Master of Sciences, Case Western Reserve University, 2024, Medical Physiology

Adults over 65 are increasingly susceptible to infections due to the phenomena of immunosenescence and inflammaging. As this population grows in number and COVID- 19 becomes assimilated with yearly illnesses, assessment of the longitudinal immune response to infection and vaccination is paramount to recommending a vaccination schedule that maximizes the senescent immune system's capabilities. As a continuation of a longitudinal study, sera were collected from NHRs in Northeast Ohio at different time points in their vaccination series. Binding and pseudovirus neutralization assays were performed to assess antibody response against SARS-CoV-2, and decay character was compared between infection histories. We hypothesized that infection history modulates decay. Through assays and data analysis, we found that those with prior infection exhibit greater antibody longevity, and that vaccinations should be administered every 6 months to minimize antibody decay.

Master of Arts, The Ohio State University, 2023, Speech Language Pathology

Purpose: The family environments of deaf and hard-of-hearing (DHH) children are comparable to that of typically hearing (TH) children. However, structural and functional dimensions of family environments are more tightly coupled to spoken language development in DHH children than TH children (e.g., Holt et al., 2020, 2022). DHH families that have increased engagement in intellectual and cultural activities in a supportive environment, are more organized in time and space, and have less control and conflict have children with better spoken language. A limitation of previous studies is establishing the directionality of the effects because data about family environment and language were measured at the same time. This study aims to look at longitudinal data to test the hypothesis that the structural and functional dimensions of family environment contribute to DHH children's spoken language over a period of one year.  Method: Two groups of children (57 TH, mean age = 5.8 years; 53 DHH, mean age = 6.6 years, 25 with hearing aids, 28 with cochlear implants) were evaluated twice on standardized measures of spoken language comprehension and receptive vocabulary (Peabody Picture Vocabulary Test-Fourth Edition [PPVT-4], Following Directions/Concepts subscale of the Clinical Evaluation of Language Fundamentals-5/P [CELF 5/P], and Sentence Comprehension subscale of the Comprehensive Assessment of Spoken Language-2 [CASL-2]). Family environment was assessed with the Family Environment Scale – 4th edition (FES-4). Language was tested at Time 1 (T1) and Time 2 (T2; 10-14 months later). The FES-4 was completed at T1. Only participants who had complete data for both intervals were included. All children passed a non-verbal IQ screening and had a goal to learn spoken language. Both groups had comparable levels of parental education.  Results: Partial correlations (controlling for age) were carried out between T1 FES subscales and T2 language composite. For both groups, the F (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 2022, Psychology

Research on the development of mathematics attitudes and anxiety has found significant effects of parent and teacher mathematics anxiety and attitudes on developing children. These significant associations have been found as early as the 1st grade. However, little research has been done that examines the effects of parent and teacher mathematics anxiety and attitudes on younger children who are of pre-school age, and on the cusp of entering the more formalized educational system. The present study attempts to develop a measure of mathematics attitudes appropriate for pre-school children, named the Pre-School Mathematics Attitudes Task (PMAT). The present study also explores the test-retest reliability of the PMAT over a period of three months and explores the independent effects of parental mathematics anxiety and attitudes on their child's performance on the PMAT. Over a three-month period, the PMAT does not appear to demonstrate good test-retest reliability. Parental mathematics anxiety and attitudes were not significantly correlated with the PMAT. Nevertheless, this study lays important groundwork for future research in this area and examines a few promising areas for further study.

