Matching Items (39)
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Description
Accumulating evidence implicates exposure to adverse childhood experiences in the development of hypocortisolism in the long-term, and researchers are increasingly examining individual-level mechanisms that may underlie, exacerbate or attenuate this relation among at-risk populations. The current study takes a developmentally and theoretically informed approach to examining episodic childhood stressors, inherent

Accumulating evidence implicates exposure to adverse childhood experiences in the development of hypocortisolism in the long-term, and researchers are increasingly examining individual-level mechanisms that may underlie, exacerbate or attenuate this relation among at-risk populations. The current study takes a developmentally and theoretically informed approach to examining episodic childhood stressors, inherent and voluntary self-regulation, and physiological reactivity among a longitudinal sample of youth who experienced parental divorce. Participants were drawn from a larger randomized controlled trial of a preventive intervention for children of divorce between the ages of 9 and 12. The current sample included 159 young adults (mean age = 25.5 years; 53% male; 94% Caucasian) who participated in six waves of data collection, including a 15-year follow-up study. Participants reported on exposure to negative life events (four times over a 9-month period) during childhood, and mothers rated child temperament. Six years later, youth reported on the use of active and avoidant coping strategies, and 15 years later, they participated in a standardized psychosocial stress task and provided salivary cortisol samples prior to and following the task. Path analyses within a structural equation framework revealed that a multiple mediation model best fit the data. It was found that children with better mother-rated self-regulation (i.e. low impulsivity, low negative emotionality, and high attentional focus) exhibited lower total cortisol output 15 years later. In addition, greater self-regulation in childhood predicted greater use of active coping in adolescence, whereas a greater number of negative life events predicted increased use of avoidant coping in adolescence. Finally, a greater number of negative events in childhood predicted marginally lower total cortisol output, and higher levels of active coping in adolescence were associated with greater total cortisol output in young adulthood. Findings suggest that children of divorce who exhibit better self-regulation evidence lower cortisol output during a standardized psychosocial stress task relative to those who have higher impulsivity, lower attentional focus, and/or higher negative emotionality. The conceptual significance of the current findings, including the lack of evidence for hypothesized relations, methodological issues that arose, and issues in need of future research are discussed.
ContributorsHagan, Melissa (Author) / Luecken, Linda (Thesis advisor) / MacKinnon, David (Committee member) / Wolchik, Sharlene (Committee member) / Doane, Leah (Committee member) / Arizona State University (Publisher)
Created2013
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Description
In order to analyze data from an instrument administered at multiple time points it is a common practice to form composites of the items at each wave and to fit a longitudinal model to the composites. The advantage of using composites of items is that smaller sample sizes are required

In order to analyze data from an instrument administered at multiple time points it is a common practice to form composites of the items at each wave and to fit a longitudinal model to the composites. The advantage of using composites of items is that smaller sample sizes are required in contrast to second order models that include the measurement and the structural relationships among the variables. However, the use of composites assumes that longitudinal measurement invariance holds; that is, it is assumed that that the relationships among the items and the latent variables remain constant over time. Previous studies conducted on latent growth models (LGM) have shown that when longitudinal metric invariance is violated, the parameter estimates are biased and that mistaken conclusions about growth can be made. The purpose of the current study was to examine the impact of non-invariant loadings and non-invariant intercepts on two longitudinal models: the LGM and the autoregressive quasi-simplex model (AR quasi-simplex). A second purpose was to determine if there are conditions in which researchers can reach adequate conclusions about stability and growth even in the presence of violations of invariance. A Monte Carlo simulation study was conducted to achieve the purposes. The method consisted of generating items under a linear curve of factors model (COFM) or under the AR quasi-simplex. Composites of the items were formed at each time point and analyzed with a linear LGM or an AR quasi-simplex model. The results showed that AR quasi-simplex model yielded biased path coefficients only in the conditions with large violations of invariance. The fit of the AR quasi-simplex was not affected by violations of invariance. In general, the growth parameter estimates of the LGM were biased under violations of invariance. Further, in the presence of non-invariant loadings the rejection rates of the hypothesis of linear growth increased as the proportion of non-invariant items and as the magnitude of violations of invariance increased. A discussion of the results and limitations of the study are provided as well as general recommendations.
ContributorsOlivera-Aguilar, Margarita (Author) / Millsap, Roger E. (Thesis advisor) / Levy, Roy (Committee member) / MacKinnon, David (Committee member) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Research shows that general parenting practices (e.g., support and discipline), influence adolescent substance use. However, socialization theory suggests that parental socialization occurs not only through general parenting practices, but also through parents' attempts to influence specific behaviors and values. A growing literature supports links between substance-specific parenting and adolescent substance

