The Influence of Pre-Migration Factors and Post-Migration Climate of the Receiving Community on the Psychological Distress of Latino Immigrants

Over forty million foreign-born residents currently live in the United States. Latinos make up the largest population of immigrants living in the U.S. Previous research suggests that Latino immigrants often experience pre-migration stressors, such as traumatic experiences, political upheaval, and unplanned migration. These stressors may have a negative impact on immigrants’ post-migration mental health. Research also suggests that the post-migration climate of the receiving community may inform the connection between pre-migration experiences and post-migration mental health. The current study examined the relationship between Latino immigrants’ reasons for migration, migration planning, and pre-migration experience of political and/or interpersonal violence, and post-migration symptoms of psychological distress. In addition to examining the effect of these pre-migration factors, the current study also examined the community “climate” experienced by Latino immigrants post-migration by assessing the influence of three post-migration factors: 1) community support and engagement, 2) discrimination, and 3) employment. The study was a secondary analysis of data collected for the National Latino and Asian American Study, which focused on the mental health and service utilization of Latinos and Asian Americans. Participants included 1,629 Latino immigrants from across the United States. Results indicated that pre-migration experience of political and/or interpersonal trauma, post-migration experience of discrimination, and female sex were positively associated with psychological distress. Post-migration employment was negatively associated with psychological distress. In addition, discrimination modified the association between unplanned migration and psychological distress; the relationship between unplanned migration and psychological distress decreased for participants who reported more discrimination. Furthermore, employment modified the association between political and/or interpersonal trauma and psychological distress; the connection between trauma and psychological distress increased among those who reported having less employment. Recommendations for further research were presented. Policy and clinical practice implications were discussed, particularly given the current climate of high anti-immigrant sentiment and hostility in the U.S.

Investigation into the Influence of Build Parameters on Failure of 3D Printed Parts

Additive manufacturing, including fused deposition modeling (FDM), is transforming the built world and engineering education. Deep understanding of parts created through FDM technology has lagged behind its adoption in home, work, and academic environments. Properties of parts created from bulk materials through traditional manufacturing are understood well enough to accurately predict their behavior through analytical models. Unfortunately, Additive Manufacturing (AM) process parameters create anisotropy on a scale that fundamentally affects the part properties. Understanding AM process parameters (implemented by program algorithms called slicers) is necessary to predict part behavior. Investigating algorithms controlling print parameters (slicers) revealed stark differences between the generation of part layers. In this work, tensile testing experiments, including a full factorial design, determined that three key factors, width, thickness, infill density, and their interactions, significantly affect the tensile properties of 3D printed test samples.

Studying the Causes and Consequences of Internal Labor Migration Using Survey and Administrative Data Sources

This dissertation comprises three chapters. The first chapter motivates the use of a novel data set combining survey and administrative sources for the study of internal labor migration. By following a sample of individuals from the American Community Survey (ACS) across their employment outcomes over time according to the Longitudinal Employer-Household Dynamics (LEHD) database, I construct a measure of geographic labor mobility that allows me to exploit information about individuals prior to their move. This enables me to explore aspects of the migration decision, such as homeownership and employment status, in ways that have not previously been possible. In the second chapter, I use this data set to test the theory that falling home prices affect a worker’s propensity to take a job in a different metropolitan area from where he is currently located. Employing a within-CBSA and time estimation that compares homeowners to renters in their propensities to relocate for jobs, I find that homeowners who have experienced declines in the nominal value of their homes are approximately 12% less likely than average to take a new job in a location outside of the metropolitan area where they currently reside. This evidence is consistent with the hypothesis that housing lock-in has contributed to the decline in labor mobility of homeowners during the recent housing bust. The third chapter focuses on a sample of unemployed workers in the same data set, in order to compare the unemployment durations of those who find subsequent employment by relocating to a new metropolitan area, versus those who find employment in their original location. Using an instrumental variables strategy to address the endogeneity of the migration decision, I find that out-migrating for a new job significantly reduces the time to re-employment. These results stand in contrast to OLS estimates, which suggest that those who move have longer unemployment durations. This implies that those who migrate for jobs in the data may be particularly disadvantaged in their ability to find employment, and thus have strong short-term incentives to relocate.