The current dissertation combines the results of three recently published papers focused on impulsive personality traits, alcohol and cannabis co-use, and alcohol misuse. The first study used alcohol administration to test whether different impulsivity facets conferred risk for heightened alcohol craving through subjective alcohol response patterns. The second study built on this study by incorporating alcohol and cannabis co-use into the acquired preparedness model, using longitudinal data. This study tested whether generalized impulsivity and sensation seeking during late adolescence predisposed individuals to co-use alcohol and cannabis, and whether co-use was indirectly associated with alcohol problems ten years later through positive expectancies and heavy drinking. The third study tested whether impulsive traits moderated the day-level effect of alcohol and cannabis co-use (vs. alcohol-only) on within-person deviations in drinking quantity on drinking days. Through the combination of these three studies, this dissertation seeks to further advance the literature on multiplicative ways in which personality enacts risk for heavy drinking, alcohol and cannabis co-use, and alcohol problems.

Do individuals flexibly and adaptively calibrate their motivation, thoughts, feelings, and behaviors in response to changing ecological opportunities and threats? Using a longitudinal six-wave survey data set collected during the COVID-19 pandemic, the study addresses three research questions: are some psychological features or characteristics more or less likely to be calibrated in response to environmental change, are certain types of people more sensitive to these ecological changes, and do individuals become more sensitized or habituated to these changes over time? The results demonstrate that individuals can flexibly adjust their psychology directly relevant to managing COVID-19 infection: people were more strongly motivated to avoid disease and perceived that they were more vulnerable to COVID-19 infection during periods when the threat of COVID-19 infection was high. Political liberals were particularly sensitive to ecological infection changes in adjusting their disease avoidance motivation. Importantly, the study also found a significant quadratic effect of COVID-19 cases on disease avoidance motivation, perceived COVID vulnerability, and preventative behaviors. This indicates that the effect of COVID-19 cases was especially pronounced during the early phase of the pandemic when new cases were relatively low, but diminished as time passed and new cases increased. These findings highlight the adaptive nature of human behavior in response to changing environmental circumstances and underscore the importance of considering both individual and contextual factors in understanding psychological flexibility.

The last two decades have seen growing awareness of and emphasis on the replication of empirical findings. While this is a large literature, very little of it has focused on or considered the interaction of replication and psychometrics. This is unfortunate given that sound measurement is crucial when considering the complex constructs studied in psychological research. If the psychometric properties of a scale fail to replicate, then inferences made using scores from that scale are questionable at best. In this dissertation, I begin to address replication issues in factor analysis – a widely used psychometric method in psychology. After noticing inconsistencies across results for studies that factor analyzed the same scale, I sought to gain a better understanding of what replication means in factor analysis as well as address issues that affect the replicability of factor analytic models. With this work, I take steps toward integrating factor analysis into the broader replication discussion. Ultimately, the goal of this dissertation was to highlight the importance of psychometric replication and bring attention to its role in fostering a more replicable scientific literature.

This project studied a four-variable single mediator model, a single mediator model: X (independent variable) to M (mediator) to Y (dependent variable), and a confounder (U) that influences M and Y. Confounding represents a threat to the causal interpretation in mediation analysis. For instance, if X represents random assignment to control and treatment conditions, the effect of X on M and the effect of X on Y have a causal interpretation under certain reasonable assumptions. However, the randomization of X does not allow for a causal interpretation of the M to Y effect unless certain confounding assumptions are satisfied. The aim of this project was to develop a significance test and an effect size comparison for two sensitivity to confounding analyses methods: Left Out Variables Error (L.O.V.E.) and the correlated residuals method. Further, the project assessed the accuracy of the methods for identifying confounding bias by simulating data with and without confounding bias.

