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The present study set out to examine whether negative goal-performance discrepancy (GPD) feedback for one task could have a negative effect on goal-setting associated with an unrelated, distinct task. A series of hierarchical regression analyses were conducted. Results show that large versus small negative GPD feedback on a creativity task impacted levels of specific self-efficacy for a stock-predicting task, which indicated a motivational spillover effect. However, large negative GPD on the creativity task was not evidenced to impact performance goals for the stock-predicting task, as hypothesized. Results also indicate that the larger the magnitude of negative GPD feedback, the more individuals experienced an increase in negative mood and decrease in positive mood, however mood was not evidenced to impact performance goals. / Master of Science

The attractiveness of the principalship is a variable that may help explain why candidates do and do not pursue principal positions. This study sought to determine if a discrepancy exists between what potential principal candidates desire and what they believe to be true about the attributes of the job of principal, and if that discrepancy can predict the attractiveness of the principalship to prospective candidates. A researcher-developed instrument was administered to teachers who are currently enrolled in four principal preparation programs in Virginia. Survey items were related to the domains that explain the attractiveness of the principalship. An overall attractiveness score was measured using a Thurstone Scale of Equal Appearing Intervals. A demographic section was included to collect background information. Overall, respondents rated the principalship as somewhat attractive. The regression found that there were five predictors of the attractiveness of the principalship. School location and number of years in education, both demographic factors, were the most significant predictors. Discrepancies in what candidates desired and believed to be provided regarding recognition of achievement, the ability to form relationships, and opportunities for professional growth followed as significant predictors of job attractiveness. / Ed. D.

Potential influences from using sexually explicit Internet material (SEIM) are controversial, however, the underlying psychological mechanism(s), which potentially can explain these found associations with SEIM consumption, have not been well studied. In the present research, I examine the relationship between SEIM consumption and subjective wellbeing (i.e., sexual and general wellbeing). In particular, I address the circumstances under which the consumption of SEIM is negative for wellbeing by assessing an ideal-actual sexual discrepancy in the context of intimate relationships. I drew on perspectives from self-discrepancy theory to explore whether SEIM consumption generates disparities between ideal and actual sexual experiences, which then may influence consumers’ sexual and general wellbeing. I expected this hypothesized ideal-actual sexual discrepancy to function as one of many underlying psychological mechanisms to explain SEIM’s negative impacts on various types of subjective sexual wellbeing (SSW). I also expected that via SSW, the discrepancy would also explain the ambiguous relationships between SEIM consumption and subjective general wellbeing (SGW) found in the past. That is, I predicted a serial mediation model with sexual self-discrepancy mediating the relationship between SEIM consumption and SSW, and SSW mediating the relationship between sexual self-discrepancy and SGW. Two studies together demonstrated the general progress from consuming SEIM to the evaluation of self-perceived wellbeing under the condition of evaluating sexual experiences with intimate partner(s). In Study 1, the data-driven gender specific sexual preference highlighted the need of model testing separately for men and women because of the potential difference in experiencing the negative impacts from consuming SEIM through the different progress of formation of ideal sex scripts influence by pornographic sex, and generation of an I-A sexual discrepancy in men and women. Results of Study 2 from male SEIM consumers further supported the hypothesized mediation role of I-A sexual discrepancy and SSW (i.e., sexual esteem and sexual satisfaction) in understanding the relationships between SEIM consumption and wellbeing. Overall, the present research illustrated the consumption of SEIM can shape one’s sexual preferences of pornographic sex and generate unrealistic expectations of pornographic sexual experiences with intimate partner(s). Hence, the experience of I-A sexual discrepancy from unachievable ideal sex is a key factor in identifying SEIM’s negative impacts on wellbeing. Moreover, parsimonious serial mediation paths through I-A sexual discrepancy and SSW also demonstrated the relationship between SEIM consumption, SSW, and SGW in one model. This finding indicates SSW works as an important indicator of ones’ SGW. The present research provides a theoretical explanation to understand the impact of consuming SEIM on wellbeing and implicates the importance exploring different types of sexual discrepancy associated with SEIM consumption and ways to mitigate the experienced I-A sexual discrepancy in intimate relationships.

