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- Creators: Brahms, Johannes, 1833-1897
Description
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.
ContributorsYeung, Wan (Author) / Aiken, Leona S. (Thesis advisor) / Davis, Mary C. (Thesis advisor) / Mackinnon, David P (Committee member) / Zautra, Alex J (Committee member) / Arizona State University (Publisher)
Created2013
Description
Although the issue of factorial invariance has received increasing attention in the literature, the focus is typically on differences in factor structure across groups that are directly observed, such as those denoted by sex or ethnicity. While establishing factorial invariance across observed groups is a requisite step in making meaningful cross-group comparisons, failure to attend to possible sources of latent class heterogeneity in the form of class-based differences in factor structure has the potential to compromise conclusions with respect to observed groups and may result in misguided attempts at instrument development and theory refinement. The present studies examined the sensitivity of two widely used confirmatory factor analytic model fit indices, the chi-square test of model fit and RMSEA, to latent class differences in factor structure. Two primary questions were addressed. The first of these concerned the impact of latent class differences in factor loadings with respect to model fit in a single sample reflecting a mixture of classes. The second question concerned the impact of latent class differences in configural structure on tests of factorial invariance across observed groups. The results suggest that both indices are highly insensitive to class-based differences in factor loadings. Across sample size conditions, models with medium (0.2) sized loading differences were rejected by the chi-square test of model fit at rates just slightly higher than the nominal .05 rate of rejection that would be expected under a true null hypothesis. While rates of rejection increased somewhat when the magnitude of loading difference increased, even the largest sample size with equal class representation and the most extreme violations of loading invariance only had rejection rates of approximately 60%. RMSEA was also insensitive to class-based differences in factor loadings, with mean values across conditions suggesting a degree of fit that would generally be regarded as exceptionally good in practice. In contrast, both indices were sensitive to class-based differences in configural structure in the context of a multiple group analysis in which each observed group was a mixture of classes. However, preliminary evidence suggests that this sensitivity may contingent on the form of the cross-group model misspecification.
ContributorsBlackwell, Kimberly Carol (Author) / Millsap, Roger E (Thesis advisor) / Aiken, Leona S. (Committee member) / Enders, Craig K. (Committee member) / Mackinnon, David P (Committee member) / Arizona State University (Publisher)
Created2011
Description
In the present research, two interventions were developed to increase sun protection in young women. The purpose of the study was to compare the effects of intervention content eliciting strong emotional responses to visual images depicting photoaging and skin cancer, specifically fear and disgust, coupled with a message of self-efficacy and benefits of sun protection (the F intervention) with an intervention that did not contain an emotional arousal component (the E intervention). Further, these two intervention conditions were compared to a control condition that contained an emotional arousal component that elicited emotion unrelated to the threat of skin cancer or photoaging (the C control condition). A longitudinal study design was employed, to examine the effects of condition immediately following the intervention, and to examine sun protection behavior 2 weeks after the intervention. A total of 352 undergraduate women at Arizona State University were randomly assigned to one of the three conditions (F n = 148, E n = 73, C n = 131). Several psychosocial constructs, including benefits of sun protection, susceptibility to and severity of photoaging and sun exposure, self-efficacy beliefs of making sun protection a daily habit, and barriers to sun protection were measured before and immediately following the intervention. Sun protection behavior was measured two weeks later. Those in the full intervention reported higher self-efficacy and severity of photoaging at immediate posttest than those in the efficacy only and control conditions. The fit of several path models was tested to explore underlying mechanisms by which the intervention affected sun protection behavior. Experienced emotion, specifically fear and disgust, predicted susceptibility and severity, which in turn predicted anticipated regret of failing to use sun protection. The relationship between this overall threat component (experienced emotion, susceptibility, severity, and anticipated regret) and intentions to engage in sun protection behavior was mediated by benefits. The present research provided evidence of the effectiveness of threat specific emotional arousal coupled with a self-efficacy and benefits message in interventions to increase sun protection. Further, this research provided additional support for the inclusion of both experienced and anticipated emotion in models of health behavior.
