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Past CUBE Projects

The projects detailed in each of the following sections are those completed by CUBE participants from past summers. While projects may change from year to year, read below to get a better idea of what you could be working on!

2023 CUBE Projects:

Project Team Member: Alicia Alvarez

Project Mentors: Alexandra HanlonAlicia LozanoJeff Stein

Study Aim: To examine the effects of specifying that rewards in a delay discounting task are certain on: 1) delay discounting, and 2) perceptions of certainty that the larger, delayed reward would be received.

Analytic Methods: Multiple linear regression modeling 

Project Team Member: Chloe Barnes

Project Mentors: Sarah RatcliffeGenevieve LyonsMatt Fritts

Study Aim: To investigate whether participation in contemplative practices outside the study activities was associated with changes in self-reported depressive symptoms

Analytic Methods: Hypothesis testing, Pearson's correlations

Project Team Member: David Henderson

Project Mentors: Monica Ahrens, Alex DiFeliceantonio,  Alexandra Hanlon

Study Aim: To examine whether persons with high cognitive restraint in relation to food are less likely to have successful flavor nutrient conditioning. 

Analytic Methods: Linear mixed effects modeling

Project Team Member: Nhu Thieu Makara Le

Project Mentors: Alexandra HanlonAlicia LozanoJeff Stein

Study Aim: To assess the mediating effect of delay discounting on the relationships between simulated scarcity with: 1) cigarette craving and 2) demand, and 3) positive/negative affect.

Analytic Methods: Mediation analyses using a Baron and Kenny approach

Project Team Member: Maggie Shideler

Project Mentors: Sarah Ratcliffe, Genevieve Lyons, Matt Fritts

Study Aim: To determine whether changes in mindfulness are associated with changes in wellbeing, and whether gender is or is not a mediating or moderating factor.

Analytic Methods: Stratified linear regression modeling, Moderation analyses

2022 CUBE Projects:

  • Project Team Members: Kinara Gasper, Kayla Williams
  • Project Mentors: Charlotte Baker, Alexandra Hanlon, Monica Ahrens, Alicia Lozano
  • Study Aim: To examine socio-demographic characteristics (race, sex, income, insurance plan, and age) associated with sports-related ACL injuries diagnosed in the Emergency Department (ED). 
  • Analytic Methods: Weighted supervised machine learning approach and weighted bivariate and multivariable logistic regression models
  • Project Team Member: Nhiya David
  • Project Mentors: Jennie Ma, Monica Ahrens, Alicia Lozano
  • Study Aim: To explore the antibody trajectories among dialysis patients after receiving the COVID-19 vaccine
  • Visual Analytics: Time series plots to observe patterns of humoral response decline using monthly immunoglobulin G (IgG) levels
  • Project Team Member: Jacqueline Morales
  • Project Mentors: Sarah Ratcliffe, Monica Ahrens, Alicia Lozano
  • Study Aim: To describe the experience of cancer pain from the perspective of patients and family caregivers using a Smart Health sensing system
  • Analytic Methods: Descriptive Statistics and CONSORT Diagram