Disordered Weight Control Behaviors in a Longitudinal Sample of Adolescents and Emerging Adults: An Intersectional and Transdiagnostic Examination

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Description
Disordered weight control behaviors (DWCB) are a pervasive and serious public health issue associated with a wide variety of psychological and physiological problems. Using the transdiagnostic cognitive behavioral model and an intersectional framework, this study uses latent class analysis to…

Disordered weight control behaviors (DWCB) are a pervasive and serious public health issue associated with a wide variety of psychological and physiological problems. Using the transdiagnostic cognitive behavioral model and an intersectional framework, this study uses latent class analysis to examine DWCB in a national longitudinal sample (N = 2,874) of late adolescents and emerging adults (19-22 years) with focus on gender and race/ethnicity. Three latent classes were identified cross-sectionally across all timepoints: A restriction behaviors group, a combined restriction and compensatory behaviors group, and a group exhibiting low DWCB. Women of all racial/ethnic groups were consistently more likely than were men to classify in the restriction behaviors class, and Black and Hispanic women were more likely to classify in the combined behaviors class in waves 6 and 7. Longitudinally, two classes were identified: A low stable and a higher stable class. Women of all racial/ethnic groups were more likely to classify in the high stable class compared with White men, however, no other racial/ethnic differences emerged. Hispanic men were more likely to classify in the high stable group. This study highlights the utility of transdiagnostic, intersectional, cross-sectional, and longitudinal approaches to studying DWCB in nonclinical populations. More work is needed to examine the influence of restriction and combined DWCB behaviors on adolescent and emerging adult development and functioning. In addition, this work underlines the need for more nuanced measurement of disordered eating pathology in national studies and epidemiological research. Finally, this study demonstrates the need for continual focus on intersectionality frameworks and the addition of cultural and identity-related variables in disordered eating research to promote wellbeing, health, and equity for all individuals.
Date Created
2023
Agent

Advances in Directional Goodness-of-fit Testing of Binary Data under Model Misspecification in Case of Sparseness

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Description
Goodness-of-fit test is a hypothesis test used to test whether a given model fit the data well. It is extremely difficult to find a universal goodness-of-fit test that can test all types of statistical models. Moreover, traditional Pearson’s chi-square goodness-of-fit…

Goodness-of-fit test is a hypothesis test used to test whether a given model fit the data well. It is extremely difficult to find a universal goodness-of-fit test that can test all types of statistical models. Moreover, traditional Pearson’s chi-square goodness-of-fit test is sometimes considered to be an omnibus test but not a directional test so it is hard to find the source of poor fit when the null hypothesis is rejected and it will lose its validity and effectiveness in some of the special conditions. Sparseness is such an abnormal condition. One effective way to overcome the adverse effects of sparseness is to use limited-information statistics. In this dissertation, two topics about constructing and using limited-information statistics to overcome sparseness for binary data will be included. In the first topic, the theoretical framework of pairwise concordance and the transformation matrix which is used to extract the corresponding marginals and their generalizations are provided. Then a series of new chi-square test statistics and corresponding orthogonal components are proposed, which are used to detect the model misspecification for longitudinal binary data. One of the important conclusions is, the test statistic $X^2_{2c}$ can be taken as an extension of $X^2_{[2]}$, the second-order marginals of traditional Pearson’s chi-square statistic. In the second topic, the research interest is to investigate the effect caused by different intercept patterns when using Lagrange multiplier (LM) test to find the source of misfit for two items in 2-PL IRT model. Several other directional chi-square test statistics are taken into comparison. The simulation results showed that the intercept pattern does affect the performance of goodness-of-fit test, especially the power to find the source of misfit if the source of misfit does exist. More specifically, the power is directly affected by the `intercept distance' between two misfit variables. Another discovery is, the LM test statistic has the best balance between the accurate Type I error rates and high empirical power, which indicates the LM test is a robust test.
Date Created
2022
Agent

Between- and Within-Family Predictors of Educational Attainment

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Description

Adolescence is an important period of scaffolding for educational attainment, which is among the strongest predictors of outcomes in multiple domains. Parents who encourage academic success and promote self-regulation may enhance their offspring’s educational attainment. However, parents with externalizing disorders…

