Matching Items (105)
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Description
Variability in subjective response to alcohol has been shown to predict drinking behavior as well as the development of alcohol use disorders. The current study examined the extent to which individual differences in alcohol pharmacokinetics impact subjective response and drinking behavior during a single session alcohol administration paradigm.

Variability in subjective response to alcohol has been shown to predict drinking behavior as well as the development of alcohol use disorders. The current study examined the extent to which individual differences in alcohol pharmacokinetics impact subjective response and drinking behavior during a single session alcohol administration paradigm. Participants (N = 98) completed measures of subjective response at two time points following alcohol consumption. Pharmacokinetic properties (rate of absorption and metabolism) were inferred using multiple BAC readings to calculate the area under the curve during the ascending limb for absorption and descending limb for metabolism. Following the completion of the subjective response measures, an ad-libitum taste rating task was implemented in which participants were permitted to consume additional alcoholic beverages. The amount consumed during the taste rating task served as the primary outcome variable. Results of the study indicated that participants who metabolized alcohol more quickly maintained a greater level of subjective stimulation as blood alcohol levels declined and reported greater reductions in subjective sedation. Although metabolism did not have a direct influence on within session alcohol consumption, a faster metabolism did relate to increased ad-libitum consumption indirectly through greater acute tolerance to sedative effects and greater maintenance of stimulant effects. Rate of absorption did not significantly predict subjective response or within session drinking. The results of the study add clarity to theories of subjective response to alcohol, and suggest that those at highest risk for alcohol problems experience a more rapid reduction in sedation following alcohol consumption while simultaneously experiencing heightened levels of stimulation. Variability in pharmacokinetics, namely how quickly one metabolizes alcohol, may be an identifiable biomarker of subjective response and may be used to infer risk for alcohol problems.
ContributorsBoyd, Stephen (Author) / Corbin, William R. (Thesis advisor) / Chassin, Laurie (Committee member) / MacKinnon, David (Committee member) / Olive, Michael Foster (Committee member) / Arizona State University (Publisher)
Created2014
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Description
The present study utilized longitudinal data from a high-risk community sample (n=254, 52.8% female, 47.2% children of alcoholics, 74% non-Hispanic Caucasian) to test questions concerning the effects of genetic risk, parental knowledge, and peer substance use on emerging adult substance use disorders (SUDs). Specifically, this study examined whether parental knowledge

The present study utilized longitudinal data from a high-risk community sample (n=254, 52.8% female, 47.2% children of alcoholics, 74% non-Hispanic Caucasian) to test questions concerning the effects of genetic risk, parental knowledge, and peer substance use on emerging adult substance use disorders (SUDs). Specifically, this study examined whether parental knowledge and peer substance use mediated the effects of parent alcohol use disorder (AUD) and genetic risk for behavioral undercontrol on SUD. The current study also examined whether genetic risk moderated effects of parental knowledge and peer substance use on risk for SUD. Finally, this study examined these questions over and above a genetic "control" which explained a large proportion of variance in the outcome, thereby providing a stricter test of environmental influences.

Analyses were performed in a path analysis framework. To test these research questions, the current study employed two polygenic risk scores. The first, a theory-based score, was formed using single-nucleotide polymorphisms (SNPs) from receptor systems implicated in the amplification of positive effects in the presence of new/exciting stimuli and/or pleasure derived from using substances. The second, an empirically-based score, was formed using a data-driven approach that explained a large amount of variance in SUDs. Together, these scores allowed the present study to test explanations for the relations among parent AUD, parental knowledge, peer substance use, and SUDs.

Results of the current study found that having parents with less knowledge or an AUD conferred greater risk for SUDs, but only for those at higher genetic risk for behavioral undercontrol. The current study replicated research findings suggesting that peer substance use mediated the effect of parental AUD on SUD. However, it adds to this literature by suggesting that some mechanism other than increased behavioral undercontrol explains relations among parental AUD, peer substance use, and emerging adult SUD. Taken together, these findings indicate that children of parents with AUDs comprise a particularly risky group, although likelihood of SUD within this group is not uniform. These findings also suggest that some of the most important environmental risk factors for SUDs exert effects that vary across level of genetic propensity.
ContributorsBountress, Kaitlin (Author) / Chassin, Laurie (Thesis advisor) / Crnic, Keith (Committee member) / Lemery-Chalfant, Kathryn (Committee member) / MacKinnon, David (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Anxiety and depression are among the most prevalent disorders in youth, with prevalence rates ranging from 15% to 25% for anxiety and 5% to 14% for depression. Anxiety and depressive disorders cause significant impairment, fail to spontaneously remit, and have been prospectively linked to problematic substance use and legal problems

