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Differences in Anxiety Presentation Amongst Collegiate Athletes
Get PDFAnxiety affects millions of individuals, spanning from mild symptoms to life-halting disorders. The symptoms and experiences individuals face in terms of anxiety vary depending on their demographics, as well as living conditions. Athletes are affected by anxiety in different ways than typical non-athlete individuals. Athletes have an entirely different realm of life to consider when thinking about anxiety, and that is, their sporting, competitive life. This study analyzes the symptoms and characteristics of anxiety in college athletes differing by gender and sport type. The data collected through a survey of collegiate athletes at Bryant University will be used to determine the leading factors and symptoms of anxiety that athletes experience daily. The data collected will be categorized by gender, individual and team sports, as well as sport type. The analysis has shown a trend between female athletes and a high presence of anxiety, as well as a larger realm of symptoms and factors that females experience in comparison to males. Independent of any categorization other than gender, female athletes experience higher levels of anxiety in comparison to men. There are also trends that individual sport athletes experience different anxiety triggers in comparison to team sport athletes. This causes a difference in anxiety symptoms and factors each individual experiences depending on their gender, sport type, and individual characteristics. The study has shown that different sports experience different clusters of symptoms and factors. Conclusions can be drawn that female individuals on team collegiate sports experience higher frequencies of anxiety, and similar symptoms and factors in comparison to others
Information Literacy: How Students Search for & Verfiy Health-Related Information on Social Media
Get PDFToday, younger generations utilize social media to access what they perceive to be reliable and accurate information, yet there are some concerns regarding validity and the ease of which students share information. This thesis evaluates how undergraduate students search for and verify information seen on popular social media platforms and analyzes the proficiency of their information literacy skills. The data collected will be used in determining which social media platforms are most frequently used and trusted by students, which types of sources are used in verification of this information if verified at all, and their perception of information literacy. The data collected will be implemented for analysis in comparison to the previously created and studied Social Media Information Literacy Scale (Heiss et al., 2023) and the e-Health Impact Questionnaire (Kelly et al., 2015) to further evaluate how undergraduate students search for and verify health-related information on social media
How Does Contemporary Business Culture Contribute to Unethical Behavior Within the Finance Industry?
Get PDFThis thesis examines how contemporary business culture contributes to unethical behavior within the financial industry, specifically focusing on the role of leadership style, codes of conduct, competitive pressures, and regulatory environments in shaping ethical decision-making. A survey was administered to 60 participants, with 32 complete responses retained for analysis. The responses were used to examine trends across demographics and asses the relationship between the identified factors and unethical behavior. Multiple regression analysis evaluated how leadership style, competition, regulation, and codes of conduct impact unethical behavior scores. The results indicated that leadership style and regulatory environment were significantly associated with unethical behavior, while codes of conduct and competition had a limited to or no significant impact
The Price of Victory: A Machine Learning Analysis of How Salary Dispersion Influences Team Success in Major League Baseball
Get PDFThis paper examines the effect of salary dispersion on team success in Major League Baseball (MLB). Using data from 29 MLB teams over eight seasons (2012-2019), this study uses multiple models, such as Ordinary Least Squares (OLS), panel data regressions, and Random Forest machine learning, to investigate the degree – if any – that inequalities in a team\u27s payroll impacts success, measured by winning percentage. The study\u27s results show that, contrary to prevailing theories, salary dispersion – measured by a Gini coefficient – is not a significant predictor of a team\u27s winning percentage (team success). Instead, team performance metrics, such as Earned Run Average (ERA), Runs Scored, and Fielding Percentage, have consistently showed to be statistically significant predictors of team success. As the results indicate that a payroll with wage inequality does not necessarily negatively impact team success, the findings suggest that MLB teams should prioritize constructing a roster that optimizes performance metrics rather than optimizes equitable salary distribution. By applying both traditional economic models (OLS, panel data regressions) and machine learning techniques (Random Forest), this study adds to the comprehensive list of literature covering organizational efficiency and labor economics in professional sports
The Baby Animal Effect in Wildlife Conservation Advertising
No full textThis study examines how baby animal appeals influence wildlife conservation intentions and donation behavior. Participants shown a baby animal demonstrated more empathy and stronger conservation intentions than those shown an adult animal. Furthermore, promotion-focused participants responded with higher conservation intentions and donation amounts after viewing baby (vs. adult) animals, while prevention-focused participants showed no preference. By demonstrating how baby animal appeals interact with self-regulatory focus, these findings shed light on the boundary conditions of the baby animal effect and identify empathy as the key mechanism driving conservation behaviors
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