Theses and Dissertations from UMD
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Item Impact of COVID-19 on Parent and Child Mental Health in India: A Mixed-methods Longitudinal Study(2023) Havewala, Mazneen Cyrus; Wang, Cixin; Psychology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The COVID-19 pandemic has affected individuals around the world. Parents of young children have experienced significant strain as they have attempted to balance their work obligations as well as take care of household duties and attend to the needs of their young children. Several studies have demonstrated the detrimental impacts of COVID-19 on parent and child mental health. However, the majority of studies are quantitative, cross-sectional in nature, and were conducted during the early phases of the pandemic. Moreover, there is limited work on the topic of parent and child mental health within the COVID-19 context among families in India. Thus, the current mixed-methods longitudinal study aimed to fill these gaps in the literature by attempting to examine the impact of COVID-19 on child mental health and parent mental health among families with young children in India. The study also aimed to understand the moderating effects of parenting behaviors with relation to child COVID-19-related stress and child mental health difficulties, and the moderating effects of social support with relation to parent COVID-19-related stress and parent mental health difficulties. One hundred and forty parents of children between the ages of 4 to 8 completed a survey between October 2020 and February 2021 (Time 1), of which 85 parents completed it between May 2021 and July 2021 (Time 2), and 70 completed it between July 2022 and October 2022 (Time 3). Qualitative in-depth individual interviews were conducted with a subset of the sample (n=20) between July 2022 and December 2022 to gain a better understanding of challenges experienced by parents and how the pandemic impacted them and their children in various ways over the course of the pandemic. The findings indicated that the stress caused by changes brought about by the pandemic was related to parent and child mental health in India. Parents in India experienced several challenges that impacted their mental health. Factors contributing to those challenges, and in turn, possibly their mental health are discussed. Parenting behaviors such as parental nurturance and restrictiveness were also related to child mental health and served as moderators of the relation between child COVID-19-related stress and child mental health difficulties; parental nurturance emerged as a protective factor while parental restrictiveness was a possible risk factor. Perceived social support was negatively linked with parent mental health difficulties, and it also served as a buffer in the relation of parent COVID-19-related stress and parent mental health difficulties at Time 1. Qualitative findings also indicated that support from spouse, other family members, friends and co-workers helped parents cope with the challenges associated with the pandemic. In sum, the findings of this study helped identify important risk and protective factors for parent and child mental health within the COVID-19 context in India. The findings have important clinical implications that inform future intervention efforts to support children and families during related stressful events.Item Second Wave Mechanics(2024) Fabbri, Anthony; Herrmann, Jeffrey W; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The COVID-19 pandemic experienced very well-documented "waves" of the virus's progression, which can be analyzed to predict future wave behavior. This thesis describes a data analysis algorithm for analyzing pandemic behavior and other, similar problems. This involves splitting the linear and sinusoidal elements of a pandemic in order to predict the behavior of future "waves" of infection from previous "waves" of infection, creating a very long-term prediction of a pandemic. Common wave shape patterns can also be identified, to predict the pattern of mutations that have recently occurred, but have not become popularly known as yet, to predict the remaining future outcome of the wave. By only considering the patterns in the data that could possibly have acted in tandem to generate the observed results, many false patterns can be eliminated, and, therefore, hidden variables can be estimated to a very high degree of probability. Similar mathematical relationships can reveal hidden variables in other underlying differential equations.Item MATHEMATICS OF THE DYNAMICS AND CONTROL OF THE SARS-COV-2 PANDEMIC(2024) Pant, Binod; Gumel, Abba B.; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The pneumonia-like illness that emerged late in 2019, caused by SARS-CoV-2 (and coined COVID-19), became the greatest public health challenge humans have faced since the 1918/1919 influenza pandemic, causing over 670 million confirmed cases and 7 million fatalities globally. This dissertation contributes in providing deep qualitative insights and understanding on the transmission dynamics and control of the pandemic, using mathematical modeling approaches together with data analytics and computation. Specifically, it addresses some of the pertinent challenges associated with modeling the dynamics of the disease, notably the disproportionate effect of the disease on certain (risk and demographic) populations (inducing various heterogeneities) and behavior changes with respect to adherence or lack