Adolescence is an important period of scaffolding for educational attainment, which is among the strongest predictors of outcomes in multiple domains. Parents who encourage academic success and promote self-regulation may enhance their offspring’s educational attainment. However, parents with externalizing disorders present a complex constellation of risk factors, including low educational attainment and poor parenting, and are more likely to have children with high levels of disinhibition. Previous research has identified low parental education, poor parenting and adolescent impulsivity as threats to educational attainment, but has not examined risk factors for discrepancies in educational attainment among siblings of the same family. Furthermore, studies have not examined the between- and within-family mechanisms that may explain why adolescents with externalizing parents have low educational attainment. The current study addressed these gaps by testing between- and within-family predictors of educational attainment using data from a longitudinal, multigenerational study that oversampled families at risk for alcohol use disorder. The sample consisted of 555 biological siblings within 240 families. We tested whether parental externalizing predicted lower educational attainment through parents’ own lower education, parents’ differential treatment of offspring, and impulsivity. Results suggested that between families, parents with externalizing disorders had lower educational attainment and more impulsive offspring, but did not exhibit increased differential parenting. Within families, siblings with greater impulsivity had lower educational attainment, whereas receiving more preferential maternal treatment than one’s siblings predicted higher educational attainment. Low parental educational attainment mediated the relation between parental externalizing disorders and low offspring educational attainment.

Date Created
2021-12
Agent

Evaluating Social Intelligence Training: Personality as a Predictor

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Description

With the emergence of programs that focus on socio-emotional regulation through online intervention, our focus is to move beyond the current literature to look at how personality might help to identify those in need of such an intervention, while also…

With the emergence of programs that focus on socio-emotional regulation through online intervention, our focus is to move beyond the current literature to look at how personality might help to identify those in need of such an intervention, while also assessing if personality may moderate the overall efficacy of the treatment in middle-aged adults. In particular, our focus is on the established improvements that similar programs have shown to have on positive affect (PA), negative affect (NA), and emotional reactivity (ER). Through a randomized controlled trial, this research examines whether an online social intelligence training (SIT) program improves socio-emotional regulation compared to an attention-control (AC) condition. During the pre- and post-test phases of the study, participants (N = 230) completed a questionnaire, along with online surveys for 14-days that included measures of social connectedness, emotional awareness, and perspective-taking. Our analysis, while lacking significant findings in the way of PA and NA, shed light on how SIT programs can improve ER, while personality can simultaneously predict baseline levels of ER and moderate the efficacy of the program.

Date Created
2021-12
Agent

Predictive Utility of a Proficiency Cut Score in a Benchmark Assessment

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Description
Since the No Child Left Behind (NCLB) Act required classifications of students’ performance levels, test scores have been used to measure students’ achievement; in particular, test scores are used to determine whether students reach a proficiency level in the state…

Since the No Child Left Behind (NCLB) Act required classifications of students’ performance levels, test scores have been used to measure students’ achievement; in particular, test scores are used to determine whether students reach a proficiency level in the state assessment. Accordingly, school districts have started using benchmark assessments to complement the state assessment. Unlike state assessments administered at the end of the school year, benchmark assessments, administered multiple times during the school year, measures students’ learning progress toward reaching the proficiency level. Thus, the results of the benchmark assessments can help districts and schools prepare their students for the subsequent state assessments so that their students can reach the proficiency level in the state assessment. If benchmark assessments can predict students’ future performance measured in the state assessments accurately, the assessments can be more useful to facilitate classroom instructions to support students’ improvements. Thus, this study focuses on the predictive accuracy of a proficiency cut score in the benchmark assessment. Specifically, using an econometric research technique, Regression Discontinuity Design, this study assesses whether reaching a proficiency level in the benchmark assessment had a causal impact on increasing the probability of reaching a proficiency level in the state assessment. Finding no causal impact of the cut score, this study alternatively applies a Precision-Recall curve - a useful measure for evaluating predictive performance of binary classification. By using this technique, this study calculates an optimal proficiency cut score in the benchmark assessment that maximizes the accuracy and minimizes the inaccuracy in predicting the proficiency level in the state assessment. Based on the results, this study discusses issues regarding the conventional approaches of establishing cut scores in large-scale assessments and suggests some potential approaches to increase the predictive accuracy of the cut score in benchmark assessments.
Date Created
2021
Agent

