Matching Items (12)
Description
The transition to college is a time of increased opportunity and stress that spans across multiple domains (e.g., social life, academic workload, finances). Adolescents who encounter significant stress during the transition to college may be vulnerable to adverse outcomes, due to a “wear and tear” of physiological systems, including the hypothalamic-pituitary-adrenal (HPA) axis. Latino students may be particularly at-risk for heightened stress exposure, as minority youth often experience both minority-specific stressors and general life stress. Despite this, the majority of research on Latino students is limited to the examination of singular forms of stress, and little is known regarding the cumulative impact of multiple forms of stress on Latino students’ HPA axis functioning. The present study employed a “multi-risk model approach” to examine the additive, common, and cumulative effects of multiple types of stress (general, academic, social, financial, bicultural, discrimination) on HPA axis functioning in Latino college students (N = 209; 64.4% female; Mage = 18.95). Results from three-level growth curve models indicated that, in the additive model, no stressors were associated with the CAR, but general stress was associated with a flatter diurnal cortisol slope (DCS) and bicultural stress was linked with a steeper DCS. In the common model, the college stress latent factor was related to a reduced cortisol awakening response (CAR), but not the DCS. In the cumulative model, cumulative risk was linked with a lower CAR, but not the DCS. These findings highlight the physiological correlates of various stressors experienced by Latino college students.
ContributorsSasser, Jeri (Author) / Doane, Leah D (Thesis advisor) / Su, Jinni (Committee member) / Grimm, Kevin J (Committee member) / Arizona State University (Publisher)
Created2022
Description
Various physical and psychological forms of development take place during the transition from childhood to adolescence, including the onset of puberty, delayed sleep-wake behavior patterns, and increases in internalizing symptomatology. Theory suggests that pubertal processes influence the onset of internalizing symptoms, and this association may differ between boys and girls. The contextual amplification hypothesis suggests that pubertal development interacts with contextual or dispositional factors to impact risk for psychopathology. Family stress and peer stress are two critical factors during early adolescence that have potential moderating effects on the association between pubertal development and internalizing symptoms. In line with the biopsychosocial framework, the current study examined various psychosocial (e.g., family stress, peer stress) and biological (e.g., sleep, genetics) factors that may have effects on the puberty-internalizing relation. Participants were a racially/ethnically and socioeconomically diverse sample of twins who were part of an ongoing longitudinal study (N=818 children; Arizona Twin Project; Lemery-Chalfant et al. 2019). The current study examined the association between puberty and internalizing symptoms, with stress (i.e., family, peer) as potential moderators, and sleep indicators (i.e., objective and self-reported sleep) as potential mediators. Behavior genetic analyses explored the moderated heritability of family stress on internalizing symptoms. Findings revealed that greater pubertal development predicted higher internalizing symptoms in boys, but not girls. For girls, peer stress interacted with pubertal development to predict internalizing symptoms, but simple slopes were not significant. Sleep indicators were not significant mediators between pubertal development and internalizing symptoms for boys or girls. Univariate twin models revealed environmental influences on internalizing symptoms, and both genetic and environmental influences on peer stress. Family stress did not significantly moderate the genetic and environmental influences of internalizing symptoms.
ContributorsLecarie, Emma (Author) / Doane, Leah D (Thesis advisor) / Lemery-Chalfant, Kathryn (Committee member) / Gewirtz, Abigail H (Committee member) / Grimm, Kevin J (Committee member) / Arizona State University (Publisher)
Created2024
Description
This dissertation combines three first-author manuscripts that focused broadly on the study of adolescent sleep within a family context (Sasser et al., 2021; Sasser & Oshri, 2023; Sasser et al., 2023). First, Chapter 1 introduces the theoretical background and empirical research that grounded the research questions and hypotheses explored across the studies. The first study (Chapter 2) examined the influence of family connection on actigraphy-measured sleep among Latinx late adolescents and explored family dynamics and cultural values as potential moderators. The second study (Chapter 3) investigated daily and average concordance between parent and youth actigraphy-measured sleep and how this varied as a function of family context (e.g., parenting, family functioning). The third study (Chapter 4) examined concordance in actigraphy sleep among parent-youth and sibling dyads and explored how relations differed across zygosity type and sleeping arrangements. The dissertation concludes with an immersive discussion (Chapter 5) that summarizes the key differences, similarities, and takeaways across studies and highlights future directions and implications for developmental science, public policy, and clinical interventions. Collectively, this dissertation contributes to the understanding of youth and adolescent sleep within a family context by identifying proximal (e.g., daily interactions with parents/siblings) and broader family-level factors (e.g., dynamics, culture) that may help promote more healthful sleep among both adolescents and their family members.