Research shows that general parenting practices (e.g., support and discipline), influence adolescent substance use. However, socialization theory suggests that parental socialization occurs not only through general parenting practices, but also through parents' attempts to influence specific behaviors and values. A growing literature supports links between substance-specific parenting and adolescent substance use. For adolescent alcohol use, there are considerable limitations and gaps within this literature. To address these limitations, the present study examined the factor structure of alcohol-specific parenting, investigated the determinants of alcohol-specific parenting, and explored its association with nondrinking adolescents' attitudes about alcohol use. Using a high-risk sample of nondrinking adolescents and their parents, the current study found three dimensions of alcohol-specific parenting using both adolescent and parent reports, but also found evidence of non-invariance across reporters. Results also revealed complex roles of parental alcohol use disorder (AUD; including recovered and current AUD), family history of AUD, and current drinking as determinants of the three dimensions of anti-alcohol parenting behaviors. Moreover, the current study showed that the effects of these determinants varied by the reporter of the parenting behavior. Finally, the current study found the dimensions of alcohol-specific parenting to be unique and significant predictors of nondrinking adolescents' attitudes about alcohol, over and above general parenting practices, parent AUD, and parent current drinking. Given its demonstrated distinctness from general parenting practices, its link with adolescent alcohol attitudes, and its potential malleability, alcohol-specific parenting may be an important complement to interventions targeting parents of adolescents.
ContributorsHandley, Elizabeth D (Author) / Chassin, Laurie (Thesis advisor) / MacKinnon, David (Committee member) / Crnic, Keith (Committee member) / Sandler, Irwin (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The nature and correlates of emerging internalizing symptoms in young children are largely unknown. Maternal factors such as psychological symptoms and detached parenting style have been found to be present in children with anxiety and depression. Further, child attentional control in task completion has been associated with difficulty related to

The nature and correlates of emerging internalizing symptoms in young children are largely unknown. Maternal factors such as psychological symptoms and detached parenting style have been found to be present in children with anxiety and depression. Further, child attentional control in task completion has been associated with difficulty related to internalizing problems. This study tested hypotheses that child anxiety and depression at age five could be predicted by a combination of maternal distress and maternal detached behavior recorded at age three. An additional hypothesis was tested to determine if child attentional control at age four may be a partial mediator of the relation between maternal symptoms and parenting to child internalizing symptoms. Using structural equation modeling, no hypotheses were supported; child internalizing problems were not significantly predicted by maternal distress nor detached parenting. Further, child attentional control was not predicted by maternal distress or detached behavior, nor did attentional control predict internalizing problems. Findings indicate that over a two-year interval, childhood internalizing problems at age five are likely best predicted by early internalizing problems at age three. There was no support that the mother or child factors tested were predictive of child outcomes.
ContributorsSkelley, Shayna (Author) / Crnic, Keith A (Thesis advisor) / Eisenberg, Nancy (Committee member) / MacKinnon, David (Committee member) / Arizona State University (Publisher)
Created2010
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Description
Psychologists report effect sizes in randomized controlled trials to facilitate interpretation and inform clinical or policy guidance. Since commonly used effect size measures (e.g., standardized mean difference) are not sensitive to heterogeneous treatment effects, methodologists have suggested the use of an alternative effect size δ, a between-subjects causal parameter describing

