Medicine and Health Sciences Commons^™

Mental Health And Online Learning - Systematic Review Dataset, Stephanie L. Moore Phd, George Veletsianos, Michael Barbour

University Libraries & Learning Sciences Faculty and Staff Publications

While there has been a lot of debate over the impact of online and remote learning on mental health and well-being, there has been no systematic syntheses or reviews of the research on this particular issue. In this paper, we review the research on the relationship between mental health / well-being and online or remote learning. Our review shows that little scholarship existed prior to 2020 with most studies conducted during the COVID-19 pandemic. We report four findings: (a) pandemic effects are not well-controlled for in most studies; (b) studies present a very mixed picture, with variability around how mental …

Dataset For Study: Reliability Of The Kiersma-Chen Empathy Scale In Health Sciences Students, David B. Gillette, Todd E. Davenport, J. Mark Vanness, Rupa Balachandran, Edward L. Rogan, Deepti Vyas, Suzanne M. Galal, Tracey Delnero, Paul Subar, Elisa Chavez

Physical Therapy Faculty & Staff Datasets

Background: Empathy is the ability to understand and identify with another person’s feelings and is important in student development.

Purpose: The purpose of this study was to assess reliability of the Kiersma-Chen Empathy Scale (KCES)[1] and its subscales in health professions students.

Methods: Students in six programs received two administrations. Surveys were matched and deidentified before analysis. Total and subscale homogeneity was assessed using Cronbach’s alpha. Association between subscale and total scores was assessed using Pearson correlation. Total and subscale reliability was determined using two-way intraclass correlation coefficients. Minimum detectable change (MDC₉₅)[2] was calculated.

Results: Two …

An Exploration In The Tools Of Options Pricing - Data, Ryan Hinson, Chris Schroeder

2021 Celebration of Student Scholarship - Oral Presentations

Stock options can be a useful tool in any investor’s portfolio. They allow the skilled investor to increase their leverage and possibility for a higher payout with less risk. However, they are only beneficial if the investor knows how to use them, and if they accurately reflect the price of the option. This presentation hopes to offer some insight into the binomial method of options pricing along with new adjustments to the model in hopes of reflecting a more accurate options price. This, along with the Monte Carlo simulation presented, will hopefully offer some insight into the mathematical investor’s toolbox.