Master of Science (MS), Ohio University, 2022, Civil Engineering (Engineering and Technology)

This research reviewed the current and future uses of Ultra-High Performance Concrete (UHPC) for bridge applications in the state of Ohio. Since most designers, owners and contractors are unfamiliar with the material and only a small percentage of all bridges utilize it, UHPC is still considered a relatively new material. Monitoring and understanding its performance in current applications will undoubtedly provide useful insights for future applications. Advantages of UHPC discussed include rapid strength gain that can be utilized in Accelerate Bridge Construction, fiber content which provides post cracking strength, high bond strength which shortens development lengths of reinforcement, and the flowable material which allows UHPC to better penetrate tighter spaces. Disadvantages of UHPC such as material cost, increased labor and time are also discussed. In addition, recommendations for future UHPC applications are provided that would benefit designers, owners and contractors through valuable insight that was gained during these research objectives. The first objective was to review the performance of UHPC in the Sollars Road adjacent prestressed concrete box beam bridge in Fayette County. The design of the UHPC longitudinal joint (shear keys) included dowel bars but eliminated intermediate diaphragms, transverse post-tensioning, and a composite deck. Comparing truck loading data from 2014 shortly after bridge construction was completed and 2017 during this study, the load distribution has improved to some extent and the bridge is responding to loading in a similar manner which implies minimal to no cracking of the UHPC shear keys. This simplified design may be a realistic alternative to solve the typical issue of cracking in the longitudinal joints (shear keys) and associated reflective cracking in composite decks for adjacent prestressed concrete box beam bridges. This improved behavior with UHPC joints may result i (open full item for complete abstract)

Master of Arts, Case Western Reserve University, 0, Psychology

At some point in their lives, everyone will experience a stressful life event. Usually, someone can cope with and make meaning from the event. However, the body of research investigating the impact of severe and/or chronic exposure to stressful life events on the brain shows that harmful effects of stress exposure accumulate. Considering the extant literature regarding religious meaning making in light of these findings and the robust literature on spiritual transformation following stressful life events, I developed three hypotheses: 1) stressful life events increase risk of (non)religious ID change, 2) earlier events continued to impact later ID changes, and 3) risk of ID change was similar across change groups. This study analyzed a nationally representative longitudinal dataset of US children born between 1980 and 1984 (N = 8984). The final analyses used multiple imputation to account for missing data and did not find evidence supporting the hypotheses.

Master of Arts (MA), Bowling Green State University, 2015, Psychology/Clinical

Objective. Social capital is generally defined as an individual's potential for tangible or social resources made available via interpersonal connections. Higher levels are related to a variety of positive health, well-being, and occupational outcomes. Social capital can be measured by a variety of indices in adulthood. Currently, the childhood precursors to adult social capital are relatively unknown. The current project tests a developmental-contextual model for both the measurement of social capital in adulthood and the childhood precursors that may impact its accumulation over the life course. Methods. 523 participants were surveyed at age 8 and again at age 48 as part of a 40-year prospective, longitudinal study. Participants completed measures of cognitive abilities, relationships with parents, peers, and spouses, information about personal traits, and beliefs and attitudes regarding social relationships. Structural Equation Modeling (SEM) was used to test the hypothesized model. Results. The proposed measurement model of social capital was generally supported, with latent domains of individual, interpersonal, socio-economic, and community level indices. Predictive models of childhood precursors for social capital differed by gender: prominent precursors were childhood aggression and cognitive ability for males, and childhood family religiosity for females. Conclusions. These findings suggest that a developmental-contextual model of social capital may account for the multiple indices of social capital and that its accumulation across the life course is different for males and females. Knowledge of precursors may be clinically helpful for fostering social capital growth in therapeutic settings.

Doctor of Philosophy, Case Western Reserve University, 2007, Epidemiology and Biostatistics

