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ASSESSING EXPECTATIONS FOR RECOVERY, PATIENT ACTIVATION, AND SELF-EFFICACY FOLLOWING PATIENT STAY IN THE CARDIAC INTENSIVE CARE UNIT
No full textExpectations for recovery are increasingly recognized as a critical yet understudied factor influencing psychological and behavioral responses following critical illness. In the context of cardiac intensive care unit (CICU) hospitalization, how patients perceive their recovery trajectory may shape engagement in post-discharge care, self-management, and long-term health outcomes. Despite emerging interest, evidence remains limited and fragmented, particularly for individuals with chronic cardiac conditions managed in critical care settings.
This dissertation sought to advance understanding of expectations for recovery among CICU survivors through three sequential studies: (1) an integrative literature review; (2) a cross-sectional analysis of predictors of expectations for recovery; and (3) a longitudinal investigation of how expectations relate to coping self-efficacy and patient activation over the early post-discharge period. The literature review synthesized 23 studies examining expectations for recovery among adults with critical cardiac illness, highlighting conceptual inconsistencies and identifying sociodemographic and clinical factors that shape recovery outlooks. Building on these findings, a cross-sectional study (N = 98) from the Wellness and Needs of Men and Women after a Cardiac ICU Stay Study (WellNOW) cohort examined associations between patients’ baseline expectations for recovery and key psychosocial and clinical characteristics. Finally, longitudinal analyses evaluated the relationship between expectations for recovery and coping self-efficacy (N = 132) and patient activation (N = 92) from baseline to three months post-discharge, using mixed-effects modeling and multiple imputation to account for missing data.
The literature review revealed that higher expectations for recovery were associated with improved functional and psychological outcomes; however, measurement approaches were inconsistent, and chronic cardiac conditions in the context of cardiac critical illness were rarely examined. In the cross-sectional study, higher depressive symptoms and lower income were significantly associated with lower expectations for recovery, whereas clinical severity was not. Longitudinal analyses demonstrated that higher expectations for recovery were consistently associated with greater coping self-efficacy over time. Although the association between expectations and patient activation was attenuated in adjusted models, a potential interaction with time suggested that expectations for recovery may help sustain engagement during the recovery process.
Expectations for recovery represent a meaningful, modifiable factor that may shape psychological adjustment and self-management among CICU survivors. This dissertation highlights the importance of incorporating expectations assessment into routine clinical care and designing interventions that foster realistic and positive recovery outlooks. Targeting expectations early in the recovery process may enhance coping capacity and maintain patient activation during the vulnerable transition from hospital to home
Gifted in Stress: A Qualitative Study of Stress in Gifted Teens
No full textThis qualitative research study involved a further investigation of stress factors in middle school teens at Midwestern Middle School (a pseudonym) through the lens of 12 stakeholders, including parents, teachers, and school counselors. A review of the literature in Chapter 1 revealed major stress factors related to both academic and interpersonal stress. The following research questions guided the study: What strategies do stakeholders use at a gifted program in a public midwestern middle school to detect or ascertain if gifted middle school students are experiencing academic stress? What strategies do stakeholders use at a gifted program in a public midwestern middle school to detect or ascertain if gifted middle school students are experiencing stress in their interpersonal relationships? What do stakeholders at a gifted program in a public midwestern middle school perceive as causes of student academic stress? What do stakeholders at a gifted program in a public midwestern middle school perceive as causes of student interpersonal stress? What changes are observed in reported stress by gifted middle school students in a public midwestern middle school over the fifth, sixth, seventh, and eighth grades? Using a qualitative narrative inquiry study design, semi-structured interviews with 12 stakeholders, including parents, teachers, and school counselors, were conducted at a suburban midwestern middle school. The thematic analysis identified emergent themes capturing the stress experienced by gifted teens: academic stress (pressures of fear of failure, pressures of perfectionism) and interpersonal stress (pressures of peer relationships, pressures of parent and community expectations). These pressures were observed by stakeholders through observations of the gifted teens’ autonomic nervous system response states. The findings suggest a critical need for additional emotional support services for gifted teens and ongoing professional development for educators. Recommendations include implementing a mental health check-in for gifted teens, providing educational services to parents and educators, and diversifying classes for gifted teens
Hybrid Semiconductor Optoelectronics for Power Generation, Sensing, and Carbon Capture
No full textOne of the grand challenges of the 21st century is the fight against climate change. It is imperative that humanity pursue renewable energy sources and ways of undoing the harm inflicted on the biosphere. Given this, several new methods and devices in the field of solution-processed photovoltaics and carbon capture are introduced in this thesis.