Anxiety and depression are among the most prevalent disorders in youth, with prevalence rates ranging from 15% to 25% for anxiety and 5% to 14% for depression. Anxiety and depressive disorders cause significant impairment, fail to spontaneously remit, and have been prospectively linked to problematic substance use and legal problems in adulthood. These disorders often share a high-degree of comorbidity in both clinical and community samples, with anxiety disorders typically preceding the onset of depression. Given the nature and consequences of anxiety and depressive disorders, a plethora of treatment and preventative interventions have been developed and tested with data showing significant pre to post to follow-up reductions in anxiety and depressive symptoms. However, little is known about the mediators by which these interventions achieve their effects. To address this gap in the literature, the present thesis study combined meta-analytic methods and path analysis to evaluate the effects of youth anxiety and depression interventions on outcomes and four theory-driven mediators using data from 55 randomized controlled trials (N = 11,413). The mediators included: (1) information-processing biases, (2) coping strategies, (3) social competence, and (4) physiological hyperarousal. Meta-analytic results showed that treatment and preventative interventions reliably produced moderate effect sizes on outcomes and three of the four mediators (information-processing biases, coping strategies, social competence). Most importantly, findings from the path analysis showed that changes in information-processing biases and coping strategies consistently mediated changes in outcomes for anxiety and depression at both levels of intervention, whereas gains in social competence and reductions in physiological hyperarousal did not emerge as significant mediators. Knowledge of the mediators underlying intervention effects is important because they can refine testable models of treatment and prevention efforts and identify which anxiety and depression components need to be packaged or strengthened to maximize intervention effects. Allocating additional resources to significant mediators has the potential to reduce costs associated with adopting and implementing evidence-based interventions and improve dissemination and sustainability in real-world settings, thus setting the stage to be more readily integrated into clinical and non-clinical settings on a large scale.
ContributorsStoll, Ryan (Author) / Pina, Armando A (Thesis advisor) / MacKinnon, David (Committee member) / Knight, George (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Methods to test hypotheses of mediated effects in the pretest-posttest control group design are understudied in the behavioral sciences (MacKinnon, 2008). Because many studies aim to answer questions about mediating processes in the pretest-posttest control group design, there is a need to determine which model is most appropriate to

Methods to test hypotheses of mediated effects in the pretest-posttest control group design are understudied in the behavioral sciences (MacKinnon, 2008). Because many studies aim to answer questions about mediating processes in the pretest-posttest control group design, there is a need to determine which model is most appropriate to test hypotheses about mediating processes and what happens to estimates of the mediated effect when model assumptions are violated in this design. The goal of this project was to outline estimator characteristics of four longitudinal mediation models and the cross-sectional mediation model. Models were compared on type 1 error rates, statistical power, accuracy of confidence interval coverage, and bias of parameter estimates. Four traditional longitudinal models and the cross-sectional model were assessed. The four longitudinal models were analysis of covariance (ANCOVA) using pretest scores as a covariate, path analysis, difference scores, and residualized change scores. A Monte Carlo simulation study was conducted to evaluate the different models across a wide range of sample sizes and effect sizes. All models performed well in terms of type 1 error rates and the ANCOVA and path analysis models performed best in terms of bias and empirical power. The difference score, residualized change score, and cross-sectional models all performed well given certain conditions held about the pretest measures. These conditions and future directions are discussed.
ContributorsValente, Matthew John (Author) / MacKinnon, David (Thesis advisor) / West, Stephen (Committee member) / Aiken, Leona (Committee member) / Enders, Craig (Committee member) / Arizona State University (Publisher)
Created2015
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Description
The current study utilized data from two longitudinal samples to test mechanisms in the relation between a polygenic risk score indexing serotonin functioning and alcohol use in adolescence. Specifically, this study tested whether individuals with lower levels of serotonin functioning as indexed by a polygenic risk score were vulnerable to

The current study utilized data from two longitudinal samples to test mechanisms in the relation between a polygenic risk score indexing serotonin functioning and alcohol use in adolescence. Specifically, this study tested whether individuals with lower levels of serotonin functioning as indexed by a polygenic risk score were vulnerable to poorer self-regulation, and whether poorer self-regulation subsequently predicted the divergent outcomes of depressive symptoms and aggressive/antisocial behaviors. This study then examined whether depressive symptoms and aggressive/antisocial behaviors conferred risk for later alcohol use in adolescence, and whether polygenic risk and effortful control had direct effects on alcohol use that were not mediated through problem behaviors. Finally, the study examined the potential moderating role of gender in these pathways to alcohol use.