This dissertation focuses on approaches to the genetic analysis of longitudinal measures of developmental disorders (DD) with specific application to a longitudinal pedigree study of children ascertained on the basis of a Speech Sound Disorder (SSD). Analysis of this longitudinal cohort is complicated by non-normal trait distributions and a potentially non-linear cognitive developmental trajectory. Prior to developing a longitudinal model I measured the power of the SSD dataset to correctly detect linkage of a quantitative trait to a genetic marker. Assuming that the function describing the genetic effect across time is correctly specified the power of the SSD data set is .18 at a .01 level of signficance. Additional data collection is planned and by doubling the sample size (from 200 to 400 sibling pairs) and number of measurement points (from 2 to 4) the power increases to .83 for the same significance level. It is therefore reasonable to develop a longitudinal approach for use at a later date. As an alternative to the longitudinal analysis, multivariate dependence functions, called copulas, are used to develop a cross-sectional model to test for polygenic*age interaction. These functions separate a multivariate joint distribution into two parts: one describing the interdependency of the probabilities (correlation), the other describing the distribution of the margins (the phenotypes). Using these functions for analysis simultaneously addresses both the non-normality problem, as the margins can be modeled with a wide variety of parametric probability distributions and the developmental trajectory question, as we incorporate age into the analysis through the use of a correlation function, the parameter estimate of which can be tested for significance using a chi-square test statistic. Four of the 13 SSD test measures showed nominal p-values less than .05. While at the broadest level the 4 tests measure different cognitive skills, short term memory plays an importan (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Psychology

This dissertation investigates the developmental trajectory of cognitive mechanisms underlying category learning and decision-making, with a particular focus on the role of cognitive control, working memory, and metacognition. The research attempts to address how children's cognitive processes transition from reliance on simpler, more automatic to more complex, goal-directed strategies. Chapter 3 explores the influence of cognitive control, specifically inhibition failure, in category learning contexts. It was hypothesized that immature cognitive control drives children's distributed attention, resulting in compression-based learning. To test this hypothesis, we introduced a paradigm that substantially decreased cognitive control (i.e., filtering) demands. If immature cognitive control is the principal driver of distributed attention, reducing such demands should result in greater attentional selectivity. However, the experimental results did not support the immature cognitive control hypothesis, instead pointing toward working memory as a more critical factor. This led to the formulation of the working memory hypothesis –compression-based, not selection-based learning results from immature working memory that cannot provide reliable guidance for selective attention. Chapter 4 presents an adult study using a dual-task paradigm to manipulate working memory capacity and assess its impact on attention distribution during category iii learning. The findings that under working memory load, adults tend to distribute attention establish a causal link between working memory and attention distribution. They suggest that immature working memory, rather than cognitive control, is the primary driver of distributed attention and compression-based category learning in children. Chapter 5 shifts to a longitudinal study that tracks the development from uncertainty-driven to performance-optimizing decision-making, discussed within the framework of metacognitive development. Th (open full item for complete abstract)

Master of Science in Engineering, Youngstown State University, 2024, Department of Civil/Environmental and Chemical Engineering

A longitudinal study in corrosion was performed on tensile-elongation dog-bones, created using 3D-printed stainless steel. The effects of exposure to an acidic environment were investigated regarding mass-loss, tensile and yield strength, modulus of elasticity, profilometry of pits and defects, and microscopy of fracture-sites. The SS316L specimens were manufactured using different print-directions, specifically overlapping unidirectional or rotated bidirectional for each layer by an additive manufacturing unit, the Mazak VC-500/5X AM HWD. The novel aspect of this research is focusing on the differences that the path the hot-wire, direct energy deposition, print-head has on its corrosion characteristics, as opposed to only focusing on the printing-parameters. The goal was to determine what printing-directions and methods were best for resisting corrosion. The research outlines the process of preparing samples for controlled weight-loss in HCl as well as the methods used to measure the mechanical properties. This allows for the results to be repeated if desired. Upon thoroughly reviewing the data and drawing connections where applicable, it was determined within the test samples that unidirectional print-directions yielded better mass-loss and mechanical attributes than bidirectional printing. It was found that some print directions, namely 90°, which is perpendicular to the printing door, performed notably better than other directions such as 0° or 45°.

