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Type 1 Diabetes Mellitus (T1DM) is a chronic disease that requires maintaining tight metabolic control through complex behavioral and pharmaceutical regimens. Subtle cognitive impairments and stress response dysregulation may partially account for problems negotiating life changes and maintaining treatment adherence among emerging adults. The current study examined whether young adults

Type 1 Diabetes Mellitus (T1DM) is a chronic disease that requires maintaining tight metabolic control through complex behavioral and pharmaceutical regimens. Subtle cognitive impairments and stress response dysregulation may partially account for problems negotiating life changes and maintaining treatment adherence among emerging adults. The current study examined whether young adults with T1DM physiologically respond to psychological stress in a dysregulated manner compared to non-diabetic peers, and if such individuals also demonstrated greater cognitive declines following psychological stress. Participants included 23 young adults with T1DM and 52 non-diabetic controls yoked to T1DM participants based on age, gender, ethnicity, participant education, and maternal education. Participants completed a laboratory-based social stressor, pre- and post-stressor neurocognitive testing, provided fingerstick blood spots (for glucose levels) and salivary samples (for cortisol levels) at five points across the protocol, and completed psychosocial questionnaires. Related measures ANOVAs were conducted to assess differences between T1DM participants and the average of yoked controls on cortisol and cognitive outcomes. Results demonstrated that differences in cortisol reactivity were dependent on T1DM participants' use of insulin pump therapy (IPT). T1DM participants not using IPT demonstrated elevated cortisol reactivity compared to matched controls. There was no difference in cortisol reactivity between the T1DM participants on IPT and matched controls. On the Stroop task, performance patterns did not differ between participants with T1DM not on IPT and matched controls. The performance of participants with T1DM on IPT slightly improved following the stressor and matched controls slightly worsened. On the Trail Making Test, the performance of participants with T1DM was not different following the stressor whereas participants without T1DM demonstrated a decline following the stressor. Participants with and without T1DM did not differ in patterns of performance on the Rey Verbal Learning Task, Sustained Attention Allocation Task, Controlled Oral Word Association Task, or overall cortisol output across participation. The results of this study are suggestive of an exaggerated cortisol response to psychological stress in T1DM and indicate potential direct and indirect protective influences of IPT.
ContributorsMarreiro, Catherine (Author) / Luecken, Linda (Thesis advisor) / Doane, Leah (Thesis advisor) / Barrera, Manuel (Committee member) / Aiken, Leona (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Missing data are common in psychology research and can lead to bias and reduced power if not properly handled. Multiple imputation is a state-of-the-art missing data method recommended by methodologists. Multiple imputation methods can generally be divided into two broad categories: joint model (JM) imputation and fully conditional specification (FCS)

Missing data are common in psychology research and can lead to bias and reduced power if not properly handled. Multiple imputation is a state-of-the-art missing data method recommended by methodologists. Multiple imputation methods can generally be divided into two broad categories: joint model (JM) imputation and fully conditional specification (FCS) imputation. JM draws missing values simultaneously for all incomplete variables using a multivariate distribution (e.g., multivariate normal). FCS, on the other hand, imputes variables one at a time, drawing missing values from a series of univariate distributions. In the single-level context, these two approaches have been shown to be equivalent with multivariate normal data. However, less is known about the similarities and differences of these two approaches with multilevel data, and the methodological literature provides no insight into the situations under which the approaches would produce identical results. This document examined five multilevel multiple imputation approaches (three JM methods and two FCS methods) that have been proposed in the literature. An analytic section shows that only two of the methods (one JM method and one FCS method) used imputation models equivalent to a two-level joint population model that contained random intercepts and different associations across levels. The other three methods employed imputation models that differed from the population model primarily in their ability to preserve distinct level-1 and level-2 covariances. I verified the analytic work with computer simulations, and the simulation results also showed that imputation models that failed to preserve level-specific covariances produced biased estimates. The studies also highlighted conditions that exacerbated the amount of bias produced (e.g., bias was greater for conditions with small cluster sizes). The analytic work and simulations lead to a number of practical recommendations for researchers.
ContributorsMistler, Stephen (Author) / Enders, Craig K. (Thesis advisor) / Aiken, Leona (Committee member) / Levy, Roy (Committee member) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2015
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Family plays an important yet understudied role in the development of psychopathology during childhood, particularly for children at developmental risk. Indeed, much of the research on families has actually concentrated more on risk processes in individual family members or within-family subsystems. In general, important and complex associations have been found