Re-Conceptualizing Genetic Influence in GxE Studies: Does Inherited Sensitivity to Environmental Influence Moderate the Indirect Effect of Parent Knowledge on Future Drinking?

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Description
Excessive drinking in adolescence is a public health issue with major consequences on both an individual and societal level. Elucidating genetic and environmental influences could be particularly informative for prevention efforts. One potential source of genetic influence is sensitivity to…

Excessive drinking in adolescence is a public health issue with major consequences on both an individual and societal level. Elucidating genetic and environmental influences could be particularly informative for prevention efforts. One potential source of genetic influence is sensitivity to environmental influences. It was hypothesized that parent knowledge would interact with genetic sensitivity to the environment to indirectly reduce risk for alcohol problems through less adolescent rule breaking behavior. Participants (N=316) provided genetic data and reported their rule breaking behavior and past year frequency of heavy drinking, and participants’ custodial parents reported their perceived knowledge of their child’s activities. A novel index of genetic sensitivity to environmental influence was created using published methylation quantitative trait locus data from the frontal lobe. Study hypotheses were mostly not supported. The study results likely reflect the poor distribution of study variables and the limitations of the current study’s sensitivity gene score. The current study underscored the importance of adhering to methodological rigor and explored alternate conceptualizations and methods that future research could use to elucidate the role of inherited to sensitivity to environmental influences in adolescent drinking.
Date Created
2020
Agent

Functional impairment, mental disorder symptomatology, and perceived bias among racial and ethnic minorities in the United States

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Description
Mental health disparities in the U.S. among racial and ethnic minorities are a serious public health issue associated with substantial ethical and economic costs as well as negative health outcomes. Compared with Whites, racial/ethnic minorities have been found to have…

Mental health disparities in the U.S. among racial and ethnic minorities are a serious public health issue associated with substantial ethical and economic costs as well as negative health outcomes. Compared with Whites, racial/ethnic minorities have been found to have greater mental disorder symptomatology, however, very little research exists on how this impacts functional outcomes and quality of life. Additionally, research addressing the impact of bias on symptomatology and functional outcomes, especially across racial/ethnic groups, is lacking. Using the International Classification of Functioning, Disability, and Health (ICF) Biopsychosocial Model of Disability as a conceptual framework, the current study aims to address the relationship between mental disorder symptomatology and functional impairment across racial/ethnic groups, as well as evaluate the influence of perceived bias on this association. These relationships were examined using data from the Collaborative Psychiatric Epidemiological Surveys (CPES) among White, Black, Latinx, and Asian American individuals (N = 10,276). Variables include past-30-day functional impairment, past-year mental disorder symptomatology, and lifetime perceived bias. One-way analyses of variance were conducted to compare mental disorder symptomatology and perceived bias across racial/ethnic groups. Pearson correlation analyses were conducted to assess the relationship between mental disorder symptomatology and functional impairment across racial/ethnic groups. Zero-inflated negative binomial regressions were conducted to evaluate the moderating effect of perceived bias on the relationship between mental disorder symptomatology and functional impairment across racial/ethnic groups. Additional exploratory analyses were conducted to assess the relationships between mental disorder symptomatology, perceived bias, and various domains of functional impairment across racial/ethnic groups. Findings speak to the need for additional research on predictors and correlates of mental health outcomes, such as social support, community, and other resiliency factors. Additionally, the need for broader conceptualizations of how bias, prejudice, stigma, and intersectional identity may impact health and wellbeing across diverse populations is illustrated in this work. Overall, findings indicate the continued existence of disparities in mental health across racial/ethnic groups and reify the need for additional work to address this public health problem.
Date Created
2019
Agent