MA, University of Cincinnati, 2024, Arts and Sciences: Geography

The escalating substance use disorder (SUD) crisis in the United States (US), marked by a significant rise in mortality since 1999, underscores the urgent need for a comprehensive analysis of its spatiotemporal dynamics. This study aims to elucidate the heterogeneous geospatial distribution of SUD mortality, identifying specific locations where vulnerable communities face heightened risk. By examining SUD mortality data from the US Center for Disease Control, for the period 2005-2020, scan statistics were used to delineate temporal and geospatial clusters of elevated SUD-related deaths, further dissecting these patterns across racial subpopulations and regions. Our findings reveal 27 distinct clusters nationwide, predominantly emerging post-2013 and persisting until 2020, indicating a shifting epicenter of the epidemic. Notably, the White subpopulation was associated with 26 clusters, closely mirroring the broader national trends, yet with a pronounced concentration in the eastern US. Conversely, the Black subpopulation demonstrated a different pattern, with 17 clusters arising between 2013 and 2020, primarily post-2015, suggesting a temporal and spatial divergence in the impact of the epidemic across racial subpopulations. This analysis not only highlights the critical need for targeted public health interventions and policies but also calls for continued surveillance to monitor and mitigate the evolving SUD crisis. By understanding the complex spatiotemporal and racial variations in SUD mortality, we can better allocate resources, develop effective prevention strategies, and support the communities most in need.

Doctor of Philosophy in Engineering, Cleveland State University, 2024, Washkewicz College of Engineering

Leveraging electronic health record data requires sophisticated methods that can optimally process this information to improve clinical decision-making. Artificial Intelligence (AI) promises to process healthcare data faster, for lower costs, and more accurately than conventional processes. Deep learning applied to longitudinal electronic health records (EHR) holds promise for disease prediction, but a systematic methods comparison has yet to be reported. Despite the promises of this technology, challenges remain in the current approaches to predicting a disease. There remains an unmet need for developing a gold-standard disease prediction framework for EHR data that can be reliably applied across many diseases. This research proposes a generalized deep learning approach that is amenable to predicting a vast number of diseases by integrating multiple streams of longitudinal clinical data and genomic features to maximize the predictive power over a broad spectrum of diseases. I provide empirical validation of the proposed solution using data from multiple datasets; including comprehensive simulated datasets and a real-world EHR datasets. The ultimate goal of this research is to develop a generalized deep learning approach that is amenable to predicting a vast number of diseases using longitudinal clinical data from the EHR.

Doctor of Philosophy, The Ohio State University, 2024, Nursing

Introduction: Colorectal cancer is the second leading cause of cancer-related deaths and was 7.8% of all new cancer diagnoses with a projected 153,020 new cases and 52,500 deaths in 2023. Colorectal cancer screening facilitates early detection thereby decreasing morbidity and mortality, yet screening rates in US health centers remain much lower than national goals. The purpose of this study was to understand organizational level factors of colorectal cancer screening uptake in medically underserved populations achieved by the following aims: 1) to rank colorectal cancer screening uptake in health centers and compare these colorectal cancer screening rates across health center characteristics and performance groups and 2) to examine how colorectal cancer screening rates change over time (6 years) in health centers and identify organizational level predictors (e.g., models of care, patient centered medical home, population health management) of rates of change. The National Institute on Minority Health and Health Disparities (NIMHD) research framework and the Donabedian model guided the study. Literature Review: Alarmingly, colorectal cancer screening has historically been lower among Black Americans, Native Americans, Alaskan Natives, Asian and Pacific Islanders, and those of Hispanic ethnicity compared to White Americans. Those living in high poverty and low resourced areas (e.g., health center patients) lag significantly behind the national average. There is a gap in evidence concerning colorectal cancer screening for community and societal levels factors. Specifically organizational level characteristics associated with screening uptake in health centers have not been well studied. Methods: A secondary analysis of the Uniform Data System, a standardized reporting system for federally funded health centers, was conducted. The following data were included for final analysis: health centers located in a US state and/or District of Columbia that received full (open full item for complete abstract)