Structural equation modeling was used to test hypotheses. Results from an independent genome-wide association study of 5-hydroxyindoleacetic acid in the cerebrospinal fluid were used to create serotonin (5-HT) polygenic risk scores, wherein higher scores reflected lower levels of 5-HT functioning. Data from three time points were drawn from each sample, and all paths were prospective. Findings suggested that 5-HT polygenic risk did not predict self-regulatory constructs. However, 5-HT polygenic risk did predict the divergent outcomes of depression and aggression/antisociality, such that higher levels of 5-HT polygenic risk predicted greater levels of depression and aggression/antisociality. Results most clearly supported adolescents’ aggression/antisociality as a mechanism in the relation between 5-HT polygenic risk and later alcohol use. Deficits in self-regulation also predicted depression and aggression/antisociality, and indirectly predicted alcohol use through aggression/antisociality. These pathways to alcohol use might be the most salient for boys with low levels of socioeconomic status.

Results are novel contributions to the literature. The previously observed association between serotonin functioning and alcohol use might be due, in part, to the fact that individuals with lower levels of serotonin functioning are predisposed towards developing earlier aggression/antisociality. Results did not support the hypothesis that serotonin functioning predisposes individuals to deficits in self-regulatory abilities. Findings extend previous research by suggesting that serotonin functioning and self-regulation might be transdiagnostic risk factors for many types of psychopathology.
ContributorsWang, Frances Lynn (Author) / Chassin, Laurie (Thesis advisor) / Eisenberg, Nancy (Committee member) / Lemery-Chalfant, Kathryn (Committee member) / MacKinnon, David (Committee member) / Arizona State University (Publisher)
Created2017
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Description
The process of combining data is one in which information from disjoint datasets sharing at least a number of common variables is merged. This process is commonly referred to as data fusion, with the main objective of creating a new dataset permitting more flexible analyses than the separate analysis of

The process of combining data is one in which information from disjoint datasets sharing at least a number of common variables is merged. This process is commonly referred to as data fusion, with the main objective of creating a new dataset permitting more flexible analyses than the separate analysis of each individual dataset. Many data fusion methods have been proposed in the literature, although most utilize the frequentist framework. This dissertation investigates a new approach called Bayesian Synthesis in which information obtained from one dataset acts as priors for the next analysis. This process continues sequentially until a single posterior distribution is created using all available data. These informative augmented data-dependent priors provide an extra source of information that may aid in the accuracy of estimation. To examine the performance of the proposed Bayesian Synthesis approach, first, results of simulated data with known population values under a variety of conditions were examined. Next, these results were compared to those from the traditional maximum likelihood approach to data fusion, as well as the data fusion approach analyzed via Bayes. The assessment of parameter recovery based on the proposed Bayesian Synthesis approach was evaluated using four criteria to reflect measures of raw bias, relative bias, accuracy, and efficiency. Subsequently, empirical analyses with real data were conducted. For this purpose, the fusion of real data from five longitudinal studies of mathematics ability varying in their assessment of ability and in the timing of measurement occasions was used. Results from the Bayesian Synthesis and data fusion approaches with combined data using Bayesian and maximum likelihood estimation methods were reported. The results illustrate that Bayesian Synthesis with data driven priors is a highly effective approach, provided that the sample sizes for the fused data are large enough to provide unbiased estimates. Bayesian Synthesis provides another beneficial approach to data fusion that can effectively be used to enhance the validity of conclusions obtained from the merging of data from different studies.
ContributorsMarcoulides, Katerina M (Author) / Grimm, Kevin (Thesis advisor) / Levy, Roy (Thesis advisor) / MacKinnon, David (Committee member) / Suk, Hye Won (Committee member) / Arizona State University (Publisher)
Created2017
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Description

The objective of articulating sustainability visions through modeling is to enhance the outcomes and process of visioning in order to successfully move the system toward a desired state. Models emphasize approaches to develop visions that are viable and resilient and are crafted to adhere to sustainability principles. This approach is

The objective of articulating sustainability visions through modeling is to enhance the outcomes and process of visioning in order to successfully move the system toward a desired state. Models emphasize approaches to develop visions that are viable and resilient and are crafted to adhere to sustainability principles. This approach is largely assembled from visioning processes (resulting in descriptions of desirable future states generated from stakeholder values and preferences) and participatory modeling processes (resulting in systems-based representations of future states co-produced by experts and stakeholders). Vision modeling is distinct from normative scenarios and backcasting processes in that the structure and function of the future desirable state is explicitly articulated as a systems model. Crafting, representing and evaluating the future desirable state as a systems model in participatory settings is intended to support compliance with sustainability visioning quality criteria (visionary, sustainable, systemic, coherent, plausible, tangible, relevant, nuanced, motivational and shared) in order to develop rigorous and operationalizable visions. We provide two empirical examples to demonstrate the incorporation of vision modeling in research practice and education settings. In both settings, vision modeling was used to develop, represent, simulate and evaluate future desirable states. This allowed participants to better identify, explore and scrutinize sustainability solutions.

