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!
2024 CUBE Projects:
- Project Team Members: Maggie Brooks, Genevieve Brunner, Julia Neres
- Collaborative Project Mentor: Jeff Stein
- Biostatistics Mentors: Alicia Lozano, Muyao (Jenny) Lin, Alexandra Hanlon
- Study Aim: To understand the effects of nicotine strength (NS), price, and user type (exclusive cigarette vs. dual cigarette/e-cigarette) on behavioral economic demand of e-cigarettes in 85 smoking adults from the Roanoke area.
- Analytic Methods: Linear mixed effects modeling
- Project Team Member: Jackie Gregasavitch, Genevieve Jean-Pierre, Sarah Lathrop
- Collaborative Project Mentor: Alexandra DiFeliceantonio
- Biostatistics Mentors: Chris Grubb, Tanner Barbour, Alexandra Hanlon
- Study Aim: To examine the frequency of GLP-1 mentions for weight loss over time, compare descriptors of frequently mentioned foods in general food discussions versus GLP-1 discussions, and compare mental health mentions related to GLP-1s with those related to metformin, a traditional T2D medication
- Analytic Methods: Natural language processing, Proportions and chi-square statistics
- Project Team Members: Chloe Burt, Grayson Weavil, Miriam Sack
- Collaborative Project Mentors: Brooks Casas, Pearl Chiu
- Biostatistics Mentors: Alicia Lozano, Muyao (Jenny) Lin, Alexandra Hanlon
- Study Aim: To examine the role of trust (mediating, moderating) on the relationship between socialization (social network index [SNI], loneliness, disability symptoms) and outcomes (depression, anxiety, alcohol use)
- Analytic Methods: General linear modeling
Photos taken during the CUBE program delivered in 2024. Nine participants were hosted and mentored at either Virginia Tech or University of Virginia.
2023 CUBE Projects:
- Project Team Member: Alicia Alvarez
- Collaborative Project Mentor: Jeff Stein
- Biostatistics Mentors: Alicia Lozano, Alexandra Hanlon
- 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
- Collaborative Project Mentor: Matt Fritts
- Biostatistics Mentors: Sarah Ratcliffe, Genevieve Lyons
- 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
- Collaborative Project Mentor: Alexandra DiFeliceantonio
- Biostatistics Mentors: Monica Ahrens, 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
- Collaborative Project Mentor: Jeff Stein
- Biostatistics Mentors: Alicia Lozano, Alex Hanlon
- 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
- Collaborative Project Mentor: Matt Fritts
- Biostatistics Mentors: Sarah Ratcliffe, Genevieve Lyons
- 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
Photos taken during the CUBE program delivered in 2023. Five participants were hosted and mentored at either Virginia Tech or University of Virginia.
2022 CUBE Projects:
- Project Team Members: Kinara Gasper, Kayla Williams
- Collaborative Project Mentor: Charlotte Baker,
- Biostatistics Mentors: 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
- Collaborative Project Mentor: Julia Scialla
- Biostatistics Mentors: Jennie Ma, Genevieve Lyons
- 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: Jackie Morales
- Collaborative Project Mentor: Virginia LeBaron
- Biostatistics Mentor: Sarah Ratcliffe, Genevieve Lyons
- 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
Photos taken during the CUBE program delivered in 2022. Four participants were hosted and mentored at either Virginia Tech or University of Virginia.
