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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
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 past, it has been assumed that measurement and predictive invariance are consistent so that if one form of invariance holds the other form should also hold. However, some studies have proven that both forms of invariance only hold under certain conditions such as factorial invariance and invariance in the common factor variances. The present research examined Type I errors and the statistical power of a method that detects violations to the factorial invariant model in the presence of group differences in regression intercepts, under different sample sizes and different number of predictors (one or two). Data were simulated under two models: in model A only differences in the factor means were allowed, while model B violated invariance. A factorial invariant model was fitted to the data. Type I errors were defined as the proportion of samples in which the hypothesis of invariance was incorrectly rejected, and statistical power was defined as the proportion of samples in which the hypothesis of factorial invariance was correctly rejected. In the case of one predictor, the results show that the chi-square statistic has low power to detect violations to the model. Unexpected and systematic results were obtained regarding the negative unique variance in the predictor. It is proposed that negative unique variance in the predictor can be used as indication of measurement bias instead of the chi-square fit statistic with sample sizes of 500 or more. The results of the two predictor case show larger power. In both cases Type I errors were as expected. The implications of the results and some suggestions for increasing the power of the method are provided.
ContributorsAguilar, Margarita Olivera (Author) / Millsap, Roger E. (Thesis advisor) / Aiken, Leona S. (Committee member) / Enders, Craig K. (Committee member) / Arizona State University (Publisher)
Created2010
Description
Aging and the menopause transition are both intricately linked to cognitive changes
during mid-life and beyond. Clinical literature suggests the age at menopause onset can differentially impact cognitive status later in life. Yet, little is known about the relationship between behavioral and brain changes that occur during the transitional stage into the post-menopausal state. Much of the pre-clinical work evaluating an animal model of menopause involves ovariectomy in rodents; however, ovariectomy results in an abrupt loss of circulating hormones and ovarian tissue, limiting the ability to evaluate gradual follicular depletion. The 4-vinylcyclohexene diepoxide (VCD) model simulates transitional menopause in rodents by selectively depleting the immature ovarian follicle reserve and allowing animals to retain their follicle-deplete ovarian tissue, resulting in a profile similar to the majority of menopausal women. Here, Vehicle or VCD treatment was administered to ovary-intact adult and middle-aged Fischer-344 rats to assess the cognitive effects of transitional menopause via VCD-induced follicular depletion over time, as well as to understand potential interactions with age, with VCD treatment beginning at either six or twelve months of age. Results indicated that subjects that experience menopause onset at a younger age had impaired spatial working memory early in the transition to a follicle-deplete state. Moreover, in the mid- and post- menopause time points, VCD-induced follicular depletion amplified an age effect, whereby Middle-Aged VCD-treated animals had poorer spatial working and reference memory performance than Young VCD-treated animals. Correlations suggested that in middle age, animals with higher circulating estrogen levels tended to perform better on spatial memory tasks. Overall, these findings suggest that the age at menopause onset is a critical parameter to consider when evaluating learning and memory across the transition to reproductive senescence. From a translational perspective, this study informs the field with respect to how the age at menopause onset might impact cognition in menopausal women, as well as provides insight into time points to explore for the window of opportunity for hormone therapy during the menopause transition to attenuate age- and menopause- related cognitive decline, and produce healthy brain aging profiles in women who retain their ovaries throughout the lifespan.
during mid-life and beyond. Clinical literature suggests the age at menopause onset can differentially impact cognitive status later in life. Yet, little is known about the relationship between behavioral and brain changes that occur during the transitional stage into the post-menopausal state. Much of the pre-clinical work evaluating an animal model of menopause involves ovariectomy in rodents; however, ovariectomy results in an abrupt loss of circulating hormones and ovarian tissue, limiting the ability to evaluate gradual follicular depletion. The 4-vinylcyclohexene diepoxide (VCD) model simulates transitional menopause in rodents by selectively depleting the immature ovarian follicle reserve and allowing animals to retain their follicle-deplete ovarian tissue, resulting in a profile similar to the majority of menopausal women. Here, Vehicle or VCD treatment was administered to ovary-intact adult and middle-aged Fischer-344 rats to assess the cognitive effects of transitional menopause via VCD-induced follicular depletion over time, as well as to understand potential interactions with age, with VCD treatment beginning at either six or twelve months of age. Results indicated that subjects that experience menopause onset at a younger age had impaired spatial working memory early in the transition to a follicle-deplete state. Moreover, in the mid- and post- menopause time points, VCD-induced follicular depletion amplified an age effect, whereby Middle-Aged VCD-treated animals had poorer spatial working and reference memory performance than Young VCD-treated animals. Correlations suggested that in middle age, animals with higher circulating estrogen levels tended to perform better on spatial memory tasks. Overall, these findings suggest that the age at menopause onset is a critical parameter to consider when evaluating learning and memory across the transition to reproductive senescence. From a translational perspective, this study informs the field with respect to how the age at menopause onset might impact cognition in menopausal women, as well as provides insight into time points to explore for the window of opportunity for hormone therapy during the menopause transition to attenuate age- and menopause- related cognitive decline, and produce healthy brain aging profiles in women who retain their ovaries throughout the lifespan.
ContributorsKoebele, Stephanie Victoria (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Aiken, Leona S. (Committee member) / Conrad, Cheryl D. (Committee member) / Wynne, Clive DL (Committee member) / Arizona State University (Publisher)
Created2015
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