To reduce the environmental burden of transport, previous studies have resorted on solutions that accentuate towards techno-economical pathways. However, there is growing evidence that transport behaviors, lifestyle choices, and the role of individuals' attitudes/perceptions are considered influential factors in shaping households’ engagement with sustainable technologies in the face of environmental crises. The objective of this dissertation is to develop multidimensional econometric model systems to explore complex relationships that can help us understand travel behaviors' implications for transport and household energy use. To this end, the second chapter of this dissertation utilizes the latent segmentation approach to quantify and unravel the relationship between attitudes and behaviors while recognizing the presence of unobserved heterogeneity in the population. It was found that two-thirds of the population fall in the causal structure where behavioral experiences are shaping attitudes, while for one-third attitudes are shaping behaviors. The findings have implications on the energy-behavior modeling paradigm and forecasting household energy use. Building on chapter two, the third chapter develops an integrated modeling framework to explore the factors that influence the adoption of on-demand mobility services and electric vehicle ownership while placing special emphasis on attitudes/perceptions. Results indicated that attitudes and values significantly affect the use of on-demand transportation services and electric vehicle ownership, suggesting that information campaigns and free trials/demonstrations would help advance towards the sustainable transportation future and decarbonize the transport sector. The integrated modeling framework is enhanced, in chapter four, to explore the interrelationship between transport and residential energy consumption. The findings indicated the existence of small but significant net complimentary relationships between transport and residential energy consumption. Additionally, the modeling framework enabled the comparison of energy consumption patterns across market segments. The resulting integrated transport and residential energy consumption model system is utilized, in chapter fifth, to shed light on the overall household energy footprint implications of shifting vehicle/fuel type choices. Results indicated that electric vehicles are driven as much as gasoline vehicles are. Interestingly, while an increase in residential energy consumption was observed with the wide-scale adoption of electric vehicles, the total household energy use decreased, indicating benefits associated with transportation electrification.

Social-emotional competence (SEC), or effectiveness of social interaction, plays a central role in children’s health and well-being. The three goals of the current study were to describe the development of SEC during a preschool year; identify an appropriate factor structure for observed teacher-child interactions; and predict SEC growth from children’s characteristics (emotional competence, language risk, gender, and race/ethnicity), teacher-child relationship quality, and classroom characteristics (relational climate, observed teacher-child interaction quality, and curriculum). Children’s social competence, anger/aggression, effortful control, and emotion knowledge (N =822) was assessed at three time points during a preschool year via teachers’ reports and behavioral assessments. In the fall, teachers reported the quality of their relationships with children and teacher-child interactions were observed in classrooms. Aim 1 results indicated that children exhibited linear increases in effortful control and social competence and stability in anger/aggression, although social competence was the only construct where linear change varied among children. Due to a lack of longitudinal measurement invariance, growth in latent emotion knowledge could not be evaluated. Several gender and racial/ethnic differences were identified in SEC intercepts, but not the social competence slope. Language risk and impulsivity were consistent predictors of SEC intercepts. Aim 2 results indicated that teacher-child interaction quality was primarily unidimensional. Finally, results from aim 3 indicated that children’s emotional competence at the beginning of the year and classroom relational climate were predictive of growth in social competence. End-of-year social competence levels were associated with supportive teacher-child relationship quality (particularly among girls), high emotional competence, low language risk, and supportive classroom relational climate; girls had higher social competence than boys. Although not directly associated with social competence, observed teacher-child interaction quality was conditionally predictive of the social competence in the context of supportive teacher-child relationships. Further, when observed teacher-child interaction quality was average or high, children with low emotional competence exhibited greater growth in social competence than children with high emotional competence. The results inform our understanding of SEC development, the nature of teacher-child interactions in preschool classrooms serving high-risk populations, and potential school-based mechanisms for promoting social competence.

This study aimed to advance understanding of the relation between social media and adolescent alcohol use while accounting for offline peer alcohol use, exploring offline peer alcohol use separately as a covariate and as a moderator, with an additional exploratory analysis of the relation between social media and alcohol use without offline peer alcohol use in the model. A total of 868 students (55% female) in grade 7 (n = 468) and grade 8 (n = 400) at wave 1, self-reported on alcohol use, binge drinking, and social media use as well as nominated friends from their school and grade. Data from nominated peers who also completed the questionnaires were used for peer-report of alcohol use. Data were collected annually from students at grades 8, 9, 10, and 11 were used in analyses. Final structural models consisted of a cross-lagged panel design with saved factor scores for social media and peer alcohol use predicting a categorical alcohol use variable or a binary binge drinking variable. With offline peer alcohol use as a covariate in the model, social media did not prospectively relate to subsequent grade alcohol use or binge drinking. However, without offline peer alcohol use, the path from social media use to subsequent grade alcohol use was significant but not the path to binge drinking. Offline peer alcohol use did not significantly moderate the relation between social media and subsequent grade alcohol use or binge drinking.