thereof to interventions. An $m-$group model, which monitors the temporal dynamics of the disease in m heterogeneous populations, was designed and used to study the impact of age heterogeneity and vaccination on the spread of the disease in the United States. For instance, the disease-free equilibrium for the case of the model with m=1 (i.e., the model with a homogeneous population) was shown to be globally-asymptotically stable for two special cases (when vaccine is perfect or when disease-induced mortality is negligible) whenever the associated reproduction number of the homogeneous model is less than one. The homogeneous model has a unique endemic equilibrium whenever the reproduction threshold exceeds unity (this equilibrium was shown to be globally-asymptotically stable for a special case, using a nonlinear Lyapunov function of Goh-Volterra type). The homogeneous model was fitted to the observed cumulative mortality data for the SARS-CoV-2 pandemic in the United States during the period from January to May of 2022 (when Omicron was the predominant variant). It was shown that vaccine-derived herd immunity (needed to eliminate the disease) cannot be attained using the homogeneous model regardless of the proportion of individuals fully vaccinated. Such vaccine-derived immunity can, however, be achieved using the $m$-group heterogeneous model, with $m=2$ (where the total population is split into two groups: those under 65 years of age, and those 65 years and older), if at least 61\% of the susceptible population is fully vaccinated. Thus, this dissertation shows that heterogeneity reduces the level of vaccine coverage needed to eliminate the pandemic (and models that do not account for heterogeneity may be over-estimating the vaccination coverage needed to achieve herd immunity in the community). To quantify the impact of human behavior changes on the spread and control of the pandemic, we designed a novel behavior-epidemiology model which considers numerous metrics for inducing human behavior changes (such as current level of disease burden and intervention adherence fatigue). Unlike the equivalent model without human behavior explicitly incorporated, the behavior-epidemiology model fits the observed cumulative mortality and predicts the observed daily mortality data very well. It was also shown that the behavior metrics related to the level of SARS-CoV-2 mortality and symptomatic transmission were more influential in inducing positive behavior changes than all other behavior metrics considered. Finally, a model was developed to assess the utility of wastewater surveillance to study the transmission dynamics and control of SARS-CoV-2 in a community. Specifically, we developed and calibrated a wastewater-based epidemiology model using wastewater data from Miami-Dade county, Florida, during the third wave of the SARS-CoV-2 pandemic. The model showed a strong correlation between the observed (detected) weekly case data and the corresponding weekly data predicted by the calibrated model. The model's prediction of the week when maximum number of SARS-CoV-2 cases will be recorded in the county during the simulation period precisely matched the time when the maximum observed/reported cases were recorded (August 14, 2021). Furthermore, the model's projection of the maximum number of cases for the week of August 14, 2021 was about 15 times higher than the maximum observed weekly case count for the county on that day (i.e., the maximum case count estimated by the model was 15 times higher than the actual/observed count for confirmed cases). In addition to being in line with other modeling studies, this result is consistent with the CDC estimate that the reported confirmed case data may be 10 times lower than the actual (since the confirmed data did not account for asymptomatic and presymptomatic transmission). Furthermore, the model accurately predicted a one-week lag between the peak in weekly COVID-19 case and hospitalization data during the time period of the study in Miami-Dade, with the model-predicted hospitalizations peaking on August 21, 2021. Detailed time-varying global sensitivity analysis was carried out to determine the parameters (wastewater-based, epidemiological and biological) that have the most influence on the chosen response function (namely, the cumulative viral load in the wastewater). This analysis identified key parameters that significantly affect the value of the response function (hence, they should be targeted for intervention). This dissertation conclusively showed that wastewater surveillance data can be a very powerful indicator for measuring (i.e., providing early-warning signal and current burden) and predicting the future trajectory and burden (e.g., number of cases and hospitalizations) of emerging and re-emerging infectious diseases, such as SARS-CoV-2, in a community.Item COVID-19 Vaccine Hesitancy and Uptake in the United States Considered Through the Lens of Health Behavior Theory(2024) Kauffman, Lauren Emily; Nguyen, Quynh; Epidemiology and Biostatistics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Given the low COVID-19 vaccine uptake rates in many areas of the United States despite their demonstrated safety and effectiveness, COVID-19 vaccine hesitancy and vaccination barriers continue to be critical areas of research in epidemiology and behavioral health science. This series of studies focuses on COVID-19 vaccine hesitancy and vaccination barriers, as they relate to vaccination intention and vaccine uptake, considered