ContributorsSasser, Jeri (Author) / Doane, Leah D (Thesis advisor) / Su, Jinni (Committee member) / Grimm, Kevin J (Committee member) / Lemery-Chalfant, Kathryn (Committee member) / Arizona State University (Publisher)
Created2023
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 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
Description
With the growing popularity of medical cannabis, and high rates of cannabis use disorder (CUD) among medical cannabis users, it is more important than ever to accurately identify the proximal antecedents and subjective effects of medical cannabis use. Subjective antecedents and effects have been proposed as key mechanisms underlying the transition from cannabis use to CUD, but little research has examined medical cannabis users’ experiences in real-time, real-world settings. The current study of 86 young-adult medical cannabis users ages 18-30 (32.6% female) used ecological momentary assessment (EMA) to characterize the antecedents and effects of medical cannabis use, and to examine whether these antecedents and effects vary as a function of CUD severity. Higher craving, pain, and withdrawal symptoms predicted greater odds of cannabis use at the next report, and lower subjective ‘high’ predicted greater odds of cannabis use at the next report. Use of medical cannabis was associated with increases in positive affect, stimulation, relaxation, and subjective ‘high’, decreases in negative affect, withdrawal symptoms, craving, and pain, and increases in cognitive problems, psychotic-like experiences, and adverse bodily effects. Further, following cannabis use, medical users with more CUD symptoms reported greater relief from craving, attenuated increases in stimulation and relaxation, and enhanced increases in sluggishness, cognitive problems, psychotic-like symptoms, and bodily symptoms. Results suggest that medical cannabis use, like recreational use, is associated with a wide range of subjective antecedents and effects, and that relief from cannabis craving may play an important role in the maintenance of CUD among medical users.
ContributorsJones, Connor (Author) / Meier, Madeline H (Thesis advisor) / Chassin, Laurie (Committee member) / Grimm, Kevin J (Committee member) / Corbin, William (Committee member) / Arizona State University (Publisher)
Created2022
Description
It has been theorized that cultural variation within the family shapes children’s self-regulatory competence, yet there is a dearth of research examining the relation between culture and self-regulation. Family orientation refers to the emphasis on providing support, respect, and obligation to the family system, and is important for children’s functioning, yet existing literature on related constructs relies on parent-reported measures. Additionally, quantitative genetic research has neglected the role of culture in the genetic and environmental contributions on children’s self-regulation. There were three main aims of this study: 1) to propose novel coding schemes and factor analytic approaches to capture family orientation, 2) to examine the relation between family orientation and self-regulation in middle childhood, and 3) to examine whether family orientation moderates the genetic and environmental influences on self-regulation in middle childhood. The sample was drawn from the Arizona Twin Project (N=710) where children (49.1% female, 55.6% White, 28.3% Hispanic/Latino) were assessed at approximately eight years of age (Mage = 8.38 years, SD = 0.66). Family orientation values were indexed by parent-reported familism, whereas family orientation behaviors comprised coded measures of children’s family orientation and experimenter ratings of caregiver and child behavior. Outcome measures of self-regulation included the Continuous Performance Task, Flanker Task, Digit Span Backward, and parent- and teacher-reported effortful control (Temperament in Middle Childhood Questionnaire). Higher family orientation behaviors predicted positively predicted children’s self-regulation, with the exception of Digit Span Backward performance, and associations were not moderated by child sex, family SES, or race/ethnicity. Twin models revealed that differences in family orientation behaviors could be attributed to genetic, shared, and nonshared environmental influences, and additive genetic and nonshared environmental influences explained the variation across measures of self-regulation. Finally, there was no evidence that family orientation values nor behaviors moderated the genetic or environmental influences on children’s self-regulation. This study highlights the complex nature of cultural variation within the family and its importance for children’s self-regulatory abilities.