Objective: To collect data regarding Canadian laypersons perceptions of smile esthetics and compare these data to US data in order to evaluate cultural differences. Methods: Using Adobe® Photoshop® 7, a digital image of a posed smile of a sexually ambiguous lower face was prepared so that hard and soft tissue could be manipulated to alter Buccal Corridor (BC), Gingival display (GD), Occlusal Cant (OC), Maxillary Midline to Face Discrepancy (MMFD) and Lateral Central Gingival Discrepancy (LCGD). Adult Canadian laypersons (n=103) completed an interactive computer-based survey of 29 randomized images to compare smile preferences for these variable. The custom survey was developed to display fluid, continuously appearing modifiable smile variables using MATLAB® R2008 for presentation. These data were compared to previously published data for US laypersons. Statistical inference was determined using Wilcoxon Rank Sum tests. Results: Canadian laypersons were more sensitive in detecting deviations from ideal and had a narrower range of acceptability thresholds for BC, GD, OC, MMFD and LCGD. Ideal esthetic values were significantly different only for BC. Conclusions: It appears cultural differences do exist related to smile characteristics. Clinically significant differences in the preference of the smile characteristics were found between Canadian and US laypersons. Canadian laypersons, on average, were more discriminating to deviations from ideal and had a narrower range of acceptability.

Objective: To collect data regarding Canadian laypersons perceptions of smile esthetics and compare these data to US data in order to evaluate cultural differences. Methods: Using Adobe® Photoshop® 7, a digital image of a posed smile of a sexually ambiguous lower face was prepared so that hard and soft tissue could be manipulated to alter Buccal Corridor (BC), Gingival display (GD), Occlusal Cant (OC), Maxillary Midline to Face Discrepancy (MMFD) and Lateral Central Gingival Discrepancy (LCGD). Adult Canadian laypersons (n=103) completed an interactive computer-based survey of 29 randomized images to compare smile preferences for these variable. The custom survey was developed to display fluid, continuously appearing modifiable smile variables using MATLAB® R2008 for presentation. These data were compared to previously published data for US laypersons. Statistical inference was determined using Wilcoxon Rank Sum tests. Results: Canadian laypersons were more sensitive in detecting deviations from ideal and had a narrower range of acceptability thresholds for BC, GD, OC, MMFD and LCGD. Ideal esthetic values were significantly different only for BC. Conclusions: It appears cultural differences do exist related to smile characteristics. Clinically significant differences in the preference of the smile characteristics were found between Canadian and US laypersons. Canadian laypersons, on average, were more discriminating to deviations from ideal and had a narrower range of acceptability.

The selection of a best-subset regression model from a candidate family is a common problem that arises in many analyses. In best-subset model selection, we consider all possible subsets of regressor variables; thus, numerous candidate models may need to be fit and compared. One of the main challenges of best-subset selection arises from the size of the candidate model family: specifically, the probability of selecting an inappropriate model generally increases as the size of the family increases. For this reason, it is usually difficult to select an optimal model when best-subset selection is attempted based on a moderate to large number of regressor variables. Model selection criteria are often constructed to estimate discrepancy measures used to assess the disparity between each fitted candidate model and the generating model. The Akaike information criterion (AIC) and the corrected AIC (AICc) are designed to estimate the expected Kullback-Leibler (K-L) discrepancy. For best-subset selection, both AIC and AICc are negatively biased, and the use of either criterion will lead to overfitted models. To correct for this bias, we introduce a criterion AICi, which has a penalty term evaluated from Monte Carlo simulation. A multistage model selection procedure AICaps, which utilizes AICi, is proposed for best-subset selection. In the framework of linear regression models, the Gauss discrepancy is another frequently applied measure of proximity between a fitted candidate model and the generating model. Mallows' conceptual predictive statistic (Cp) and the modified Cp (MCp) are designed to estimate the expected Gauss discrepancy. For best-subset selection, Cp and MCp exhibit negative estimation bias. To correct for this bias, we propose a criterion CPSi that again employs a penalty term evaluated from Monte Carlo simulation. We further devise a multistage procedure, CPSaps, which selectively utilizes CPSi. In this thesis, we consider best-subset selection in two different modeling frameworks: linear models and generalized linear models. Extensive simulation studies are compiled to compare the selection behavior of our methods and other traditional model selection criteria. We also apply our methods to a model selection problem in a study of bipolar disorder.