Matching Items (33)
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Recent advances in hierarchical or multilevel statistical models and causal inference using the potential outcomes framework hold tremendous promise for mock and real jury research. These advances enable researchers to explore how individual jurors can exert a bottom-up effect on the jury’s verdict and how case-level features can exert a

Recent advances in hierarchical or multilevel statistical models and causal inference using the potential outcomes framework hold tremendous promise for mock and real jury research. These advances enable researchers to explore how individual jurors can exert a bottom-up effect on the jury’s verdict and how case-level features can exert a top-down effect on a juror’s perception of the parties at trial. This dissertation explains and then applies these technical advances to a pre-existing mock jury dataset to provide worked examples in an effort to spur the adoption of these techniques. In particular, the paper introduces two new cross-level mediated effects and then describes how to conduct ecological validity tests with these mediated effects. The first cross-level mediated effect, the a1b1 mediated effect, is the juror level mediated effect for a jury level manipulation. The second cross-level mediated effect, the a2bc mediated effect, is the unique contextual effect that being in a jury has on the individual the juror. When a mock jury study includes a deliberation versus non-deliberation manipulation, the a1b1 can be compared for the two conditions, enabling a general test of ecological validity. If deliberating in a group generally influences the individual, then the two indirect effects should be significantly different. The a2bc can also be interpreted as a specific test of how much changes in jury level means of this specific mediator effect juror level decision-making.
ContributorsLovis-McMahon, David (Author) / Schweitzer, Nicholas (Thesis advisor) / Saks, Michael (Thesis advisor) / Salerno, Jessica (Committee member) / MacKinnon, David (Committee member) / Arizona State University (Publisher)
Created2015
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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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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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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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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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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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This thesis introduces new techniques for clustering distributional data according to their geometric similarities. This work builds upon the optimal transportation (OT) problem that seeks global minimum cost for matching distributional data and leverages the connection between OT and power diagrams to solve different clustering problems. The OT formulation is

This thesis introduces new techniques for clustering distributional data according to their geometric similarities. This work builds upon the optimal transportation (OT) problem that seeks global minimum cost for matching distributional data and leverages the connection between OT and power diagrams to solve different clustering problems. The OT formulation is based on the variational principle to differentiate hard cluster assignments, which was missing in the literature. This thesis shows multiple techniques to regularize and generalize OT to cope with various tasks including clustering, aligning, and interpolating distributional data. It also discusses the connections of the new formulation to other OT and clustering formulations to better understand their gaps and the means to close them. Finally, this thesis demonstrates the advantages of the proposed OT techniques in solving machine learning problems and their downstream applications in computer graphics, computer vision, and image processing.
ContributorsMi, Liang (Author) / Wang, Yalin (Thesis advisor) / Chen, Kewei (Committee member) / Karam, Lina (Committee member) / Li, Baoxin (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2020
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Description

Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process during an early symptomatic stage. Structural magnetic resonance imaging (MRI)

Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process during an early symptomatic stage. Structural magnetic resonance imaging (MRI) measures have been the mainstay of Alzheimer's disease (AD) imaging research, however, ventricular morphometry analysis remains challenging because of its complicated topological structure. Here we describe a novel ventricular morphometry system based on the hyperbolic Ricci flow method and tensor-based morphometry (TBM) statistics. Unlike prior ventricular surface parameterization methods, hyperbolic conformal parameterization is angle-preserving and does not have any singularities. Our system generates a one-to-one diffeomorphic mapping between ventricular surfaces with consistent boundary matching conditions. The TBM statistics encode a great deal of surface deformation information that could be inaccessible or overlooked by other methods. We applied our system to the baseline MRI scans of a set of MCI subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI: 71 MCI converters vs. 62 MCI stable). Although the combined ventricular area and volume features did not differ between the two groups, our fine-grained surface analysis revealed significant differences in the ventricular regions close to the temporal lobe and posterior cingulate, structures that are affected early in AD. Significant correlations were also detected between ventricular morphometry, neuropsychological measures, and a previously described imaging index based on fluorodeoxyglucose positron emission tomography (FDG-PET) scans. This novel ventricular morphometry method may offer a new and more sensitive approach to study preclinical and early symptomatic stage AD.

ContributorsShi, Jie (Author) / Stonnington, Cynthia M. (Author) / Thompson, Paul M. (Author) / Chen, Kewei (Author) / Gutman, Boris (Author) / Reschke, Cole (Author) / Baxter, Leslie C. (Author) / Reiman, Eric M. (Author) / Caselli, Richard J. (Author) / Wang, Yalin (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2015-01-01
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Description

Background: Counselor behaviors that mediate the efficacy of motivational interviewing (MI) are not well understood, especially when applied to health behavior promotion. We hypothesized that client change talk mediates the relationship between counselor variables and subsequent client behavior change.

Methods: Purposeful sampling identified individuals from a prospective randomized worksite trial using an MI

Background: Counselor behaviors that mediate the efficacy of motivational interviewing (MI) are not well understood, especially when applied to health behavior promotion. We hypothesized that client change talk mediates the relationship between counselor variables and subsequent client behavior change.

Methods: Purposeful sampling identified individuals from a prospective randomized worksite trial using an MI intervention to promote firefighters’ healthy diet and regular exercise that increased dietary intake of fruits and vegetables (n = 21) or did not increase intake of fruits and vegetables (n = 22). MI interactions were coded using the Motivational Interviewing Skill Code (MISC 2.1) to categorize counselor and firefighter verbal utterances. Both Bayesian and frequentist mediation analyses were used to investigate whether client change talk mediated the relationship between counselor skills and behavior change.

Results: Counselors’ global spirit, empathy, and direction and MI-consistent behavioral counts (e.g., reflections, open questions, affirmations, emphasize control) significantly correlated with firefighters’ total client change talk utterances (rs = 0.42, 0.40, 0.30, and 0.61, respectively), which correlated significantly with their fruit and vegetable intake increase (r = 0.33). Both Bayesian and frequentist mediation analyses demonstrated that findings were consistent with hypotheses, such that total client change talk mediated the relationship between counselor’s skills—MI-consistent behaviors [Bayesian mediated effect: αβ = .06 (.03), 95% CI = .02, .12] and MI spirit [Bayesian mediated effect: αβ = .06 (.03), 95% CI = .01, .13]—and increased fruit and vegetable consumption.

Conclusion: Motivational interviewing is a resource- and time-intensive intervention, and is currently being applied in many arenas. Previous research has identified the importance of counselor behaviors and client change talk in the treatment of substance use disorders. Our results indicate that similar mechanisms may underlie the effects of MI for dietary change. These results inform MI training and application by identifying those processes critical for MI success in health promotion domains.

ContributorsPirlott, Angela (Author) / Kisbu-Sakarya, Yasemin (Author) / DeFrancesco, Carol A. (Author) / Elliot, Diane L. (Author) / MacKinnon, David (Author) / College of Liberal Arts and Sciences (Contributor)
Created2012-06-08