ContributorsRea-Sandin, Gianna (Author) / Lemery-Chalfant, Kathryn (Thesis advisor) / Doane, Leah D (Committee member) / Causadias, Jose (Committee member) / Grimm, Kevin J (Committee member) / Arizona State University (Publisher)
Created2022
Description
The hypothalamic pituitary adrenal (HPA) axis is a primary neuroendocrine system posited to mediate the associations between early life stress and long-term deleterious psychological and physical health outcomes. The effects of early life adversity on HPA axis functioning have been well-documented in primarily White samples, with statistical advances allowing researchers to isolate latent trait cortisol as a stable indicator of HPA axis functioning to account for day-to-day influences on diurnal cortisol patterns. However, directional associations have been mixed depending on developmental stage, demographic composition, and methodological differences across studies. The few studies of early adversity and HPA axis functioning in Hispanic/Latino/a/x samples demonstrate complex interactions between cultural processes and adversity in predicting HPA axis output. Further, nascent literature has isolated the cognitive, meaning-making, and prosocial skills involved in ethnic racial identity (ERI) and its subconstructs of exploration, resolution, and affirmation as promotive during the adolescent stage of development in Latinx youth. Such skills might better prepare youth for neurobiological stress regulation after adversity. To my knowledge, no study has examined whether ERI plays a protective role against the effects of early adversity on trait-level indicators of the HPA axis during adolescence, despite the particularly high rates of cumulative exposure to early life adversity in Latinx youth as compared to White counterparts. Guided by adaptive cultural resilience theories, this study of 197 socioeconomically diverse Latinx older-adolescents aimed to leverage recent findings of stable trait indicators of cortisol output to 1) identify consistent directional markers of the effects of early life adversity on latent trait cortisol in a Latinx sample and 2) elucidate the degree to which ERI might act as a promotive feature for HPA axis levels and protective factor against cumulative early life adversity. Confirmatory factor analyses identified a theory-driven model as an adequate measure of latent trait cortisol. Greater exposure to early adversity predicted lower latent trait cortisol, but ERI demonstrated neither protective nor promotive effects. The present study reifies that early adversity exposure has deleterious effects on trait-level HPA axis functioning, but identifying sources of cultural resilience among Latinx youth remains critical for the future of health equity.
ContributorsGusman, Michaela S. (Author) / Doane, Leah D (Thesis advisor) / Causadias, José M (Committee member) / Grimm, Kevin J (Committee member) / Wolchik, Sharlene A (Committee member) / Arizona State University (Publisher)
Created2022
Description
Latent profile analysis (LPA), a type of finite mixture model, has grown in popularity due to its ability to detect latent classes or unobserved subgroups within a sample. Though numerous methods exist to determine the correct number of classes, past research has repeatedly demonstrated that no one method is consistently the best as each tends to struggle under specific conditions. Recently, the likelihood incremental percentage per parameter (LI3P), a method using a new approach, was proposed and tested which yielded promising initial results. To evaluate this new method more thoroughly, this study simulated 50,000 datasets, manipulating factors such as sample size, class distance, number of items, and number of classes. After evaluating the performance of the LI3P on simulated data, the LI3P is applied to LPA models fit to an empirical dataset to illustrate the method’s application. Results indicate the LI3P performs in line with standard class enumeration techniques, and primarily reflects class separation and the number of classes.