Psychologists report effect sizes in randomized controlled trials to facilitate interpretation and inform clinical or policy guidance. Since commonly used effect size measures (e.g., standardized mean difference) are not sensitive to heterogeneous treatment effects, methodologists have suggested the use of an alternative effect size δ, a between-subjects causal parameter describing the probability that the outcome of a random participant in the treatment group is better than the outcome of another random participant in the control group. Although this effect size is useful, researchers could mistakenly use δ to describe its within-subject analogue, ψ, the probability that an individual will do better under the treatment than the control. Hand’s paradox describes the situation where ψ and δ are on opposing sides of 0.5: δ may imply most are helped whereas the (unknown) underlying ψ indicates that most are harmed by the treatment. The current study used Monte Carlo simulations to investigate plausible situations under which Hand’s paradox does and does not occur, tracked the magnitude of the discrepancy between ψ and δ, and explored whether the size of the discrepancy could be reduced with a relevant covariate. The findings suggested that although the paradox should not occur under bivariate normal data conditions in the population, there could be sample cases with the paradox. The magnitude of the discrepancy between ψ and δ depended on both the size of the average treatment effect and the underlying correlation between the potential outcomes, ρ. Smaller effects led to larger discrepancies when ρ < 0 and ρ = 1, whereas larger effects led to larger discrepancies when 0 < ρ < 1. It was useful to consider a relevant covariate when calculating ψ and δ. Although ψ and δ were still discrepant within covariate levels, results indicated that conditioning upon relevant covariates is still useful in describing heterogeneous treatment effects.
ContributorsLiu, Xinran (Author) / Anderson, Samantha F (Thesis advisor) / McNeish, Daniel (Committee member) / MacKinnon, David (Committee member) / Arizona State University (Publisher)
Created2023
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Description
The proliferation of intensive longitudinal datasets has necessitated the development of analytical techniques that are flexible and accessible to researchers collecting dyadic or individual data. Dynamic structural equation models (DSEMs), as implemented in Mplus, provides the flexibility researchers require by combining components from multilevel modeling, structural equation modeling, and time

The proliferation of intensive longitudinal datasets has necessitated the development of analytical techniques that are flexible and accessible to researchers collecting dyadic or individual data. Dynamic structural equation models (DSEMs), as implemented in Mplus, provides the flexibility researchers require by combining components from multilevel modeling, structural equation modeling, and time series analyses. This dissertation project presents a simulation study that evaluates the performance of categorical DSEM using a probit link function across different numbers of clusters (N = 50 or 200), timepoints (T = 14, 28, or 56), categories on the outcome (2, 3, or 5), and distribution of responses on the outcome (symmetric/approximate normal, skewed, or uniform) for both univariate and multivariate models (representing individual data and dyadic longitudinal Actor-Partner Interdependence Model data, respectively). The 3- and 5-category model conditions were also evaluated as continuous DSEMs across the same cluster, timepoint, and distribution conditions to evaluate to what extent ignoring the categorical nature of the outcome impacted model performance. Results indicated that previously-suggested minimums for number of clusters and timepoints from studies evaluating continuous DSEM performance with continuous outcomes are not large enough to produce unbiased and adequately powered models in categorical DSEM. The distribution of responses on the outcome did not have a noticeable impact in model performance for categorical DSEM, but did affect model performance when fitting a continuous DSEM to the same datasets. Ignoring the categorical nature of the outcome lead to underestimated effects across parameters and conditions, and showed large Type-I error rates in the N = 200 cluster conditions.
ContributorsSavord, Andrea (Author) / McNeish, Daniel (Thesis advisor) / Grimm, Kevin J (Committee member) / Iida, Masumi (Committee member) / Levy, Roy (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Behavior challenges impact children and educational professionals on a daily basis; however, it is difficult for educators to obtain high quality training in behavior management. The purpose of this study was to compare cognitive apprenticeship and group work, two teaching methods, to determine which provides better knowledge and implementation outcomes