First, we introduce a novel mass data collection method and a machine learning model that accelerates the characterization process of solar cells. This method utilizes a translation stage which moves devices in 25µm steps, while a fixed beam probes the sample. By treating each step as a separate device, massive quantities of training data can be gathered. Furthermore, a new process now allows us to convert 1D current-voltage curves to 2D images, which enables the use of convolutional networks and other architectures normally reserved for image/vision-based applications. We test our methods on colloidal quantum dot (CQD) solar cells. Researchers can now measure a single current-voltage curve and obtain multiple materials parameters in a matter of seconds.
Second, we introduce a brand-new type of dye sensitized solar cell (DSSC) that performs both power generation and carbon capture simultaneously. Instead of traditional redox couples found in DSSCs, we use CO2 sorbents capable of undergoing reversible redox reactions. CO2 can now be captured using sunlight as the sole energy source under ambient conditions.
Third, we use our mass data collection method to investigate perovskite photovoltaics for indoor lighting applications, specifically, differences between MAPI (methylammonium-lead-iodide) and TA (MAPbI2.6Br0.2Cl0.2) material systems. Differences in open-circuit voltage deficit maps between the two cells were used to check for non-uniformity and study macroscopic defects. The results explain why MAPI cells may be more suitable for indoor photovoltaics and provide insight into further improving these technologies.
Lastly, we explore novel horizontal and vertical field effect transistors (FETs) which allow researchers to probe formerly inaccessible materials parameters of PbS CQD thin films, specifically anisotropic carrier transport. We found that FET performance depended on architecture and ligands, with halide-treated planar devices showing higher mobility due to vertical devices being limited by film strain and tunneling effects
Iron and Flavins: Essential Nutrients in the Fungal Pathogen Candida albicans
Get PDFCandida albicans, the most prevalent human fungal pathogen, is of high public health concern. It causes both mild mucosal and potentially fatal systemic infections. During infection, the innate immune system employs nutritional immunity to starve pathogens of vital micronutrients, including iron (Fe), leading to anemia of infection. Fungal pathogens have adapted to survive this Fe-limitation. In this thesis, we examine several pathways involved in fungal adaptation to Fe-starvation, which are possible future therapeutic targets.
In Chapter 2, we examine Fe-sensing and homeostasis through a novel mechanism involving C. albicans metal transporter Smf11 and ferric reductase Fre1. Mutants of both SMF11 and FRE1 hyperaccumulate Fe but behave Fe-starved. Due to Fe-overload and poor Fe-sensing, these mutants exhibit defective hyphal morphogenesis, a state important for virulence, and lose the ROS burst of morphogenesis, which requires Fe. Additionally, these mutants show delayed growth and sensitivity to cell wall-targeting antifungals. In our model, Smf11 and Fre1 partner to transport ferrous Fe for Fe-sensing and Fe homeostasis.
In Chapter 3, we examined a curious response to fungal Fe-starvation: flavin secretion. Flavins are essential, redox-active, yellow compounds. Vitamin B2, riboflavin, is a precursor of FMN and FAD, necessary enzyme cofactors. C. albicans was previously shown to secrete an unknown flavin during Fe-starvation. We used HPLC and mass spectrometry to identify this as riboflavin. Under Fe-starvation conditions, intracellular flavins show a marked increase in riboflavin, without increasing FMN or FAD. This was corroborated through our mRNA analysis, where genes for riboflavin synthesis, but not flavin conversion, are upregulated by Fe-starvation. This process is mediated by the Fe-sensing transcription factor, Sef1, and mutants of SEF1 are defective in flavin secretion. Finally, we provide the first evidence that riboflavin assists in Fe uptake from serum, providing a possible role for riboflavin secretion during infection.
Lastly, in the appendix, we investigate the effects of Fe-starvation on mitochondrial flavins. We observe that FMN predominates in crude mitochondria, while FAD predominates in whole cells. Interestingly, mitochondria showed no increased riboflavin under Fe-starvation.
Overall, this thesis illuminates Fe sensing, acquisition, and homeostasis in C. albicans, illustrating the importance of Fe for fungal pathogens
ESSAYS IN LABOR ECONOMICS
Get PDFThese essays focus on research questions in labor economics, aiming to evaluate and design policies that improve the well-being of individuals affected by adverse economic shocks and those raised in disadvantaged environments.
Chapter 1 evaluates the long-term effects of unemployment insurance (UI) on post-displacement outcomes. I find that a 13-week extension in maximum UI duration reduces long-term earnings losses by 10–15% over a 10-year period. This reduction is primarily driven by an increase in hours worked, with minimal impact on wage rates. Evidence from the data and a search model suggests that the increase in labor supply is driven by improvements in non-pecuniary job attributes, which result from shifts in reservation utility.
