DEPRESSION SCREENING IN OUTPATIENT PHYSICAL THERAPY

N/ADoctor of Nursing Practic

Archipelagos of History: Indigenous Legal Mobilization in Colonial Chiloé, 1684-1730

Between 1684 and 1730, Indigenous communities in colonial Chiloé began to increasingly seek out the Spanish legal system in order to denounce Spanish abuses, advocate for their communal interests, and ultimately contest the norms and terms of the local colonial system. Far from subjecting themselves to a foreign system imposed on them, Indigenous communities creatively took advantage of the possibilities offered to them through litigation in order to build stronger communal positions and leverage their own strengths, in the process developing a unique politics of engagement with the Spanish colonial system. Chiloé—the Spanish empire’s southernmost possession in the Americas—was a remote and isolated outpost of colonial rule where Spanish officials consistently took advantage of the region’s borderlands character in order to subvert proper legal process. In spite of this, Chiloé’s Indigenous communities leveraged a series of adaptations to their local environmental conditions, in addition to place-based forms of knowledge, as a way of highlighting Spanish dependence on Indigenous labor and know-how, By contesting arbitrary Spanish colonial administration, Chiloé’s Indigenous communities asserted themselves as active participants in the co-constitution of a negotiated local colonial order.Doctor of Philosoph

Statistical Challenges in Sequencing Data: Addressing Uncertainty in Analysis

The advancement of high-throughput sequencing technologies has revolutionized biological research. However, these technologies also introduce new statistical uncertainties. In this work, we present novel statistical methods that account for statistical uncertainties and best practice to mitigate bias in analyzing sequencing data. In project 1, we focus on detecting allelic imbalance on the isoform level, caused by non-coding variants in the regulatory regions. This analysis requires accounting for inferential uncertainty, caused by multi-mapping of RNA-sequencing reads. Our proposed method, SEESAW, uses Salmon and Swish to offer analysis at various levels of resolution, while accounting for inferential uncertainty. In project 2, we address the challenge of detecting cell composition changes using paired single-cell RNA-sequencing (scRNA-seq) data in cancer research. We proposed a novel approach scSTMseq, a topic modeling-based framework designed to infer cell clusters and estimate clustering uncertainty while integrating cell-level covariates, such as time. We coupled this framework with Multivariate analysis of variance for repeated measures to infer cell composition changes. In project 3, we explored the CRISPR inference/activation screens to study the regulatory roles of non-coding elements. Unlike standard scRNA-seq, scaling-based normalization introduces selection bias due to correlations between perturbation states and the sequencing depth, which complicates the case-control classification. We demonstrated this bias and proposed Poisson regression as a better alternative for normalization in the CRISPR-i/a studies.Doctor of Philosoph

Simulation-based Testing of the Traffic Rules Requirements for Autonomous Vehicles at Intersections

To successfully integrate autonomous vehicles as a mode of transportation, we must test these systems against their end-to-end requirements. When AVs and humans (pedestrians, bicyclists, human-driven vehicles) share the road, they must follow the same traffic rules. Using the common traffic rules (written for human drivers) as an engineering requirement poses a challenge due to the ambiguity of the natural language. On the other hand, an AV is fundamentally different from a human, and a simple road test is not sufficient to assess an AV's compliance and skills. This calls for automated, systematic and scalable testing techniques. The focus of this dissertation is on simulation-based testing of the traffic-rules requirements. This dissertation develops techniques for systematic exploration of the test-case space of autonomous vehicles based on two crucial concepts: complexity and coverage. Here, these concepts are formalized with respect to the traffic rules requirements. The efficiency of finding bugs is improved by incrementally increasing the complexity of a test-case, namely making it harder for an AV to pass a test-case. On the other hand, the diversity of a test-suite is improved by guiding the test-case generation towards increasing the coverage of a test-suite. The framework for formalization of the traffic rules is made more amenable to vetting by the authorities and regulators by narrowing the gap between human intuition and machine language. This is achieved by formalizing traffic rules in first-order logic (FOL) which allows modeling objects and predicates.Doctor of Philosoph

THE ROLE OF SOCIAL SAFETY NETS IN SHAPING DEVELOPMENT OUTCOMES: EFFECTS ON PERSONALITY, GENDER NORMS AND EMPLOYMENT TRAJECTORIES

