abstract: ABSTRACT The phenomenon of cyberbullying has captured the attention of educators and researchers alike as it has been associated with multiple aversive outcomes including suicide. Young people today have easy access to computer mediated communication (CMC) and frequently use it to harass one another -- a practice that many researchers have equated to cyberbullying. However, there is great disagreement among researchers whether intentional harmful actions carried out by way of CMC constitute cyberbullying, and some authors have argued that "cyber-aggression" is a more accurate term to describe this phenomenon. Disagreement in terms of cyberbullying's definition and methodological inconsistencies including choice of questionnaire items has resulted in highly variable results across cyberbullying studies. Researchers are in agreement however, that cyber and traditional forms of aggression are closely related phenomena, and have suggested that they may be extensions of one another. This research developed a comprehensive set of items to span cyber-aggression's content domain in order to 1) fully address all types of cyber-aggression, and 2) assess the interrelated nature of cyber and traditional aggression. These items were administered to 553 middle school students located in a central Illinois school district. Results from confirmatory factor analyses suggested that cyber-aggression is best conceptualized as integrated with traditional aggression, and that cyber and traditional aggression share two dimensions: direct-verbal and relational aggression. Additionally, results indicated that all forms of aggression are a function of general aggressive tendencies. This research identified two synthesized models combining cyber and traditional aggression into a shared framework that demonstrated excellent fit to the item data. / Dissertation/Thesis / Ph.D. Educational Psychology 2013

abstract: Fibromyalgia (FM) is a chronic pain condition characterized by debilitating fatigue. This study examined the dynamic relation between interpersonal enjoyment and fatigue in 102 partnered and 74 unpartnered women with FM. Participants provided three daily ratings for 21 days. They rated their fatigue in late morning and at the end of the day. Both partnered and unpartnered participants reported their interpersonal enjoyment in the combined familial, friendship, and work domains (COMBINED domain) in the afternoon. Additionally, partnered participants reported their interpersonal enjoyment in the spousal domain. The study was guided by three hypotheses at the within-person level, based on daily diaries: (1) elevated late morning fatigue would predict diminished afternoon interpersonal enjoyment; (2) diminished interpersonal enjoyment would predict elevated end-of-day fatigue; (3) interpersonal enjoyment would mediate the late morning to end-of-day fatigue relationship. In cross-level models, the study explored whether individual differences (between-person) in late morning fatigue and afternoon interpersonal enjoyment would moderate within-person relations from late morning fatigue to afternoon interpersonal enjoyment, and from afternoon interpersonal enjoyment to end-of-day fatigue. Furthermore, it explored whether the hypothesized relationships at the within-person level would also emerge at the between-person level (between-person mediation models). Multilevel structural equation modeling and multilevel modeling were employed for model testing, separately for partnered and unpartnered participants. Within-person mediation models supported that on high fatigue mornings, afternoon interpersonal enjoyment was dampened in the spousal and combined domains in partnered and unpartnered samples. Moreover, low afternoon interpersonal enjoyment in both the spousal and combined domains predicted elevated end-of-day fatigue. Afternoon interpersonal enjoyment mediated the relationship of late morning to end-of-day fatigue in the combined domain but in not the spousal domain. Cross-level moderation analyses showed that individual differences in afternoon spousal enjoyment moderated the day-to-day relation between afternoon spousal enjoyment and end-of-day fatigue. Finally, the mediational chain was not observed at the between-person level. These findings suggest that preserving interpersonal enjoyment in non-spousal relations limits within-day increases in FM fatigue. They highlight the importance of examining domain-specificity in interpersonal enjoyment when studying fatigue, and suggest that targeting enjoyment in social relations may improve the efficacy of existing treatments. / Dissertation/Thesis / Ph.D. Psychology 2013

abstract: 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. / Dissertation/Thesis / Ph.D. Psychology 2013

abstract: 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. / Dissertation/Thesis / Ph.D. Psychology 2013