in the context of established health behavior theories. The first study is a systematic review of existing research on COVID-19 vaccine hesitancy using one or more health behavior theories as key components of the design or analysis. This study examined the types of theories that are most often used, how they are used, and where research gaps exist. The remaining two studies use data from the U.S. COVID-19 Trends and Impact Survey, a national cross-sectional survey. The second study investigates the association between recent feelings of anxiety or depression and vaccination intention, as well as between these feelings and identifying with specific vaccine hesitancy reasons. The third study examines vaccine hesitancy and barriers among those with chronic illness or disease, a particularly vulnerable population. Factor analysis was conducted using constructs from the Theory of Planned Behavior as a framework, and the results were used in a regression model to investigate the association between these underlying factors and vaccination intention. This research demonstrated the usefulness of the Theory of Planned Behavior, the Health Belief Model, and the 3 Cs Model in existing and future COVID-19 vaccine hesitancy research, as well as identified Protection Motivation Theory as a promising area for future research. Additionally, psychological states were demonstrated to be significantly associated with vaccine hesitancy, adjusting for demographic, socioeconomic, and time factors. Lastly, the Theory of Planned Behavior was found to be applicable to those unvaccinated and with chronic illness, as the construct factor scores developed were significantly associated with vaccine hesitancy (adjusting for the presence of specific chronic conditions and demographic, socioeconomic, and time factors). These associations were also consistently demonstrated in subgroup analyses of participants with specific chronic conditions.Item The Role of Personal Integrity in Shaping Healthcare Worker Perceptions of Patient Safety Culture in US Hospitals During the Covid-19 Pandemic(2024) Edelstein, Lauren Michelle; Franzini, Luisa; Health Services Administration; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Abstract Overview: The COVID-19 pandemic strained hospitals in unprecedented ways that required healthcare workers to adapt to and endure challenges, testing their ability to do a good job with the human and technological resources available to them. Using a proxy variable for personal self-integrity (PSI), derived from questions on the Agency for Healthcare Research and Quality (AHRQ) Hospital Survey on Patient Safety Culture (HSOPS), this dissertation explores the way workers’ capacity to maintain alignment of their actions and morals shifted during the pandemic. Conceptual Framework: The investigations within this study can be understood through the Healthcare Workforce Integrity Model, an innovation based on the Job Demands and Resources Model that accounts for the deeply moral nature of healthcare work. The model holds that intensity of job demands and the strength of supportive job resources shape workers’ abilities to maintain PSI in their work. Over a sustained period, this impacts worker energy and motivation, and ultimately, organizational resilience. Methods: The study uses descriptive statistics and regression modeling based on data from the AHRQ’s HSOPS and data from the Hospital Cost and Utilization Project (HCUP), from timeframes before and during the COVID-19 pandemic, to analyze shifting perceptions about patient safety culture within the hospital workforce. Results: Workers’ capacity to maintain their PSI worsened steadily over the pandemic. When patient mortality was higher, workers’ PSI worsened, with particularly acute effects experienced in ICU settings. When hospital workers perceived teamwork and leadership support negatively, and when they perceived that staff were blamed for patient safety problems, their perceptions of their own personal integrity diminished by statistically significant margins. No significant associations indicate that hospital workers’ perceptions of teamwork, leadership support, or being blamed for safetyproblems were more closely tied with their ability to maintain positive PSI during the pandemic than they were before the pandemic. Conclusions: Organizational solutions are needed to support healthcare workers’ ability to thrive and maintain integrity in non-crisis moments just as much as they are needed during moments of crisis and uncertainty. Achieving this goal can better ensure that healthcare workers feel they can depend on their institutions and its people to do the right thing.Item EXPLORING TEMPORAL AND SPATIAL VARYING IMPACTS ON COMMUTE TRIP CHANGE DUE TO COVID-19(2023) Saleh Namadi, Saeed; Niemeier, Deb; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)COVID-19 has deeply affected people’s daily life and travel behaviors. This study uses large-scale mobile device location data at the U.S. county level in the DMV area to reveal the impacts of demographic and socioeconomic variables on commute trip change. The study investigates the contribution of these variables to the temporal and spatial varying impacts on commuter trips. It reflects the short and long-term impact of COVID-19 on travel behavior via linear regression and geographically weighted regression models. The results indicate that commute trips decreased with more white-collar jobs, while blue-collar sectors demonstrated the opposite effect. Unexpectedly, elderly