I examine the impact of social safety nets on personality traits, labor market outcomes, and gender norms and attitudes. For the first two outcomes, I draw on data from a nine-year longitudinal evaluation of Malawi’s Social Cash Transfer Program (SCTP), implemented by the Government of Malawi. In the first chapter, I investigate how cash transfers influence personality traits among young adults in Malawi, specifically those aged 19 to 28. I pay particular attention to whether these effects differ by receiving three additional years of treatment and gender. Given the variation in age within the sample, I also explore whether the program’s impact varies across different age cohorts. The second chapter is a systematic literature review to assess the impact of social safety nets on gender norms and attitudes. I hypothesize that social safety nets that are gender aware or those that have plus components are likely to have favorable impacts. Hence, I examine whether impacts vary by the type of social safety net, whether they are gender aware or not, integration of plus components, or the domain (type) of gender-related attitudes and norms measured. Finally, the third chapter examines the impact of cash transfers on time use among young adults in Malawi. I specifically examine whether receiving three additionally years of unearned income helps young adults’ transition from low productive jobs to high productive jobs in a context of a fragile macroeconomic situation and whether this impact varies by gender. Taken together, the three chapters of this dissertation contribute to a more comprehensive understanding of the breadth and depth of the effects that cash transfers can have across multiple dimensions of individuals’ lives.Doctor of Philosoph

Implementation of Interventions to Improve Breast, Cervical, and Prostate Cancer Screening Among Transgender Adults in Primary Care Settings: A Systematic Review Protocol

Transgender people face harassment in clinics and report feeling uncomfortable seeking care, leading to avoidance of needed medical care. Breast, cervical, and prostate cancer screening may induce gender dysphoria. Transgender people are less likely to be up to date on breast, cervical, and prostate cancer screening compared to cisgender people. This scoping review aims to answer the question: what screening interventions have been implemented to improve breast, cervical, and prostate cancer screening among transgender adults in primary care settings? PubMed, Embase and PsychINFO will be searched for eligible studies. ClinicalTrials.gov will be searched for eligible unpublished studies. Two reviewers will independently screen all records and complete full text review. Intervention categories and themes will be synthesized and presented in a table

USE OF A PRIORI AND A POSTERIORI METHODOLOGIES TO INFORM THE DEVELOPMENT OF FEASIBLE EATING STRATEGIES THAT PROMOTE GLYCEMIC MANAGEMENT IN YOUNG PEOPLE WITH TYPE 1 DIABETES

There are no evidence-based eating strategies for youth with type 1 diabetes, despite established understanding that nutrition is fundamental to glycemic management and complication prevention, and self-management is worse during adolescence compared to all other life stages. Critically, existing eating strategies do not provide guidance related to timing, frequency, or macronutrient composition of eating occasions to optimize short-term or longer-term glycemic measures. The objective of this dissertation was to inform the development of eating strategies that consider these factors, with the ultimate goal of prospectively evaluating their effectiveness for improving of glycemic management among youth with type 1 diabetes. In Aim 1, we developed a daily eating behavior pattern focused on number and timing of eating occasions and distribution of macronutrients throughout the day, and conducted a pilot trial to explore feasibility and diabetes management benefits among 52 adolescents with type 1 diabetes. We observed excellent retention (85%), attendance (15.8[SD=0.6]/16 sessions), food log adherence (4.0[SD=2.6]/≥3 logs per week), ≥90% participation in evaluation procedures, and no adverse effects. Endline adherence to most (≥3) goals was ≥90% according to unannounced dietary recalls. Hemoglobin A1c decreased on average by 0.3(SD=0.9)% (p=0.03). Youth and parents (>85%) endorsed acceptability. Findings supported progression to a trial to evaluate effectiveness. Aim 2 was a secondary analysis using 175 days of overlapping eating, insulin, physical activity, continuous glucose monitoring, and clinical data from 49 participants in the Aim 1 trial. We trained a generalized additive model that incorporated predictors over a 6-hour window divided into 1-hour intervals (-2 to -1 hours, -1 to 0 hours, 0 to +1 hours, +1 to +2 hours, +2 to +3 hours, +3 to +4 hours), to predict near-term time in range (0 to +4 hours). We demonstrated a proof-of-concept for the intended application of the model: a personalized, adaptive eating decision support tool that enables users to select from meals/snack options and adjust timing to optimize near-term glycemic management amidst food or timing constraints. Our studies lay groundwork for the development of behaviorally interpretable, specific and feasible eating strategies that youth with type 1 diabetes can use to support day-to-day management.Doctor of Philosoph