Doctor of Philosophy, University of Akron, 2024, Psychology-Industrial/Organizational

Feedback orientation is a person's general receptivity to feedback; although early theorizing about the construct described how it should change over time in the context of ongoing performance management experiences, the extant literature has largely neglected to study whether changes to feedback orientation do in fact occur. This study involves an experiment that was designed to improve participant feedback orientation, and evaluated how that change might be influenced by feedback environment, leader-member exchange, and perceived organizational support. A longitudinal study of feedback orientation was conducted to assess the construct weekly for four weeks, and discontinuous growth curve modeling was used to evaluate whether the experimental intervention induced an increase to feedback orientation that was greater than what would be expected from the normal weekly fluctuations of the construct. Results from an online study of working adults conducted on Prolific revealed that the intervention successfully produced an increase in participants' feedback orientation, relative to both pre-intervention fluctuations and to the impact of a control intervention. Furthermore, initial feedback orientation and leader-member exchange were found to moderate the size of the feedback orientation boost that was produced by the experimental intervention, such that the boost was larger for those with lower initial feedback orientations and for those with higher initial leader-member exchanges. Feedback environment, meanwhile, moderated feedback orientation dynamics such that participants who perceived higher levels of feedback environment maintained higher levels of feedback orientation post-intervention for two weeks after the intervention. These results offer clear insights into feedback orientation dynamics and how they are impacted by critical feedback events, feedback environments, and leader-member exchange.

Master of Science (M.S.), University of Dayton, 2024, Aerospace Engineering

Recent advancements in battery technology have led to an increase in the development of electric Vertical Takeoff and Landing (eVTOL) vehicles, typically using electrically-powered propellers to generate both lift and thrust. These vehicles typically operate in low-altitude, and limited-space conditions in urban environments. Unsteady flows from building wakes or atmospheric boundary layer effects raise concern to the stability of eVTOL-capable aircraft under normal operating conditions and during transition from vertical to forward flight and vice-versa in population dense areas. Although all types of unsteady flows have been studied for decades, little has been published on the influence of unsteady flow on a propeller-wing system. Understanding of this system is crucial to ensuring the safety of not only the passengers of these VTOL aircraft, but also the safety of the public. Investigation into powered wing response to streamwise gust encounters was conducted through various propeller locations, angles of attack, reduced frequencies, and thrust levels. All experiments were run at the University of Dayton Low Speed Wind Tunnel (UD-LSWT) in its open-jet configuration. The shuttering system downstream of the test section consists of a set of rotating louvers that change angle to effectively change the blockage ratio of the wind tunnel. Different louver angles and actuation frequencies provide different velocities and reduced frequencies. Particle Image Velocimetry (PIV) was conducted on the freestream flow during actuation of the louvers to spatially characterize the angle of attack variation throughout the test section. The results from PIV were used to determine the optimal testing location and wing size for the test article. The wing was designed to be modular, accepting a number of different propeller Distribution Statement A: Approved for Public Release; Distribution is Unlimited. PA# AFRL-2024-2083 4 locations. Four total configurations were considered – (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Psychology

Current longitudinal research in developmental science has shown that during college, students generally experience a progressive decline in psychosocial adjustment. First-generation college students (FGCS) encounter unique adjustment difficulties that impact their academic success. Yet, no current research tracks these students' progress based on key factors (i.e., socioemotional competence, psychosocial adjustment, and perceived academic control) that are critical to academic success. To fill this research gap, this short-term longitudinal study is the first to examine how these variables affect academic outcomes among emerging adult college freshmen at two timepoints, as they take one of their first college courses during their first semester of college. Findings show that the associations between most of these study variables are statistically significant and indicative of unique differences between FGCS and continuing-generation college students (CGCS) as academic learners. Perceived academic control was the only key predictor of academic performance. Despite reporting higher levels of psychological distress than CGCS across both timepoints, FGCS only showed significant differences in depression levels by the end of their first semester of college. Academic enrichment program participation did not impact academic performance. These study findings are used to expand FGCS research and offer practitioners relevant insights to support these students' positive adjustment to college upon entry.