With the advent of the Global War on Terror in 2001, more than 2 million troops have deployed in support of contingency operations throughout the world. During this time, the divorce rates have increased throughout the military, hitting an all-time high in 2011, and dropping slightly thereafter. Enlisted members on active duty in the United States Air Force exhibited a higher rate of divorce than did their counterparts in any other branch of military service. At present, the reasons for the heightened Air Force divorce rates are still unknown. Perhaps more importantly, research has not identified which specific subgroups within the Air Force stand at the highest risk of divorce. Current research has identified several factors that contribute to divorce in military personnel. These factors include career group, gender, race, and deployments. The purpose of this archival quantitative study, based on the stress hypothesis, was to describe, compare, analyze, and explore divorce status of the active duty enlisted corps of the U.S. Air Force in 2011 (N = 247,644), the year in which military divorce rates peaked. Research questions were answered using tables, bar graphs, and chi-square tests to explore associations among the variables. The study examined four independent variables, Air Force specialty, career group, gender, and race and found a statistically significant correlation between each of the independent variables and divorce rates. A weak association was found between deployments and divorce, with the greatest association found between gender and divorce. Among Air Force servicemembers, females were more than twice as likely to be divorced than males. This study may contribute to positive social change by reducing the rates of marital dissolution in the Air Force.

Extending prior alcohol expectancy measurement research, this researcher (McMurray, 2013) recently developed the Pharmacological and Social Alcohol Expectancy Scale (PSAES). The PSAES is the only alcohol expectancy measure to date that provides adequate coverage of both social expectancies and the anticipated positive pharmacological effects resulting from alcohol consumption, and was developed and validated in a sample of young adults (aged 18-23). Research has shown that adolescents at high risk for alcohol use disorder (AUD) hold higher expectations of reward from alcohol, suggesting that expectancy patterns may help distinguish at-risk youth. Building upon the previous PSAES validation study, the primary purpose of the current study was to examine whether a version of the PSAES adapted for adolescents (the PSAES-A) provided a valid measure of pharmacological and social alcohol expectancies in adolescents. Results demonstrated that a respecified model of the PSAES-A adequately fit the proposed two-dimensional factor structure and provided justification for the items representing two distinguishable domains: social and pharmacological. The PSAES-A was then used to 1) examine patterns of alcohol expectancies and drinking behaviors in adolescents and 2) investigate whether risk (e.g., sensation seeking personality) was differentially associated with pharmacological and social expectancies in adolescents. Results indicated that pharmacological and social expectancies were differentially associated with various drinking behaviors (e.g., quantity, frequency) and that sensation seeking was significantly associated with both social and pharmacological expectancies in adolescents. The fact that alcohol expectancies differentially predicted quantity and frequency of drinking suggests that different expectancy processes affect adolescent’s decisions about how often they drink versus how much alcohol they consume on a given occasion. Implications and limitations are discussed.

Prisoner recidivism is a problem of great social importance, as recidivism represents a failure of the rehabilitative goal of incarceration. The problem addressed in this study was the lack of accurate estimates of race as a predictor of recidivism risk in the United States, after taking demographics and criminal variables into account. Applying the life-course theory of recidivism, the purpose of this archival, epidemiological study was to calculate whether recidivism risk varied based on race, across different seriousness levels of commitment offense and number of prior arrests, among a sample of male federal prisoners released from custody. A Cox proportional hazards ratio was applied to determine both the statistical significance and the magnitude of being Black, rather than White, as a predictor of recidivism in six distinct scenarios. Analysis indicated that Black prisoners were more likely to recidivate in some instances, whereas White prisoners were more likely to recidivate in other instances. The results of the study can assist psychologists, parole boards, and other stakeholders in more accurately estimating the role of race in recidivism risk. The results of the study were that race is a significant risk factor in some kinds of recidivism, but not in others, and also that being African-American is not universally associated with higher recidivism risk. The results suggest that race might be a less prominent recidivism factor than previously thought.

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