individuals, who were highly vulnerable to COVID-19, negatively correlated with decreased commute trips. Moreover, in the DMV area, counties with a higher proportion of Democratic voters also showed a negative correlation with reduced commute trips. Notably, the pandemic's impact on commuting behaviors was global at the onset of COVID-19. Still, the effects exhibited local correlations as the pandemic evolved, suggesting a geographical impact pattern.Item WHEN GLOBAL CONSPIRACY THEORIES BECOME LOCAL PROPAGANDA: THE INFLUENCE OF CHINA AND U.S. RIGHT-WING COVID-19 NARRATIVES ON TAIWAN(2023) Li, Wei-Ping; Oates, Sarah; Journalism; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation examined how foreign conspiracy theories propagated by authoritarian countries traverse national borders and are transformed into “news” in domestic media systems. It also assessed the impact of these conspiracy theories incorporated into the transnational information campaign as propaganda tools. Using the controversial COVID-19 virus-origin theory as a case study, this dissertation examined how the COVID-19 virus-origin conspiracy theories were constructed as propaganda by Chinese state media and how these conspiracy theories influenced the media in Taiwan, which has historically been the main target of China's information influence activities. After analyzing COVID-19 virus-origin narratives that contained conspiracy theories propagated by Chinese state media, the study found that the Chinese state media constructed its narratives about the origin of the COVID-19 virus by repeating consistent themes, recurrent terms, and assigning distinctive personalities to key protagonists in news events. The Chinese state media portrayed China as a team player in the international community and collaborated with the international community by sharing data openly. However, the United States and other Western nations attempted to contain the rise of China by attacking it with conspiracy theories about the origin of the virus. The Chinese narratives were mostly rejected by mainstream Taiwanese media. Although Taiwanese media mentioned some conspiracy theories promoted by Chinese state media, Taiwanese media were aware of Chinese propaganda and disinformation. They also viewed the disputes between China and the United States regarding the origin of the virus as a struggle for power between the two nations. Even though Taiwanese media and Chinese state media used identical terms to describe the same news events about the origin of the COVID-19 virus and highlighted the same protagonists, Taiwanese media presented narratives that were in stark contrast to Chinese media. The research concluded that Chinese state media had limited influence on Taiwanese media in the case of COVID-19 virus-origin narratives. Nonetheless, this study also uncovered a concerning trend: a number of Taiwanese media articles amplified conspiracy theories disseminated by right-wing American media outlets, such as the War Room, Newsmax, or overseas Chinese media organizations notorious for spreading disinformation. The improper use of foreign media as news sources is one of the vulnerabilities of Taiwanese media in the battle against foreign propaganda and conspiracy theories. This dissertation increased the understanding of the influence of conspiracy theories propagated by authoritarian regimes and identified elements crucial to their success or failure as propaganda tools. Moreover, it sheds light on the strengths and weaknesses of media systems in democratic nations when battling against foreign propaganda. The findings of this study are useful not only to Taiwan but also to democratic and open societies worldwide.Item MATHEMATICS INSTRUCTION IN JUVENILE CORRECTIONAL FACILITIES DURING COVID-19(2023) Ross Benedick, Amanda; Taboada Barber, Ana; Special Education; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Students with disabilities are overrepresented in correctional settings in the United States and there is a dearth of information in the professional literature about the adequacy of instruction for these youth. Moreover, during the recent COVID-19 pandemic (2020-2022), access to education was abridged for many youth including those in juvenile correctional facilities (JCFs). This dissertation addresses the adequacy of academic instruction in juvenile corrections with a specific focus on mathematics instruction for youth receiving special education services. After an introduction to the topic in this first chapter, Chapter II presents a systematic review of academic and vocational interventions in juvenile correctional facilities (JCFs). Chapter III presents a descriptive study of special education mathematics teachers in JCF. Among other things the survey attempted to provide a snapshot of curriculum choices, instructional contexts, instructional adaptations for students with disabilities, and barriers to instruction for students during the initial weeks (March 20, 2020, through July 31, 2020) of the COVID-19 pandemic. The survey was framed by the existing literature on evidence- based mathematical curriculum and instructional approaches found to be successful in traditional secondary school settings. Results showed that the 31 respondents infrequently used state and locally based curriculum, frequently incorporated the use of student calculators when teaching, and found only a few barriers to teaching during the initial weeks of COVID-19 pandemic.Chapter IV provides suggestions to practitioners