ContributorsMoser, Stephanie E (Author) / Aiken, Leona S. (Thesis advisor) / Shiota, Michelle N. (Committee member) / Kwan, Sau (Committee member) / Castro, Felipe (Committee member) / Arizona State University (Publisher)
Created2011
Description
Coarsely grouped counts or frequencies are commonly used in the behavioral sciences. Grouped count and grouped frequency (GCGF) that are used as outcome variables often violate the assumptions of linear regression as well as models designed for categorical outcomes; there is no analytic model that is designed specifically to accommodate GCGF outcomes. The purpose of this dissertation was to compare the statistical performance of four regression models (linear regression, Poisson regression, ordinal logistic regression, and beta regression) that can be used when the outcome is a GCGF variable. A simulation study was used to determine the power, type I error, and confidence interval (CI) coverage rates for these models under different conditions. Mean structure, variance structure, effect size, continuous or binary predictor, and sample size were included in the factorial design. Mean structures reflected either a linear relationship or an exponential relationship between the predictor and the outcome. Variance structures reflected homoscedastic (as in linear regression), heteroscedastic (monotonically increasing) or heteroscedastic (increasing then decreasing) variance. Small to medium, large, and very large effect sizes were examined. Sample sizes were 100, 200, 500, and 1000. Results of the simulation study showed that ordinal logistic regression produced type I error, statistical power, and CI coverage rates that were consistently within acceptable limits. Linear regression produced type I error and statistical power that were within acceptable limits, but CI coverage was too low for several conditions important to the analysis of counts and frequencies. Poisson regression and beta regression displayed inflated type I error, low statistical power, and low CI coverage rates for nearly all conditions. All models produced unbiased estimates of the regression coefficient. Based on the statistical performance of the four models, ordinal logistic regression seems to be the preferred method for analyzing GCGF outcomes. Linear regression also performed well, but CI coverage was too low for conditions with an exponential mean structure and/or heteroscedastic variance. Some aspects of model prediction, such as model fit, were not assessed here; more research is necessary to determine which statistical model best captures the unique properties of GCGF outcomes.
ContributorsCoxe, Stefany (Author) / Aiken, Leona S. (Thesis advisor) / West, Stephen G. (Thesis advisor) / Mackinnon, David P (Committee member) / Reiser, Mark R. (Committee member) / Arizona State University (Publisher)
Created2012
ContributorsBrahms, Johannes, 1833-1897 (Composer)
ContributorsBrahms, Johannes, 1833-1897 (Composer)
ContributorsBrahms, Johannes, 1833-1897 (Composer)
ContributorsBrahms, Johannes, 1833-1897 (Composer)
Description
Female infertility can present a significant challenge to quality of life. To date, few, if any investigations have explored the process by which women adapt to premature ovarian insufficiency (POI), a specific type of infertility, over time. The current investigation proposed a bi-dimensional, multi-factor, model of adjustment characterized by the identification of six latent factors representing personal attributes (resilience resources and vulnerability), coping (adaptive and maladaptive) and outcomes (distress and wellbeing). Measures were collected over the period of one year; personal attributes were assessed at Time 1, coping at Time 2 and outcomes at Time 3. It was hypothesized that coping factors would mediate associations between personal attributes and outcomes. Confirmatory Factor Analysis (CFA), simple regressions and single mediator models were utilized to test study hypotheses. Overall, with the exception of coping, the factor structure was consistent with predictions. Two empirically derived coping factors, and a single standalone strategy, avoidance, emerged. The first factor, labeled "approach coping" was comprised of strategies directly addressing the experience of infertility. The second was comprised of strategies indicative of "letting go /moving on." Only avoidance significantly mediated the association between vulnerability and distress.
ContributorsDriscoll, Mary (Author) / Davis, Mary C. (Thesis advisor) / Aiken, Leona S. (Committee member) / Luecken, Linda J. (Committee member) / Zautra, Alex J. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Researchers are often interested in estimating interactions in multilevel models, but many researchers assume that the same procedures and interpretations for interactions in single-level models apply to multilevel models. However, estimating interactions in multilevel models is much more complex than in single-level models. Because uncentered (RAS) or grand mean centered (CGM) level-1 predictors in two-level models contain two sources of variability (i.e., within-cluster variability and between-cluster variability), interactions involving RAS or CGM level-1 predictors also contain more than one source of variability. In this Master’s thesis, I use simulations to demonstrate that ignoring the four sources of variability in a total level-1 interaction effect can lead to erroneous conclusions. I explain how to parse a total level-1 interaction effect into four specific interaction effects, derive equivalencies between CGM and centering within context (CWC) for this model, and describe how the interpretations of the fixed effects change under CGM and CWC. Finally, I provide an empirical example using diary data collected from working adults with chronic pain.
ContributorsMazza, Gina L (Author) / Enders, Craig K. (Thesis advisor) / Aiken, Leona S. (Thesis advisor) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2015