Chapter 2 investigates the impact of maternal job displacement on children's educational attainment in single-mother households. After accounting for pre-displacement partnership dynamics, partner income, and the duration of single motherhood, I find that the effects on children’s educational outcomes are generally small and, in some cases, even positive depending on the child’s age at the time of displacement. These patterns are largely explained by differential household income dynamics following displacement.
Chapter 3 examines how genetic propensity for same-sex sexual behavior is associated with sexual orientation and socioeconomic outcomes from adolescence to adulthood, and how it interacts with the adolescent environment, measured by parental religiosity. We find that greater genetic propensity is associated with a higher likelihood of same-sex sexual behavior and risky behaviors, as well as worse mental health, educational attainment, and labor market outcomes. In contrast, higher parental religiosity is associated with a lower likelihood of same-sex sexual behavior and risky behaviors, and with better mental health, education, and labor market outcomes. Examining gene–environment interactions, we find that genetic propensity for same-sex sexual behavior interacts strongly with parental religiosity in predicting some of these outcomes
Weaponized Deception: The Nature and Consequences of Russian Biological Weapons Disinformation
No full textWhen Russia began its full-scale invasion of Ukraine in 2022, it also began a coordinated disinformation (false information that is spread intentionally) campaign accusing the United States of developing biological weapons in Ukrainian laboratories. While this campaign has received considerable attention, its associated allegations are not new, as Russia has long (and falsely) accused the United States of conducting illicit biological activities in the post-Soviet space. Such allegations have raised concerns among scholars, who have argued that Russian disinformation could undermine peaceful biological activities, weaken the Biological Weapons Convention (or BWC, the international treaty banning the development of biological weapons), or erode the global norm against biological weapons. However, there is much about Russian biological weapons disinformation that remains unknown. This dissertation examines the nature and consequences of Russian biological weapons disinformation, providing policy makers and communicators with empirical evidence to inform decision making.
This dissertation consists of three specific aims. In Aim 1, a mixed-methods analysis of BWC meeting recordings, transcripts, and documents revealed that discussion of Russia’s false allegations at the BWC 9th Review Conference resulted in lost time, inability to achieve consensus, and potential mistrust and discord between states parties. In Aim 2, qualitative analysis of 199 pro-Kremlin news media items was used to develop of a taxonomy of Russian biological weapons disinformation. This taxonomy can be used to inform interventions to pre-empt and counter future Russian disinformation campaigns. In Aim 3, a virtual red teaming simulation exercise revealed that Russian disinformation can affect state actors’ interest in pursuing both offensive and defensive activities related to biological weapons.
Together, findings from this dissertation reveal the dangers posed by Russian biological weapons disinformation—dangers to the integrity of the BWC and to the global norm against biological weapons. However, findings from this project also suggest that there are steps policy makers can take to mitigate some of these harms, including the development of debunking and prebunking interventions. As global tensions persist and technological advances continue to lower the barriers to causing harm (whether through biological weapons or disinformation), such approaches should be developed, tested, and implemented urgently
From Data to Decisions: Engineering Pathways to Equitable and Resilient Public Health Systems
No full textInfectious diseases represent one of the most significant threats to human well-being, capable of causing immense loss of life, disrupting economies, and deepening social inequities. To combat these threats, societies depend on robust infectious disease modeling to guide public health responses. However, creating models that are both accurate and equitable requires a collaborative effort across diverse fields, including epidemiology, computer science, economics, and social science. In this complex landscape, engineering provides the essential bridge, offering systematic approaches to translate interdisciplinary insights into functional, data-driven solutions. This dissertation embodies engineering approaches through two interrelated thrusts.
The first research thrust advances short-term infectious disease forecasting by developing multimodal machine learning frameworks. These include a deep-learning model that integrates diverse disease-relevant data streams (Chapter 2), such as epidemiological and mobility data, alongside a Large Language Model-based architecture (PandemicLLM) that reframes forecasting as a text-reasoning task (Chapter 3).
Recognizing that real-world human behavior often drives disease dynamics, the second research thrust moves beyond forecasting to model human behavior in complex systems. This is accomplished first by using large-scale mobility data to empirically measure widening behavioral inequities between socioeconomic groups since the COVID-19 pandemic (Chapter 4) and second by developing a Feedback-Informed Epidemiological Model (FIEM) to simulate how individual health-wealth trade-offs interact with disease spread mechanistically (Chapter 5).
Collectively, this thesis provides new directions for infectious disease modeling by advocating integrated computational approaches and emphasizing the importance of human behavior. The insights and frameworks developed herein strengthen the ‘data to decisions’ pipeline, with the ultimate goal of supporting more equitable and resilient public health systems
Running on Hope: Female Community Health Labor in Rajasthan, India
No full textThroughout India, Accredited Social Health Activists (ASHAs) visit households in their communities to deliver essential health services and link community members with key health benefits. Like many other female Community Health Workers across the world, ASHAs are often portrayed as virtuous, passive volunteers, selflessly providing services to their neighbors.