Family plays an important yet understudied role in the development of psychopathology during childhood, particularly for children at developmental risk. Indeed, much of the research on families has actually concentrated more on risk processes in individual family members or within-family subsystems. In general, important and complex associations have been found among family-related constructs such as marital conflict, parent-child relationships, parental depression, and parenting stress, which have in turn been found to contribute to the emergence of children's behavioral problems. Research has begun to emerge that certain family system constructs, such as cohesion, organization, and control may influence children's development, but this research has been limited by a focus on parent-reports of family functioning, rather than utilizing observational methods. With notable exceptions, there is almost no observational research examining families of children at developmental risk. This study examined the longitudinal relations among family risk and family system constructs, as well as how family systems constructs mediated the relations between family risk and child outcome. Further, the study examined how developmental risk moderated these relations. The sample followed 242 families of children with and without developmental risk across the transition-to-school period. Family risk factors were assessed at 5 years, using parental reports of symptomatology, parenting stress, and marital adjustment, and observational assessments of the parent-child relationship. Family system constructs (cohesion, warmth, conflict, organization, control) were measured at age 6 using structured observations of the entire family playing a board game. Child behavior problems and social competence were assessed at age 7. Results indicated that families of children with developmental delays did not differ from families of typically developing children on the majority of family system attributes. Cohesion and organization mediated the relations between specific family risk factors and social competence for all families. For families of typically developing children only, higher levels of control were associated with more behavior problems and less social competence. These findings underscore the importance of family-level assessment in understanding the development of psychopathology. Important family effects on children's social competence were found, although the pathways among family risk and family systems attributes are complex.
ContributorsGerstein, Emily Davis (Author) / Crnic, Keith A (Thesis advisor) / Aiken, Leona (Committee member) / Bradley, Robert (Committee member) / Gonzales, Nancy (Committee member) / Arizona State University (Publisher)
Created2012
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Purpose: Over-identification of Navajo Head Start children into special education on the Navajo Reservation has come to the attention of Tribal leaders, Educational leaders, and parents due to the use of invalid assessment measures. Dynamic assessment (DA) of narratives may be a tool for distinguishing language differences from language

Purpose: Over-identification of Navajo Head Start children into special education on the Navajo Reservation has come to the attention of Tribal leaders, Educational leaders, and parents due to the use of invalid assessment measures. Dynamic assessment (DA) of narratives may be a tool for distinguishing language differences from language disorders. The purpose of this study is to determine whether the Predictive Early Assessment of Reading and Language (PEARL), a dynamic assessment of narratives, accurately classifies Navajo Head Start students with typically developing (TD) language or with language impairment (LI), and to examine which measures best predict children’s overall performances on the PEARL.

Method: Ninety, 4- and 5-year-old Navajo preschoolers with LI and with TD language were selected. Children completed the PEARL, which measured both language comprehension and production using pretest and posttest scores, and a modifiability scale. In addition, children completed the Clinical Evaluation of Language Fundamental, Preschool, Second Edition (CELF – Preschool 2) and language samples. A Navajo Speech Language Pathologist confirmed the diagnosis of the participants. Research assistants pretested, briefly taught the principles of narrative structure (story grammar, language complexity and episode) and evaluated response to learning using an index of modifiability.

Results: Results of discriminant analysis indicated that PEARL pretest differentiated both ability groups with 89% accuracy. In addition, posttest scores discriminated with 89% accuracy and modifiability scores with 100% accuracy. Further, the subtest story grammar was the best predictor at pretest and posttest, although modifiability scores were better predictors of both ability groups.

Conclusion: Findings indicate that the PEARL is a promising assessment for accurately differentiating Navajo preschool children with LI from Navajo preschool children with TD language. The PEARL’s recommended pretest cut score over-identified Navajo children with TD language; therefore, a new recommended cut score was determined.
ContributorsHenderson, Davis E (Author) / Restrepo, Maria Adelaida (Thesis advisor) / Aiken, Leona (Committee member) / Petersen, Douglas (Committee member) / Romero-Little, Mary Eunice (Committee member) / Kleinsasser, Robert (Committee member) / Arizona State University (Publisher)
Created2017
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Description
In investigating mediating processes, researchers usually use randomized experiments and linear regression or structural equation modeling to determine if the treatment affects the hypothesized mediator and if the mediator affects the targeted outcome. However, randomizing the treatment will not yield accurate causal path estimates unless certain assumptions are satisfied. Since

