Research and Internships

Previous research examining the relationship between personality and obsessive-compulsive symptoms (OCS) found that high neuroticism and low conscientiousness are related to elevated OCS severity; however, this research has mostly conceptualized OCD as a unitary condition. Therefore, we examined the relationship between factor-analyzed OCD symptom dimensions and personality factors to better understand how these trait characteristics relate to unique symptoms of OCD. Three hundred and ten undergraduates completed the Big Five Inventory and the Dimensional Obsessive-Compulsive Scale. Multiple linear regression analyses demonstrated a positive relationship between neuroticism and the Responsibility for Harm, Symmetry and Taboo dimensions. Contrary to previous research though, there was a significant negative relationship between trait agreeableness and the severity of the Contamination dimension. This finding may suggest that individuals who fear germs and contamination may possess less trust for others and their environment, and future research must determine whether this prospectively worsens OC symptom severity.
Taylor performed this project with the help of faculty advisor Noah C. Berman.

College-aged females are more likely to have higher GPAs and graduate at faster rates than males. Yet, women are still underrepresented in high-ranking campus positions such as being president of the Student Government Association (Johnson, 2011; Miller & Kraus, (2004). These disparities in leadership participation between males and females are important to understand since the college environment is one of the few settings where access to leadership roles is abundant and easily attainable. The purpose of this study is to discover specific predictors that influence one’s participation in leadership roles among third and fourth year students. This study is a replication of Peralta 's (2015) study, which suggested that women’s attitudes about public speaking were strong predictors of leadership participation, but it differs by including men. Participants filled out a questionnaire where they answered questions on overall leadership participation, general self-efficacy, career aspiration, self-reported fear of negative evaluation from others, attitudes toward public speaking, perceived social support, and aspirations to obtain elite leadership in their future career. Regression and correlation analyses will be conducted to determine the predictors of leadership participation among college students. 
Binah performed this project with the help of her faculty advisory Danuta Bukatko.

Caffeine has previously been more restricted to adult use, but unfortunately, children and adolescents are now the fastest growing group of users (Temple, 2009). The allure of caffeine typically comes from a desire for energy enhancement or social interaction (Ludden et al., 2017). Increased adolescent caffeine use has been linked to sensation seeking, other substance use as well as sleep dysfunction, poor diet, and nervousness (Branum et al., 2015, Temple et al., 2010). The current study examined how health-related factors, substance use, sports and work participation, and academic engagement were associated with late adolescents’ use of energy drinks, energy shots, soda, and alcohol mixed with energy drinks in a series of hierarchical linear regressions. We utilized nationally-representative survey data from 12th graders (N = 2103) from the 2016 Monitoring the Future study. Results indicated that students who skipped more classes, worked more hours, and participated in more evenings out for fun were more likely to report energy drink use and mixing alcohol and energy drinks together. In addition, health factors, particularly substance use, were predictors of adolescents’ use of energy drinks/shots, soda, and alcohol mixed with energy drinks. Adolescents’ marijuana use, e-cigarette use, and cigarette use were all associated with higher consumption of caffeinated beverages.

Christine performed this project with the help of Blake DeVries ’18, Samantha Girard ’19, Grace Hurley ’20, Minh Nguyen ’19 and faculty advisor Alison Bryant Ludden.

Schizophrenia is a psychiatric illness characterized by psychotic symptoms, cognitive impairment, and social dysfunction. Unfortunately, antipsychotic medications used to treat schizophrenia have severe metabolic side effects. It is unclear whether metabolic risk genes established in the general population are also associated with poor metabolic outcomes among antipsychotic-treated patients. Exploration of this clinical question requires a statistical approach that accommodates variable selection and allows for potentially complex interactions among covariates. Tree-based machine learning algorithms such as Classification and Regression Trees (CART) handle these data analytic challenges and provide results that are easily interpretable for physicians. We review implementation of CART using the R statistical software package and demonstrate the utility of tree-based algorithms using a motivating data set provided by the Schizophrenia Research Program at Massachusetts General Hospital. Among a cohort of several hundred patients, genetic risk factors emerged as predictive of several metabolic outcomes, suggesting that genetic screening may prove useful for personalized decision making and treatment management.

