capture method with small thrusters for removal is identified as the optimal ADR method. Additionally, the use of a laser system is selected to stabilize target objects that may be rotating too quickly for capture. An analysis on different mission architectures is conducted using both a low fidelity tool (for preliminary results) and a high fidelity tool (for more precise results). A mission architecture composed of two different "chaser" satellites which rendezvous with and deorbit the five different target objects is selected. The analysis used on the selected mission architecture provides valuable insight to the mission timeline, fuel estimates, and approximate mass requirements. The results of the target selection process, ADR selection process, and the mission architecture analysis are meant to provide an initial concept and introduce possible requirements for a nearfuture ADR mission. These approximate results provide information to further develop research that can help us solve the orbital debris population growth challenge for future space missions.

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