The reality is more complicated and much more interesting. Drawing on ethnographic work in Rajasthan, Running on Hope follows ASHAs through striking personal transformations. From their positions as rural daughters‑in‑law—a particularly low‑power position in Rajasthan—ASHAs have, over years of work, gained unprecedented autonomy for young rural women. They have also gained a deep understanding of what many argue is the exploitation involved in their low‑ranking position in the health system. ASHAs often earn less than $100 per month for extensive work, well below the legal minimum wage.
To counter this, many ASHAs have joined unions—an endeavor that has ultimately proven disappointing: union leaders’ desires for political advancement are often at odds with ASHAs’ own needs. However, ASHAs do not have connections, money, or social power to organize effectively on their own, without a political patron. In Running on Hope, authors Svea Closser and Surendra Singh Shekhawat interview women who work as ASHAs to learn about their organizing goals, their roles in their community as conduits to health education and resources, and their hopes for a better future
Precursor and Substrate Design Principles Enabling Control of Two-Dimensional Crystal Properties
Get PDFTwo-dimensional (2D) transition metal dichalcogenides (TMDs) have emerged as a transformative class of materials owing to their atomically thin profiles and unique mechanical, electronic, and optical properties. These attributes make them promising candidates for applications in next-generation technologies, including flexible electronics, optoelectronics, and energy storage systems. However, the ability to fully harness these properties is currently limited by challenges in synthesis, particularly with respect to controlling the crystallinity, uniformity, morphology, and defect density of the resulting materials. This dissertation addresses these challenges through the systematic design of precursors and substrates, with the aim of enabling precise control over 2D TMD crystal properties during chemical vapor deposition (CVD) processes.
The first part of the research introduces a seeded growth strategy that combines top-down etching and bottom-up synthesis to produce size-tunable, monodisperse oxide seeds. These seeds are used to nucleate MoSe2 crystals via CVD, resulting in highly uniform and well-defined 2D materials. This approach is shown to enable independent control over crystal size and thickness with high reproducibility. The second part of the work focuses on substrate engineering, in which Si(001) substrates are modified using phosphine (PH₃) gas. This method enables the growth of MoSe2 crystals with reduced defect densities. Furthermore, by increasing the PH₃ dosage and incorporating salt-assisted methods, this platform is extended to produce MoSe₂/MoS₂ heterostructure nanoribbons with tailored lateral architecture.
Altogether, this dissertation develops and demonstrates a set of design principles for controlling the nucleation, growth, and structural quality of 2D TMDs. These strategies not only deepen our mechanistic understanding of precursor-substrate interactions in CVD synthesis but also offer practical methodologies for scalable production of high-quality TMDs with tunable properties. The insights gained here pave the way for more reproducible, customizable, and application-specific 2D materials synthesis, with broad implications for the development of future nanoelectronic and optoelectronic devices
SIGNALS RELATED TO SEQUENTIAL DECISION-MAKING IN THE NON-HUMAN PRIMATE CEREBRAL CORTEX
Get PDFIn this thesis, I investigated the neural mechanisms underlying sequential decision- making using the framework of reinforcement learning. In the first set of experiments, I examined cortical activity in scenarios where integrating information about previous choices and rewards was either beneficial or irrelevant for guiding future decisions. Single-unit activity from five cortical regions, the dorsolateral prefrontal cortex (dlPFC), dorsomedial prefrontal cortex (dmPFC), dorsal anterior cingulate cortex (ACCd), orbitofrontal cortex (OFC) and lateral intraparietal area (LIP) were analyzed. I found that nonlinear interaction between two successive choices in the prefrontal cortex, specifically dlPFC and ACCd, tracked the behavioral relevance of learning from past experiences.
In the second set of experiments, I explored how the hippocampus supports model- based planning in non-human primates using an abstract maze task. In this task, monkeys learned to make a series of interdependent choices to reach a long-term goal. Behavioral analyses showed that the monkeys predominantly relied on a model-based reinforcement learning strategy, with some influence from model-free mechanisms. Analyzing single- and multi-unit activity from the hippocampus revealed that hippocampus encoded both the identity of individual states in the maze and their proximity to the goal, two key features essential for constructing an internal model of the environment.
Together, these findings suggest that the cerebral cortex in non-human primates encodes higher-order relationships between multiple actions generated by the animals and between multiple states in the environment. These representations contribute to the construction of internal models that facilitate adaptive and efficient decision-making