working in JCFs in preparation for any future health emergency. While directed at special education mathematics teachers and administrators in these facilities, other practitioners who work in JCFs could benefit from these tips. Proactive planning is a theme present in all the suggestions created in response to the concerns and needs presented by both administrators and teachers working in JCF at the start of the COVID-19 pandemic. Chapter V summarizes and synthesizes information from the systematic literature review, the empirical study presented in Chapter III, and the suggestions for practitioners presented in Chapter IV. The final chapter also discusses implications that flow from the elements of the dissertation and suggests areas for future research.Item A CRITICAL FEMINIST METHODOLOGY OF UNDERGRADUATE BLACK WOMXN AT HWIs & HOW THEY DEFINED, CREATED, AND SUSTAINED COMMUNITY AND SUPPORT DURING BLM, COVID-19, AND VIRTUAL LEARNING(2023) Greene, Patrice; Kelly, Dr. Bridget Turner; Counseling and Personnel Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The simultaneous impact of COVID-19, BLM racial uprisings, and virtual learning caused a societal shift as a global pandemic, global protests, and widespread campus closures placed the world in unprecedented times. Though these societal events had a profound global impact, how undergraduate Black womxn experienced and navigated these times is understudied throughout literature. This study explored how undergraduate Black womxn at historically white institutions (HWIs) defined, created and sustained community and support during the societal context of Black Lives Matter (BLM), COVID-19, and virtual learning. Utilizing Black Feminist Thought and critical feminist methodology, eight collaborators shared their experiences through individual interviews, artifact reviews, and a focus group. The study focused on two guiding questions: 1.) How are undergraduate Black womxn at historically white institutions defining community and support in the context of COVID-19, BLM, and virtual learning? And 2.) How have undergraduate Black womxn at historically white institutions supported and built community with one another during COVID-19, BLM, and virtual learning? The findings revealed these emergent themes: (1) Defining and (Re)Defining Community and Support, (2): Navigating COVID-19, BLM, and Virtual Learning: Emotional Processing, (3): Seeking and/or Continuing Inclusive Curricular Co-Curricular Experiences, (4) BLM & The Pandemic: An Opportunity for Understanding Within and Across the Diaspora, and (5): The Role of Social Media and Technology in Creating and Sustaining Community and Support. The findings illuminate how Black womxn undergraduate students ascribe meaning to community and support and how they traversed the emotional impact of the societal shift.Item CYCLING AROUND THE CLOCK: MODELING BIKE SHARE TRIPS AS HIGH-FREQUENCY SPATIAL INTERACTIONS(2023) Liu, Zheng; Oshan, Taylor; Geography/Library & Information Systems; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Spatial interactions provide insights into urban mobility that reflects urban livability. A range of traditional and modern urban mobility models have been developed to analyze and model spatial interaction. The study of bike-sharing systems has emerged as a new area of research, offering expanded opportunities to understand the dynamics of spatial interaction processes. This dissertation proposes new methods and frameworks to model and understand the high-frequency changes in the spatial interaction of a bike share system. Three challenges related to the spatial and temporal dynamics of spatial interaction within a bike share system are discussed via three studies: 1) Predicting spatial interaction demand at new stations as part of system infrastructure expansion; 2) Understanding the dynamics of determinants in the context of the COVID-19 pandemic; and 3) Detecting events that lead to changes in the spatial interaction process of bike share trips from a model-based proxy. The first study proposes a hybrid strategy to predict 'cold start' trips by comparing flow interpolation and spatial interaction methods. The study reveals 'cold start' stations with different classifications based on their locations have different best model choices as a hybrid strategy for the research question. The second study demonstrates a disaggregated comparative framework to capture the dynamics of determinants in bike share trip generation before, during, and after the COVID-19 lockdown and to identify long-term bike share usage behavioral changes. The third study investigates an event detection approach combining martingale test and spatial interaction model with specification evaluation from simulated data and explorative examination from bike share datasets in New York City, Washington, DC, and San Francisco. Results from the study recognize events from exogenous factors that induced changes in spatial interactions which are critical for model evaluation and improvement toward more flexible models to high-frequency changes. The dissertation elaborated and expanded the spatial interaction model to more effectively meet the research demands for the novel transportation mode of bike-share cycling in the context of a high-frequency urban environment. Taken as a whole, this dissertation contributes to the field of transportation geography and geographic information science and contributes methods toward the creation of improved transport systems for more livable cities.