Addressing the Variable Selection Bias and Local Optimum Limitations of Longitudinal Recursive Partitioning with Time-Efficient Approximations

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Description
Longitudinal recursive partitioning (LRP) is a tree-based method for longitudinal data. It takes a sample of individuals that were each measured repeatedly across time, and it splits them based on a set of covariates such that individuals with similar trajectories…

Longitudinal recursive partitioning (LRP) is a tree-based method for longitudinal data. It takes a sample of individuals that were each measured repeatedly across time, and it splits them based on a set of covariates such that individuals with similar trajectories become grouped together into nodes. LRP does this by fitting a mixed-effects model to each node every time that it becomes partitioned and extracting the deviance, which is the measure of node purity. LRP is implemented using the classification and regression tree algorithm, which suffers from a variable selection bias and does not guarantee reaching a global optimum. Additionally, fitting mixed-effects models to each potential split only to extract the deviance and discard the rest of the information is a computationally intensive procedure. Therefore, in this dissertation, I address the high computational demand, variable selection bias, and local optimum solution. I propose three approximation methods that reduce the computational demand of LRP, and at the same time, allow for a straightforward extension to recursive partitioning algorithms that do not have a variable selection bias and can reach the global optimum solution. In the three proposed approximations, a mixed-effects model is fit to the full data, and the growth curve coefficients for each individual are extracted. Then, (1) a principal component analysis is fit to the set of coefficients and the principal component score is extracted for each individual, (2) a one-factor model is fit to the coefficients and the factor score is extracted, or (3) the coefficients are summed. The three methods result in each individual having a single score that represents the growth curve trajectory. Therefore, now that the outcome is a single score for each individual, any tree-based method may be used for partitioning the data and group the individuals together. Once the individuals are assigned to their final nodes, a mixed-effects model is fit to each terminal node with the individuals belonging to it.

I conduct a simulation study, where I show that the approximation methods achieve the goals proposed while maintaining a similar level of out-of-sample prediction accuracy as LRP. I then illustrate and compare the methods using an applied data.
Date Created
2019
Agent

Examining variability in identity, resilience, and college adjustment among multiracial Hispanic/Latinx and White college students

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Description
Over 35% of multiracial college students fail to earn a degree, which can have significant economic and health costs over their lifespan. This study aimed to better understand college and psychological adjustment among multiracial college students of Hispanic/Latinx and White…

Over 35% of multiracial college students fail to earn a degree, which can have significant economic and health costs over their lifespan. This study aimed to better understand college and psychological adjustment among multiracial college students of Hispanic/Latinx and White non-Hispanic descent by examining students’ racial identities and use of resilience resources. Latent profiles of identity were identified to better understand how different aspects of racial identity are clustered in this population. Multiracial college students (N=221) reported on racial identity as measured on multiple dimensions: Hispanic/Latinx identity, Hispanic/Latinx cultural orientation, White identity, identity integration, shifting expressions of identity, and identity malleability. Students also reported on their use of multiple resilience resources (personal mastery, social competence, perspective taking, coping flexibility, familism support values) and both college and psychological adjustment. Through regression and SEM analyses, results indicated that, of the resilience resources, only personal mastery was positively related to both college and psychological adjustment, while social competence was positively related to college adjustment. More shifting expressions of identity was related to poorer college and psychological adjustment, which was partially mediated via personal mastery. Stronger Hispanic/Latinx identity was related to higher perspective taking and coping flexibility, while stronger White identity was related to higher familism support values. Latent profiles of identity indicated a four-class solution, consisting of 1) “low identity”, 2) “integrated, low shifting”, 3) “integrated, shifting”, and 4) “high shifting, low integration”. Findings highlight the need for person-centered and ecological approaches to understanding identity development and resilience among multiracial college students, and can inform prevention and intervention efforts for multiracial college students of Hispanic/Latinx and White non-Hispanic descent. Results also demonstrate the importance of assessing multiracial identity via multiple dimensions including factors such as identity integration, shifting expressions of identity, and identity malleability.
Date Created
2020
Agent
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