ContributorsIwaniec, David (Author) / Childers, Dan (Author) / VanLehn, Kurt (Author) / Wiek, Arnim (Author) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2014-07-01
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It has become common for sustainability science and resilience theory to be considered as complementary approaches. Occasionally the terms have been used interchangeably. Although these two approaches share some working principles and objectives, they also are based on some distinct assumptions about the operation of systems and how we can

It has become common for sustainability science and resilience theory to be considered as complementary approaches. Occasionally the terms have been used interchangeably. Although these two approaches share some working principles and objectives, they also are based on some distinct assumptions about the operation of systems and how we can best guide these systems into the future. Each approach would benefit from some scholars keeping sustainability science and resilience theory separate and focusing on further developing their distinctiveness and other scholars continuing to explore them in combination. Three areas of research in which following different procedures might be beneficial are whether to prioritize outcomes or system dynamics, how best to take advantage of community input, and increasing the use of knowledge of the past as a laboratory for potential innovations.

Created2013-11-30
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Description

The context in which many self-governed commons systems operate will likely be significantly altered as globalization processes play out over the next few decades. Such dramatic changes will induce some systems to fail and subsequently to be transformed, rather than merely adapt. Despite this possibility, research on globalization-induced transformations of

The context in which many self-governed commons systems operate will likely be significantly altered as globalization processes play out over the next few decades. Such dramatic changes will induce some systems to fail and subsequently to be transformed, rather than merely adapt. Despite this possibility, research on globalization-induced transformations of social-ecological systems (SESs) is still underdeveloped. We seek to help fill this gap by exploring some patterns of transformation in SESs and the question of what factors help explain the persistence of cooperation in the use of common-pool resources through transformative change. Through the analysis of 89 forest commons in South Korea that experienced such transformations, we found that there are two broad types of transformation, cooperative and noncooperative. We also found that two system-level properties, transaction costs associated group size and network diversity, may affect the direction of transformation. SESs with smaller group sizes and higher network diversity may better organize cooperative transformations when the existing system becomes untenable.

ContributorsYu, David (Author) / Anderies, John (Author) / Lee, Dowon (Author) / Perez, Irene (Author) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2013-11-30
Description

The effects of urbanization on ozone levels have been widely investigated over cities primarily located in temperate and/or humid regions. In this study, nested WRF-Chem simulations with a finest grid resolution of 1 km are conducted to investigate ozone concentrations O3 due to urbanization within cities in arid/semi-arid environments. First,

The effects of urbanization on ozone levels have been widely investigated over cities primarily located in temperate and/or humid regions. In this study, nested WRF-Chem simulations with a finest grid resolution of 1 km are conducted to investigate ozone concentrations O3 due to urbanization within cities in arid/semi-arid environments. First, a method based on a shape preserving Monotonic Cubic Interpolation (MCI) is developed and used to downscale anthropogenic emissions from the 4 km resolution 2005 National Emissions Inventory (NEI05) to the finest model resolution of 1 km. Using the rapidly expanding Phoenix metropolitan region as the area of focus, we demonstrate the proposed MCI method achieves ozone simulation results with appreciably improved correspondence to observations relative to the default interpolation method of the WRF-Chem system. Next, two additional sets of experiments are conducted, with the recommended MCI approach, to examine impacts of urbanization on ozone production: (1) the urban land cover is included (i.e., urbanization experiments) and, (2) the urban land cover is replaced with the region's native shrubland. Impacts due to the presence of the built environment on O3 are highly heterogeneous across the metropolitan area. Increased near surface O3 due to urbanization of 10–20 ppb is predominantly a nighttime phenomenon while simulated impacts during daytime are negligible. Urbanization narrows the daily O3 range (by virtue of increasing nighttime minima), an impact largely due to the region's urban heat island. Our results demonstrate the importance of the MCI method for accurate representation of the diurnal profile of ozone, and highlight its utility for high-resolution air quality simulations for urban areas.

ContributorsLi, Jialun (Author) / Georgescu, Matei (Author) / Hyde, Peter (Author) / Mahalov, Alex (Author) / Moustaoui, Mohamed (Author) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2014-11-01