Behavior challenges impact children and educational professionals on a daily basis; however, it is difficult for educators to obtain high quality training in behavior management. The purpose of this study was to compare cognitive apprenticeship and group work, two teaching methods, to determine which provides better knowledge and implementation outcomes for educators taking a course on behavior analysis. Seventeen educational professionals currently working with students who display challenging behavior were randomly assigned to the cognitive apprenticeship or group work conditions. The difference between the conditions is the introduction of a coach in the cognitive apprenticeship condition. The coach guides learners through the process of understanding and using behavior analysis throughout the course by providing feedback, scaffolding, and encouraging reflection and exploration. Participants completed pre-, post-, and post-posttests that measured their knowledge of behavior analysis and how well they implemented the skills taught in the course. Additionally, they completed weekly quizzes and reported how often they used the skills in real-life situations. Overall group differences across time points for knowledge and implementation scores were analyzed using a repeated measures analysis of variance (ANOVA). There were significant differences across time for both scores but not condition or time by condition. A covariance pattern model was used to determine if self-efficacy, self-confidence, previous behavior knowledge, or overall quiz performance predicted the variance in knowledge and implementation scores on the pre-, post-, and post-posttests across conditions. Time was the only significant predictor of knowledge scores, while time, condition and self-efficacy significantly predicted the variance in implementation scores. Additionally, one-way ANOVAs were used to find condition-based differences in quiz scores and practical skill use, neither of which were significant. Finally, a linear regression was used to determine if on quiz performance predicts the use of skills in real-world settings, which it did not. The courses impact on learning, skill use, and student behavior as well as future applications are discussed.
ContributorsSacchetta, Melissa (Author) / Gray, Shelley (Thesis advisor) / Braden, B. Blair (Committee member) / McNeish, Daniel (Committee member) / Zuiker, Steve (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Attendance and engagement in available parenting interventions in both research and community settings is often inconsistent. Recent research suggests that varying the delivery modality of the intervention (i.e., in-person, telehealth, or online) has the potential to increase engagement with evidence-based parenting programs. However, while it is known that both facilitator

Attendance and engagement in available parenting interventions in both research and community settings is often inconsistent. Recent research suggests that varying the delivery modality of the intervention (i.e., in-person, telehealth, or online) has the potential to increase engagement with evidence-based parenting programs. However, while it is known that both facilitator and parent characteristics also influence engagement, no study has evaluated whether those characteristics moderate the influence that modality has on engagement. Utilizing data from the randomized controlled comparative effectiveness trial of the After Deployment, Adaptive Parenting Tools intervention, this study aimed to assess whether facilitators’ gender, military background, and competence moderated the effect of modality on parents’ engagement. Results suggested that parents were significantly more likely to have attended when they were randomized to the telehealth condition. Additionally, while there were no moderating relationships, female facilitators and facilitators who were more competent had overall higher attendance. Additionally, in the group format, facilitators with military backgrounds had higher engagement than those who did not. Understanding the effects that delivery modality and facilitators have on parental engagement is critical to continue and amplify implementation efforts in community settings.
ContributorsBasha, Sydni A. J. (Author) / Gewirtz, Abigail H (Thesis advisor) / Berkel, Cady (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Mediation analysis is integral to psychology, investigating human behavior’s causal mechanisms. The diversity of explanations for human behavior has implications for the estimation and interpretation of statistical mediation models. Individuals can have similar observed outcomes while undergoing different causal processes or different observed outcomes while receiving the same treatment. Researchers

Mediation analysis is integral to psychology, investigating human behavior’s causal mechanisms. The diversity of explanations for human behavior has implications for the estimation and interpretation of statistical mediation models. Individuals can have similar observed outcomes while undergoing different causal processes or different observed outcomes while receiving the same treatment. Researchers can employ diverse strategies when studying individual differences in multiple mediation pathways, including individual fit measures and analysis of residuals. This dissertation investigates the use of individual residuals and fit measures to identify individual differences in multiple mediation pathways. More specifically, this study focuses on mediation model residuals in a heterogeneous population in which some people experience indirect effects through one mediator and others experience indirect effects through a different mediator. A simulation study investigates 162 conditions defined by effect size and sample size for three proposed methods: residual differences, delta z, and generalized Cook’s distance. Results indicate that analogs of Type 1 error rates are generally acceptable for the method of residual differences, but statistical power is limited. Likewise, neither delta z nor gCd could reliably distinguish between contrasts that had true effects and those that did not. The outcomes of this study reveal the potential for statistical measures of individual mediation. However, limitations related to unequal subpopulation variances, multiple dependent variables, the inherent relationship between direct effects and unestimated indirect effects, and minimal contrast effects require more research to develop a simple method that researchers can use on single data sets.
ContributorsSmyth, Heather Lynn (Author) / MacKinnon, David (Thesis advisor) / Tein, Jenn-Yun (Committee member) / McNeish, Daniel (Committee member) / Grimm, Kevin (Committee member) / Arizona State University (Publisher)
Created2022
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Description
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

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.
ContributorsAlvarez Bartolo, Diana (Author) / Mackinnon, David P. (Thesis advisor) / Grimm, Kevin J. (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2022