Matthew Silveri is receiving Bachelor of Science in Psychology with a concentration in the clinical field. After graduation, Matt plans to find a job in an area that will allow him to apply the skills and knowledge that he acquired throughout his undergraduate education. Matt’s ultimate goal is to attain his doctorate of philosophy in Clinical Psychology with a focus on Neuropsychology, allowing him to conduct research, inspire others through education, and become a practicing clinician. He was the Vice President of his class in the 2006 school year, student representative on the judicial panel, orientation advisor, member of the psychology club, member of Psi Chi National Honor Society, and member of Delta Epsilon Sigma National Honor Society for Catholic Universities. Matt would like to thank every teacher that taught with passion and enthusiasm. It was these teachers that instilled in him a love for education and fervor for achievement. Matt would also like to express his gratitude for all the support and love his family offered throughout the last four years. Additionally, Matt would like to personally acknowledge Marywood University as a true hidden gem of private universities.
Director: Dr. Edward Crawley
Reader: Christina Elvidge
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The scientific study of prosocial behavior has led to a number of models designed to explain the helping process. The current studies examined one such model, the arousal: costreward model. The arousal: cost-reward model posits that a person chooses to help, after cognitively weighing several variables in a specific situation. The arousal: cost-reward model predicts that individuals will be most likely to help in a situation when the costs of helping are the lowest; conversely, individuals will be least likely to help when the costs of helping are the highest. Participants’ subjectively and objectively reported individual likeliness to help across several situations. Objective and subjective scores were analyzed with actual helping behavior. The results of the study provided further evidence that this model can successfully predict helping behavior.
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