Doctor of Philosophy, Miami University, 2024, Psychology

Introduction: This study aims to better understand the psychosocial mechanisms by which individuals who report subjective concerns about their memory (SCI) are at a higher risk for objective cognitive impairments (OCI) over time. It also aims to identify modifiable risk factors that may disrupt this progression. Aim 1 tests if symptoms of affective disorders mediate the relationship between SCI and OCI over time. Aim 2 tests if self-perceptions of aging moderate the relationship between SCI and symptoms of affective disorders over time. Aim 3 tests if self-perceptions of aging moderate the indirect effect of symptoms of affective disorders on the relationship between SCI and OCI over time. Method: Data was sourced from the Health and Retirement Study, a national longitudinal dataset, across 8 years. 4,002 adults, 65 and older, were included in the sample. The moderation, mediation, and moderated mediation analyses were conducted using a path model in Mplus (Version 8 Plus). Relevant covariates including demographic and health variables were controlled for. Results: Analyses confirmed that symptoms of affective disorders partially mediated the relationship between SCI and OCI. For individuals with negative self-perceptions of aging, the relationship between SCI and symptoms of affective disorders strengthened over time, while for individuals with positive self-perceptions of aging, the relationship ceased to exist. Finally, positive self-perceptions of aging weakened, while negative self-perceptions of aging strengthened the indirect effect of symptoms of affective disorders on the relationship between SCI and OCI. Conclusion: Results of the current study clarify the psychosocial mechanisms involved in the progression from SCI to OCI, and add support to literature identifying positive beliefs about aging and mental health as protective factors against cognitive impairment among older adults. This study implicates the need for more interdisciplinary research studying (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 2024, Epidemiology and Biostatistics

There has been a lack of causal mediation analysis methods developed for complex longitudinal data. Most existing work focuses on extensions of parametric models that have been well developed for causal mediation analysis for cross-sectional data. To better handle complex, including irregular, longitudinal data, our approach takes advantage of the flexibility of penalized splines and performs causal mediation analysis under the structural equation model framework. The incorporation of penalized splines allows us to deal with repeated measures of the mediator and the outcome that are not all recorded at the same time points. The penalization avoids otherwise difficult choices in selecting knots and prevents the splines from overfitting so that the prediction for future time points will be more reasonable. We also provide the formula for identifying the natural direct and indirect effects based on our semiparametric models, whose inference is carried out by delta method and Monte Carlo approximation. This frequentist approach can be straightforward and efficient when implemented under the linear mixed model (LMM) framework, but it sometimes faces convergence problems as the random effects components introduce complications when using the commonly seen optimization algorithms in most of the statistical software. Although Bayesian modeling under LMM is less likely to face the convergence problem with the help of Markov chain Monte Carlo (MCMC) sampling, it can be computationally expensive compared to the frequentist approach due to the nature of the MCMC algorithm. As an alternative Bayesian approach, Gaussian process regression (GPR) also has the flexibility to fit various data patterns and will be more efficient than Bayesian modeling using MCMC, as the posterior distribution in GPR is a known form from which the posterior samples can be directly drawn. We thus attempt to extend the standard GPR approach to allow multiple covariates of both continuous and categorical (open full item for complete abstract)

