Monthly Archives: November 2022

Lewis Luttrell, a first-year Master’s student, presented his thesis proposal, “Using Polyculturalism to Reduce Intergroup Threat” on November 8th, 2022, in preparation for the upcoming departmental presentation. Polyculturalism is defined as cultures that are byproducts of historical interaction with different groups without a “pure” culture belonging to any one group along with an emphasis on the interconnectionnedness rather than separation. It is one of the four concepts of interethnic ideologies. Some examples would be the two distinct cultures in Louisiana (i.e., Cajun and Creoloe); music genres (i.e., jazz and country); food (i.e., tacos); and architecture (i.e., Indonesian style).

To understand the concept of polyculturalism, it is important to create a solid foundation interconnecting theories such as Social Dominance Theory and Intergroup Threat Theory with Realistic Threat, Perceptions of Threat, and Artifical Segreation. Within previous research, investigations upon ascertaining how polycultural approach may be received by marginalized racial and ethnic groups has been limited. Experts have hypothesized those of marginalized groups could have negative attitudes towards dominant groups which could lead to a decrease in interactions.

At the initial stages of Luttrell’s study, hypothesis one states that polyculturalism with attenuate intergroup threat for all participants regardless of race, ethnicity, and gender. Hypothesis two will narrow the scope to white participants with the expectation that polyculturalism will attenuate intergroup threat regardless of social domination orientation. Measures that will be utilized include SDO-D and SDO-E of SOD7 (alpha=.93), Polyculturalism (alpha= .88), and Intergroup Threat [ITT] for symbolic and realistic threat. Through a prior analysis, Luttrell discovered he would need to obtain 175 participants per group despite previous studies utilizing about 60 individuals per group with the time one and time two phases. During time 1, partipants will initially complete ITT, SDO7, and demographic information. Participants will complete interethnic ideology shift (experimental group) or read an section from the farmers almanac as a control within time 2. However, Luttrell identifies three potential limitations including: a need for a third factor of race; dependence on least one other of race or ethnicity; and two-part study which would increase likelihood of attrition.

We wish you the best of luck on your Master Thesis Defense at the end of the Fall 2022 semester, Lewis! Keep up the wonderful work.

Taylor Elam, a first year Ph.D. Student, recently gave a presentation on her research proposal titled, “I’ll Believe it When I See it: Behavior Change and Person Perception”. This project focuses on how and when people change their perceptions of others.

Taylor explains that people can change by changing their habits, behaviors, attitudes, outlook, verbal and/or physical responses, and most recently discovered, personality. Studies so far have focused on how people change through therapy, how impressions are made and how accurate they are, and how to help people change. Elam saw a need for research that studies when we change our perceptions of others whether the perception is accurate or not.

Elam hypothesized that those who watch a video describing a person’s behavior will change their perception of the person sooner than those who read the vignettes. She aimed to explore the influence of participant characteristics, mood, and interpersonal accuracy on person perception change. The study recruited 300 college students 18+, 100 in each group, for an online survey with 4 time points.

The study would include a person named Taylor described in differing settings and behaviors. For example one setting would be:

“Taylor walks into class, smiling. She shakes hands with teachers and greets her classmates. She sits straight up while watching the lecture. She laughs at the jokes during the presentation. “

“Taylor drives to work listening to upbeat music. “

“Taylor cries at home. Her house is messier because she hasn’t cleaned. She slams her backpack down and goes straight to sleep. “

Other settings would switch out the behaviors with sad connotations with happy behaviors. Throughout the 4 time points, participants would experience differing settings of the same story about Taylor through a video, vignette, or a combination of both. Participants would then complete the survey reporting their demographics, psychological status, adversity experience, personality, mood, emotional intelligence, and empathy. They would then complete the task to report their perception of Taylor based off the video or vignettes.

This study called for a repeated measures design with between and within groups. Data will be analyzed using correlation and regression as well as repeated measures ANOVA. Limitations include the potential need for 5 time points to show stability and consistency, the lack of person-memory concept, lack of subject background information, demographics, and previous behaviors.

Taylor did an excellent job designing and presenting her research proposal, and we can’t wait to follow her through this process!

Paxton Hicks, a first-semester undergraduate research assistant, recently gave a presentation on the article titled,” Social Interaction in Online Support Groups: Preference for Online Social Interaction Over Offline Social Interaction” from Jae Eun Chung.

Online support groups [OSG] have been a rapid source for individuals seeking support. Sixty percent of users who search for health-related information use social media. The usage of the internet alleviates barriers to communication (i.e., geography), which is beneficial to those with rare conditions in order to easily access resources. However, short-term relationships are more common than not along with the increased chance of the spread of unhealthy advice. Researchers have previously observed the excessive use of the internet and its connection to the preferences of online interaction without the context of OSGs. Therefore, there has been an increase in the current body of research focusing on the positive aspects of OSGs.

The purpose of the presented study was to examine the potential factors that influence the presence of online social interaction as opposed to in-person, how support is integrated from online and offline relationships, and advance the understanding of the role of the internet for patient healthcare. Chung hypothesized that (1) compared to those with weaker relationships in OSGs, individuals with deeper relationships in OSGs will develop a stronger preference for social interaction in OSGs over offline social interaction; (2) compared to those with a higher level of satisfaction with offline social support, individuals with a lower level of satisfaction with offline social support will develop a stronger preference for social interaction in OSGs over offline social interaction; and (3) compared to those with a higher level of satisfaction with medical care, individuals with a lower level of satisfaction with medical care will develop a stronger preference for social interaction in OSGs over offline social interaction.

A sample was recruited through four established OSGs of 158 participants (M= 48.2, SD= 16.4) who completed an approximately 15 minutes in length survey. The demographics were 52.2% male, 47.8% female, the majority of the white race, and residency with a spread of 34.6% urban, 47.2% suburban, and 18.2% rural. Measures included Adapted PIU & GPIUS, Adapted QRI, Standard SSO, and PSQ. The Adapted PIU & GPIUS scales, Problematic Internet Use, were used to gauge the preference of social interaction in OSGs. Adapted QRI, Quality of Relationships Inventory, assessed the depth of relationship within the OSG to other users. The shortened version of the SSQ, Social Support Questionaire, measured satisfaction with offline support. The PSQ, Patient Satisfaction Questionaire, measured patient satisfaction with the medical care received.

A correlation matrix was performed to examine the relationships between the variables. Results indicated the depth of relations in OSGs correlated with a preference for social interaction in OSGs (p < .001). Satisfaction with offline support is related to satisfaction with medical care (p < .001). Satisfaction with offline support negatively correlated with a preference for social interaction in OSGs. Multivariate regression was used to measure the effect of these predictors on preference for social interaction in OSGs.

After the data analysis was performed, the results indicated hypothesis 1 and hypothesis 2 were supported. Individuals with higher relationships in OSGs showed higher preferences for social interaction in OSGs. People with lower levels of satisfaction in offline social support reported a higher preference for interaction in OSGs. Hypothesis 3 was not supported; therefore, no significant changes were found.

Chung listed the cross-sectional design as a limitation since it was unable to see the consequences of the developing preference for OSGs. A longitudinal design could have looked at the development of a preference and its consequences better. Hicks, however, believes the under-coverage of certain demographics (i.e., those of different races and communities) and differences in the types of relationships measured were also limitations. Future directions could include applying OSGs in the relevant wake of the COVID-19 pandemic since the lockdown restrictions limited in-person resources. There are various opportunities in investigating individuals with varying health statuses.

Wonderful presentation! We are looking forward to where your research takes you. Keep up the great work, Paxton Hicks!