Grace performed this project with the help of faculty advisors Shannon Stock and Alo Basu.

An attentional bias towards unhealthy food cues is implicated in the etiology of obesity and is thought to influence cravings and food consumption. Research has yet to determine whether similar breakdowns in control toward food cues occur in normal weight individuals as well. 32 female undergraduates with a normal weight Body Mass Index (BMI) were tested on an antisaccade task (look away from cue) on unhealthy food, healthy food, and non-food cues. Breakdowns in control (making errors and looking at cue) to only unhealthy foods were significantly associated with BMI (p< 0.005). These findings indicate that breakdowns in control to unhealthy foods occur in normal weight, not only obese, individuals, though the magnitude of error is directly associated with body weight.

Christine performed this project with the help of Glorianna Theodhoraqi ’18, Abigail Szkutak ’19, Koryna O’Besso ’18, Federico Sorcini ’20, Emma Gurchiek ’19, Julia Hall ’20, Celeste Ferre ’18, Michael Rabinovich ’18, Samuel Acheampong ’19, Surbhi Daryani ’20, Hannah Johnson ’21 and Faculty Advisors Jumi Hayaki and Gregory J. DiGirolamo.

When asked to explain the causal mechanisms of the day-night cycle, elementary school students often show coherent, albeit often scientifically incorrect, mental models (Vosniadou & Brewer, 1994). More recent findings suggest that children may not have a consistent narrative when describing these mechanisms and instead present a more fragmented understanding (Vosniadou & Skopeliti, 2017). Drawing on this research, we analyzed video interviews about the day/night cycle from 3rd-grade children (N=120). We found that children hold a variety of intuitive conceptions related to Sun motion: that the Sun orbits Earth, the Sun goes into the ground, the Sun goes up and down, the Sun and Earth trade places, and the Sun rotates. Currently we are further developing this coding rubric to capture the extent to which children’s conceptions are (1) consistent with scientific knowledge (low, medium, high) and (2) scientifically integrated (low, high). For example, a child who describes day/night solely on the basis of Earth-based observations (e.g., the Sun goes up and down) would be classified as low in both scientific knowledge and integration, whereas a child who uses Earth’s rotation to explain day/night but uses Sun motion to describe sunrise/sunset would be classified as having some (medium) scientific knowledge but low integration. Further analyses may also reveal the extent to which children anthropomorphize celestial bodies and incorporate teleological thinking in their explanations.

Victoria performed this project with the help of Amanda M. McCarthy ’18 and Faculty Advisors Florencia K. Anggoro and Benjamin D. Jee (Worcester State University).

Through the qualitative work of narrative psychology, this thesis explores experiences of mixed race individuals who have one white parent, one minority parent, and who grew up in a predominantly white community. The data were drawn from the author’s own first-hand experiences as well as in-depth interviews from three Holy Cross students about their mixed race identities. On the basis of these data, three forms of self-identity were found to be especially salient: the unaware self, the unique self, and the liminal self. The unaware self can be understood as not knowing how one appears to others. The unique self is manifested in a desire to feel special in comparison to others. The liminal self is experienced as a state of “in-betweenness,” in the sense of not feeling fully a part of either racial background. The liminal self could be experienced negatively, as if one has to choose which racial group to identify with or when one feels one is only entitled to half a voice. However, the liminal self could also be experienced as a “positive marginality” (Daniel, 1996), as when one sees one’s mixed race identity as an opportunity to explore one’s multifaceted nature and connect with multiple social worlds.

Kelly performed this project with the help of Faculty Advisor Mark Freeman.