HARNESSING TOPIC MODELING AND KNOWLEDGE GRAPHS FOR ENHANCED DISCOVERY IN HEALTH INTEROPERABILITY RESEARCH THROUGH RETRIEVAL-AUGMENTED GENERATION

Technologies today rarely function in isolation. Disparate data repositories and fragmented information systems necessitate seamless interoperability to support both clinical and research applications. This dissertation develops a computational framework for systematically evaluating interoperability standards that facilitate data exchange between research technologies and health systems.Rather than assessing interoperability through a single standard or methodology, this research introduces a structured knowledge model that categorizes interoperability concepts and cross-references them with relevant components, technologies, and terminologies. To achieve this, the study integrates artificial intelligence (AI) techniques, including natural language processing, machine learning, and graph analytics to extract, classify, and visualize interoperability relationships from health informatics literature.The framework applies unsupervised and semi-supervised learning methods, using AI techniques such as Latent Dirichlet Allocation (LDA), Non-Negative Matrix Factorization (NMF), and BERTopic to discover latent topic structures across thousands of biomedical publications. These topic models serve as the foundation for a domain-specific knowledge graph, allowing deeper semantic understanding and organization of interoperability research.To enhance the accuracy of concept extraction and entity recognition, the study creates fine-tunes a biomedical transformer model, Health Interoperability Research Bidirectional Encoder Representation from Transformers (HIResBERT), adapted for health interoperability. This model supports contextualized sentence embeddings and Named Entity Recognition tailored to interoperability use cases.The resulting AI-powered knowledge graph is operationalized through Graph-based Retrieval-Augmented Generation (GraphRAG) application, which facilitates semantic question answering and contextual discovery. Researchers can navigate complex interoperability relationships, uncover gaps, and retrieve literature mapped to relevant standards.Additionally, this research offers a structured mechanism for analyzing interoperability trends and delivers insights. By making complex standards and relationships more navigable, the framework enables researchers to effectively learn about and engage with interoperability concepts and technologies. By leveraging AI to automate the extraction, synthesis, and navigation of domain knowledge, this dissertation presents a scalable and reusable framework for advancing interoperability, clinical decision support, and health data integration within clinical and translational science.Ultimately, this work demonstrates how AI can be harnessed to advance literature discovery, knowledge modeling, and conceptual clarity across key areas of health informatics, laying the foundation for more transparent, data-driven, and integrative approaches to health research.Doctor of Philosoph

LOVE THY NEIGHBOR: POST-CIVIL WAR RECONCILIATION AND SOCIAL INEQUALITY

This thesis investigates the role of social inequality in the recurrence of civil war, arguing that prevailing peacebuilding strategies—such as power-sharing agreements and peacekeeping missions—are insufficient without a genuine commitment to social equity. Drawing on theories of relative deprivation and (re)humanization, I contend that unresolved grievances rooted in perceptions of civil and public inequality among social groups significantly undermine the durability of peace. Using a multilevel logistic regression analysis of post-conflict societies from 1992 to 2023, I find that greater equality in civil liberties and access to public services significantly reduces the likelihood of renewed conflict, even when controlling for established peacebuilding mechanisms. These findings are further illustrated through a comparative case study of the First and Second Liberian Civil Wars, which underscores the importance of inclusive governance and community-level reconciliation. This research contributes to the peacebuilding literature by highlighting the critical need to address social grievances in post-conflict societies to prevent cyclical violence and promote sustainable peace.Master of Art

The Association Between Perceived Social Support and Perceived Stress in Racial and Ethnic Minority Patients Following Anterior Cruciate Ligament Reconstruction

Background: Outcomes after anterior cruciate ligament reconstruction (ACLR) may be influenced by psychological stressors and social support. Racial and ethnic minority patients may face unique life stressors that affect their rehabilitation. The purpose of this study was to explore the relationship between stress and social support in racial and ethnic minority patients after ACLR. We hypothesized that high perceived stress would be associated with low social support. Methods: 20 racial and/or ethnic minority patients post-ACLR completed assessments of perceived stress and social support. Pearson product moment correlations were used to evaluate the relationship between these variables. Results: No significant associations were found between perceived stress and social support in this population. Conclusion: Persistent mental health stigma observed in racial and ethnic minority populations may have contributed to these results. Healthcare providers should consider culturally tailored interventions to foster supportive environments and improve the recovery process for patients after ACLR.Master of Art