ContributorsHoupt, Russell Paul (Author) / Grimm, Kevin J (Thesis advisor) / McNeish, Daniel (Committee member) / Edwards, Michael C (Committee member) / Arizona State University (Publisher)
Created2022
Description
Chronic low-grade inflammation is a main pathogenic link between obesity and Type 2 Diabetes (T2D) and a putative target for treatment. While a wide array of pharmacologic agents is available to manage T2D, many patients still face perturbed glycemia and subclinical inflammation. Therefore, complementary nutraceutical strategies that target inflammation, metabolism, and resolution physiology hold promise as adjunctive options to quell the disturbed immuno-metabolic milieu observed in T2D. Omega-3 polyunsaturated fatty acids (PUFAs) and anthocyanins are two dietary components evidenced to mitigate inflammation and improve T2D risk factors, through distinct and similar targets. However, the combined use of such nutraceuticals has not yet been examined in individuals with T2D. This dissertation leveraged data from a larger randomized, double-blind, placebo-controlled trial conducted between January 2022—September 2023 investigating the use of combined supplementation (active treatment; [FOM]) of anthocyanins (600 mg/d maqui berry extract) and omega-3 PUFAs (3 g/day fish oil; 2 g/d EPA, 1 g/d DHA) for 8 weeks on cytokines and mental acuity in individuals with T2D, compared to a placebo (CON). The current study examined the effects of this supplemental strategy on markers of metabolic inflammation, oxidative stress, and cardiometabolic risk. The results indicated that a marker of sustained omega-3 dietary intake and tissue accumulation termed the Omega-3 Index was inversely associated with HbA1c (? = -8.5, 95%CI -15.1, -1.4, p = 0.022) and glucose (? = -12.4, 95%CI -22.9, -0.5, p = 0.042), after adjustment for covariates at baseline across all participants with T2D in this study. However, outcomes from linear mixed model analyses demonstrated that there were no significant differences in change from baseline between FOM and CON groups at week 8 in any of the inflammatory, oxidative stress, glycemic control, or circulating lipid markers assessed in this study. These null effects were observed despite a 93% greater increase from baseline in the Omega-3 Index observed in the FOM group compared to the CON group at week 8. Therefore, the findings do not support significant treatment effects associated with 2 months of combined marine omega-3 PUFAs and maqui berry extract on inflammatory and cardiometabolic outcomes in individuals with T2D.
ContributorsFessler, Samantha Nicole (Author) / Johnston, Carol S (Thesis advisor) / Sweazea, Karen (Committee member) / Wang, Shu (Committee member) / Kavouras, Stavros A (Committee member) / Grimm, Kevin J (Committee member) / Arizona State University (Publisher)
Created2024
Description
Decision trees is a machine learning technique that searches the predictor space for the variable and observed value that leads to the best prediction when the data are split into two nodes based on the variable and splitting value. Conditional Inference Trees (CTREEs) is a non-parametric class of decision trees that uses statistical theory in order to select variables for splitting. Missing data can be problematic in decision trees because of an inability to place an observation with a missing value into a node based on the chosen splitting variable. Moreover, missing data can alter the selection process because of its inability to place observations with missing values. Simple missing data approaches (e.g., deletion, majority rule, and surrogate split) have been implemented in decision tree algorithms; however, more sophisticated missing data techniques have not been thoroughly examined. In addition to these approaches, this dissertation proposed a modified multiple imputation approach to handling missing data in CTREEs. A simulation was conducted to compare this approach with simple missing data approaches as well as single imputation and a multiple imputation with prediction averaging. Results revealed that simple approaches (i.e., majority rule, treat missing as its own category, and listwise deletion) were effective in handling missing data in CTREEs. The modified multiple imputation approach did not perform very well against simple approaches in most conditions, but this approach did seem best suited for small sample sizes and extreme missingness situations.
ContributorsManapat, Danielle Marie (Author) / Grimm, Kevin J (Thesis advisor) / Edwards, Michael C (Thesis advisor) / McNeish, Daniel (Committee member) / Anderson, Samantha F (Committee member) / Arizona State University (Publisher)
Created2023