In investigating mediating processes, researchers usually use randomized experiments and linear regression or structural equation modeling to determine if the treatment affects the hypothesized mediator and if the mediator affects the targeted outcome. However, randomizing the treatment will not yield accurate causal path estimates unless certain assumptions are satisfied. Since randomization of the mediator may not be plausible for most studies (i.e., the mediator status is not randomly assigned, but self-selected by participants), both the direct and indirect effects may be biased by confounding variables. The purpose of this dissertation is (1) to investigate the extent to which traditional mediation methods are affected by confounding variables and (2) to assess the statistical performance of several modern methods to address confounding variable effects in mediation analysis. This dissertation first reviewed the theoretical foundations of causal inference in statistical mediation analysis, modern statistical analysis for causal inference, and then described different methods to estimate causal direct and indirect effects in the presence of two post-treatment confounders. A large simulation study was designed to evaluate the extent to which ordinary regression and modern causal inference methods are able to obtain correct estimates of the direct and indirect effects when confounding variables that are present in the population are not included in the analysis. Five methods were compared in terms of bias, relative bias, mean square error, statistical power, Type I error rates, and confidence interval coverage to test how robust the methods are to the violation of the no unmeasured confounders assumption and confounder effect sizes. The methods explored were linear regression with adjustment, inverse propensity weighting, inverse propensity weighting with truncated weights, sequential g-estimation, and a doubly robust sequential g-estimation. Results showed that in estimating the direct and indirect effects, in general, sequential g-estimation performed the best in terms of bias, Type I error rates, power, and coverage across different confounder effect, direct effect, and sample sizes when all confounders were included in the estimation. When one of the two confounders were omitted from the estimation process, in general, none of the methods had acceptable relative bias in the simulation study. Omitting one of the confounders from estimation corresponded to the common case in mediation studies where no measure of a confounder is available but a confounder may affect the analysis. Failing to measure potential post-treatment confounder variables in a mediation model leads to biased estimates regardless of the analysis method used and emphasizes the importance of sensitivity analysis for causal mediation analysis.
ContributorsKisbu Sakarya, Yasemin (Author) / Mackinnon, David Peter (Thesis advisor) / Aiken, Leona (Committee member) / West, Stephen (Committee member) / Millsap, Roger (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Women are exposed to numerous endogenous and exogenous hormones across the lifespan. In the last several decades, the prescription of novel hormonal contraceptives and hormone therapies (HTs) have resulted in aging women that have a unique hormone exposure history; little is known about the impact of these hormone exposures on

Women are exposed to numerous endogenous and exogenous hormones across the lifespan. In the last several decades, the prescription of novel hormonal contraceptives and hormone therapies (HTs) have resulted in aging women that have a unique hormone exposure history; little is known about the impact of these hormone exposures on short- and long- term brain health. The goal of my dissertation was to understand how lifetime hormone exposures shape the female cognitive phenotype using several innovative approaches, including a new human spatial working memory task, the human radial arm maze (HRAM), and several rodent menopause models with variants of clinically used hormone treatments. Using the HRAM (chapter 2) and established human neuropsychological tests, I determined males outperformed females with high endogenous or exogenous estrogen levels on visuospatial tasks and the spatial working memory HRAM (chapter 3). Evaluating the synthetic estrogen in contraceptives, ethinyl estradiol (EE), I found a high EE dose impaired spatial working memory in ovariectomized (Ovx) rats, medium and high EE doses reduced choline-acetyltransferace-immunoreactive neuron population estimates in the basal forebrain following Ovx (chapter 4), and low EE impaired spatial cognition in ovary-intact rats (chapter 5). Assessing the impact of several clinically-used HTs, I identified a window of opportunity around ovarian follicular depletion outside of which the HT conjugated equine estrogens (CEE) was detrimental to spatial memory (chapter 6), as well as therapeutic potentials for synthetic contraceptive hormones (chapter 9) and bioidentical estradiol (chapter 7) during and after the transition to menopause. Chapter 6 and 7 findings, that estradiol and Ovx benefitted cognition after the menopause transition, but CEE did not, are perhaps due to the negative impact of ovarian-produced, androstenedione-derived estrone; indeed, blocking androstenedione’s conversion to estrone prevented its cognitive impairments (chapter 8). Finally, I determined that EE combined with the popular progestin levonorgestrel benefited spatial memory during the transition to menopause, a profile not seen with estradiol, levonorgestrel, or EE alone (chapter 9). This work identifies several cognitively safe, and enhancing, hormonal treatment options at different time points throughout female aging, revealing promising avenues toward optimizing female health.
ContributorsMennenga, Sarah E (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Aiken, Leona (Committee member) / Whiteaker, Paul (Committee member) / Talboom, Joshua (Committee member) / Arizona State University (Publisher)
Created2015