PhD, University of Cincinnati, 2023, Business: Business Administration

The three chapters presented in this work focus on improving statistical inference for time series models and clinical trial data. In the first chapter, a Bayesian approach is proposed for testing serial error independence in time series models, addressing the Lindley paradox and outperforming frequentist tests in AR1 models. The second chapter provides simulation evidence comparing conventional Mixed Models for Repeated Measures (MMRM) with Bayesian hierarchical models that explicitly specify dynamic correlation, showing improved predictive accuracy and reliable treatment effect estimation in small samples. The third chapter applies the best-performing model specifications from the previous chapter to clinical trial data, highlighting the importance of socioeconomic factors in treatment outcomes for major depressive disorder. The first chapter addresses the assumption of serial independence of model approximation errors in time series modeling, which is crucial for reliable inference. While frequentist methods like the Ljung-Box and Breusch-Godfrey tests have been widely used for hypothesis testing, the increasing popularity of Bayesian Inference demands comparable Bayesian testing procedures. However, Bayesian hypothesis testing has faced challenges in resolving the Lindley paradox, resulting in contradictory inference when compared to frequentist tests. To address this issue, we propose a Bayesian procedure for testing serial error independence in time series models, which enables paradox-free inference. The results demonstrate that the proposed Bayesian test outperforms frequentist tests in Autoregressive Order 1 (AR1) models in small to moderate-sized samples and performs comparably well in higher order autoregressive models. Clinical trials are often costly and have limited observations, making it crucial to achieve precise inference about treatment effects in small samples. The Mixed Models for Repeated Measures (MMRM) have been the standard to (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2023, Sociology

This dissertation consists of three studies of worker power and economic inequality. The studies extend inequality research by assessing the impacts of worker bargaining power on two less commonly examined outcomes: household wealth and employer-provided fringe benefits. I conceptualize and measure several types of worker power, spanning marketplace and associational forms, measured at the individual, local-regional, and institutional scales. The studies broaden theories of how worker bargaining power influences the wage and income distributions to the case of wealth and fringe benefits. In the first chapter, I examine the relationship between labor union coverage and household wealth accumulation and inequality. Informed by life course theories of cumulative advantage, I develop novel measures of cumulative exposure to unionization across the career. Using data from the National Longitudinal Survey of Youth-1979 Cohort (NLSY-79) and fixed-effects regression, I find that cumulative career union coverage supports wealth accumulation. This positive association is driven by the influence of union coverage on the accumulation of savings and durable assets. Unconditional quantile regression models reveal that career union coverage is more strongly associated with increases in wealth for low- and middle- than high-wealth individuals. Results suggest worker power is associated with a more equal distribution of wealth and that deunionization contributed to rising wealth inequality among this cohort. The second chapter advances research on the determinants of job quality by considering the effects of worker power on fringe benefit offers. Using uniquely comprehensive data on benefits in the NLSY-79, I leverage changes in union coverage status due to involuntary job displacements (layoffs and business closures) to estimate the effects of unionization on the number of fringe benefits made available to workers by their employers. I find that transitioning to a union job i (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2023, Educational Studies

The field of online language education is experiencing rapid growth, emphasizing the need to understand factors that influence students' communication behaviors in online learning environments. This research study examines the relationships between need satisfaction, willingness to communicate (WTC), quantity of communication(i.e., frequency of communication), and quality of communication (i.e., language performance) in asynchronous and synchronous learning modes. Using Experience Sampling Methodology, data was collected from high school students enrolled in an online language course. Weekly surveys were used to capture participants' situational need satisfaction, WTC, and quantity of communication. Quality of communication was assessed through weekly writing assignments and synchronous speaking performance. Findings from multiple group path analyses revealed that students' need satisfaction for competence, and relatedness were significantly related to their WTC in both asynchronous and synchronous learning modes. The study identified differences in relationship patterns in asynchronous and synchronous learning modes, highlighting the influence of specific contextual factors on communication behaviors. Additionally, the study employed cross-lagged analyses to explore the temporal effects between need satisfaction and WTC, and between WTC and communication behaviors. The findings revealed the associations between students' prior learning experiences, students' perceptions, and subsequent engagements over time. The study explored the specificity of relationships within and across learning modes and content units, providing insights into contextual factors that are associated with students' communication behaviors. By examining the differences in relationships across various modes and considering temporal dynamics within specific contexts, this research enhances our understanding of factors contributing to supportive online environments and positive communication (open full item for complete abstract)