Theses and Dissertations

Prior research has established a relation between parenting behaviors and symptoms of child psychopathology, and this association may be influenced by both genetic and environmental factors. Gene-environment correlation, or the influence of a child’s genes on the environment they receive, represents one possible mechanism through which genes and environment combine to influence child outcomes. This study examined evocative gene-environment correlation in the relation between parenting and symptoms of child psychopathology in a sample of 676 twins (51.5% female, 58.5% Caucasian, 23.7% Hispanic/Latinx, primarily middle class, MAge=8.43, SD=.62) recruited from Arizona birth records. Using univariate ACE twin biometric models, genetic influences were found to moderately contribute to internalizing symptoms (A=.47, C=.25, E=.28), while externalizing (A=.86, E=.14) and ADHD (A=.84, E=.16) symptoms were found to be highly heritable. The genetic influences for positive (C=.54, E=.46) and negative (C=.44, E=.56) parenting were smaller and found to be nonsignificant. The correlations between parenting and types of psychopathology were examined and bivariate Cholesky decompositions were conducted for statistically significant correlations. Negative parenting was moderately positively correlated with externalizing and ADHD symptoms; the relation between externalizing symptoms and negative parenting was found to be due to shared genetics, whereas the relation between negative parenting and ADHD symptoms was due to the shared environment. The mixed results regarding the role of gene environment correlation in relations between parenting and child psychopathology indicate that further research on the mechanisms of this relation is needed.

Using a dataset of ASU students from the 2016-2017 cohort, we interact gender and parent education level to observe gaps in academic achievement. We see a statistically insignificant achievement gap for males across parent education level, but a statistically significant achievement gap for females across parent education level. We also observe dropout gaps among these interaction groups. We see the widest dropout gap being between males across parent education level, with the smallest dropout gap being between females across parent education level. So with males we see an insignificant achievement gap but the widest dropout gap across parent education level, and with females we see a significant achievement gap but the smallest dropout gap across parent education level. What is driving these gaps and causing more similarly performing students to drop out at wider rates? At the aggregate level, we see larger gaps in grade- associated dropout probability across parent education level for males which may be able to explain the larger difference in overall proportions of dropouts between males. However, when predicting dropout probability of the semester with the most first generation and non-first generation dropouts, we see that females have the largest differences across parent education level in grade-associated dropout probability. This suggests that our model may be best suited in using college achievement data to predict overall dropout probabilities, not next-semester dropout probabilities using current semester data. Our findings also suggest that first generation students’ dropout probability is more sensitive to the grades they receive than non-first generation students.