Familism values have been shown to have a multitude of benefits for Mexican American youth. Understanding different pathways of the adoption of familism values from adolescence and young adulthood, and predictors of these pathways, is critical. The current study assessed different classes of change in familism values across five waves from fifth grade to young adulthood, and fifth-grade predictors of these profiles, among a sample of 749 Mexican American youth. Univariate and growth mixture modeling was used to determine classes of familism change and found two classes—one class that showed small, insignificant declines across adolescence that accelerated into young adulthood and one class that showed significant declines across adolescence that stabilized and increased into young adulthood. The three-step procedure was then used to examine the following fifth-grade predictors of familism classes: family conflict, family cohesion, harsh parenting, parental acceptance, economic hardship, and perceived ethnic discrimination. Family conflict and perceived ethnic discrimination were significant predictors of familism class membership. Greater family conflict predicted a greater probability of being in the class of significant declines in familism across adolescence that stabilized and increased into young adulthood. Greater perceived ethnic discrimination predicted a greater probability of being in the class of small, insignificant decreases across adolescence that accelerated into young adulthood. Gender moderated the impact of family cohesion. For females, greater father-reported family cohesion predicted a greater probability of being in the class with significant declines during adolescence that stabilized and increased into young adulthood. For males, greater father-reported family cohesion predicted a greater probability of being in the class with slight, insignificant declines in adolescence that accelerated into young adulthood. Youth nativity moderated the impact of maternal acceptance. For youth born in the U.S., greater mother-reported acceptance predicted a greater probability of being in the class of slight, insignificant declines across adolescence that accelerated into young adulthood. For youth born in Mexico, greater mother-reported acceptance predicted a greater probability of being in the class of significant declines in familism across adolescence that stabilized and increased into young adulthood. Limitations and implications for prevention and future research are discussed.

The current study assessed whether the interrater reliability and predictive validity of fidelity ratings differed significantly across the modalities of audio and video recordings. As empirically supported programs are moving to scale, attention to fidelity, the extent to which a program is delivered as intended, is essential because high fidelity is needed for positive program effects. Consequently, an important issue for prevention science is the development of feasible and acceptable methods for assessing fidelity. Currently, fidelity monitoring is rarely practiced, as the typical way of measuring fidelity, which uses video of sessions, is expensive, time-consuming, and intrusive. Audio recording has multiple advantages over video recording: 1) it is less intrusive; 2) equipment is less expensive; 3) recording procedures are simpler; 4) files are smaller so it takes less time to upload data and storage is less expensive; 5) recordings contain less identifying information; and 6) both clients and providers may be more willing to have sensitive interactions recorded with audio only. For these reasons, the use of audio recording may facilitate the monitoring of fidelity and increase the acceptability of both the intervention and implementation models, which may serve to broaden the scope of the families reached and improve the quality of the services provided. The current study compared the reliability and validity of fidelity ratings across audio and video rating modalities using 77 feedback sessions drawn from a larger randomized controlled trial of the Family Check-Up (FCU). Coders rated fidelity and caregiver in-session engagement at the age 2 feedback session. The composite fidelity and caregiver engagement scores were tested using path analysis to examine whether they predicted parenting behavior at age 3. Twenty percent of the sessions were double coded to assess interrater reliability. The interrater reliability and predictive validity of fidelity scores and caregiver engagement did not significantly differ across rating modality. However, caution must be used in interpreting these results because the interrater reliabilities in both conditions were low. Possible explanations for the low reliability, limitations of the current study, and directions for future research are discussed.

The present study aimed to advance the current understanding of the relation between disability and subjective well-being by examining the extent to which different facets of subjective well-being (life satisfaction, positive affect, and negative affect) change before and after disability onset, and the extent to which age and type of disability moderate such changes. Multiphase growth-curve models to prospective longitudinal survey data from Waves 1-16 of the Household, Income and Labour Dynamics in Australia (HILDA) survey (N = 3,795; mean age = 50.22; age range: 16-99; 51% women). On average, life satisfaction remained relatively stable across the disability transition, whereas positive affect declined and negative affect increased the year surrounding disability onset; in the years thereafter, neither positive affect nor negative affect returned to pre-onset levels. Individuals who acquired disability in old age were more likely to report sustained declines in subjective well-being than were individuals who became disabled in midlife or young adulthood. Psychological disability was associated with the strongest declines across each indicator of subjective well-being at disability onset but also greater adaptation in the years thereafter. The findings provide further evidence against the set-point theory of hedonic adaptation and for a more moderate viewpoint that allows for processes of adaptation to vary based on the outcome examined, the type of stressor, and individual characteristics. The discussion focuses on possible mechanisms underlying the moderating roles of age and type of disability.