Melissa DeShaw, Abbie Joseph, and Grace Page (Advisor: Danielle Findley-Van Nostrand)

Background Information

In the midst of a pandemic, how have our relationships changed? Due to the COVID-19 pandemic, we suspected that the number of individuals in long-distance relationships may have increased as a result of quarantine and travel restrictions. We also thought this may have disproportionately affected college students who were used to being in geographically-close relationships when they were living on their school’s campus. This shift from being in a geographically-close relationship to being in a long-distance relationship could be a major source of stress that ultimately decreases couples’ satisfaction, and we were interested in considering how this relational dissatisfaction could potentially be reduced in such unprecedented times. After researching relational maintenance behaviors, we decided to examine how the education and implementation of relational maintenance behaviors in college students’ romantic relationships during the COVID-19 pandemic could potentially affect satisfaction in their relationships. Relational maintenance behaviors refer to the several behaviors used to maintain a healthy and successful relationship (Weigel & Ballard-Reisch, 2001). The most common way to measure this is by using the Relational Maintenance Strategy Measure (RMSM) which contains five groups of strategies: positivity, openness, assurances, social networks, and sharing tasks (Stafford & Canary, 1991). These behaviors have been proven to increase satisfaction levels when implemented into a relationship (Weigel & Ballard-Reisch, 2001). Satisfaction was measured using the Relationship Assessment Scale (RAS) which describes several relationship dimensions such as love, problems, and expectations (Hendrick, 1988). Several studies have been conducted on how the use of relational maintenance behaviors correlates with satisfaction, but there are no studies that have used an experiment to test this like ours did. An experiment allows us to determine whether something like relational maintenance behaviors may have a causal impact on satisfaction, and whether they may be able to change through intervention.

Methods

The 36 participants were recruited through Roanoke College’s SONA system in the psychology department and received 2 SONA credits for participating in all parts of the study. Participants had to have been in a romantic relationship. Participants signed up for a Zoom session where they were asked to complete a pre-survey in order to measure satisfaction within their current relationships. After the completion of the pre-survey, participants were asked to return to the Zoom session. Those in the experimental group were read a list of examples from the RMSM and encouraged to try some in their current romantic relationships, and those in the control group were asked to watch a 5 minute video about helpful habits for better sleep. The purpose of a control group is to have a base-line to be able to compare the changes in the experimental group to. Within a week, all participants received an email with a link for a post-survey, and their satisfaction in their romantic relationship was once again assessed using the RAS.

Results and Discussion

Contrary to expectations, participants in the experimental group, who received the informational session on relational maintenance behaviors, did not report more satisfaction at the time of the post-survey compared to the time of the  pre-survey. Additionally, participants in the experimental group did not report more satisfaction than participants in the control group at the time of the post-survey. However, we did find that participants in both the control and experimental groups who reported using more relational maintenance behaviors at the post-survey also reported more satisfaction at the post-survey. Participants in both the control and experimental groups who reported more use of relational maintenance behaviors at the time of the pre-survey also reported more use of these maintenance behaviors at the time of the post-survey. Also, participants from both groups who reported high satisfaction at the pre-survey also reported high satisfaction at the post-survey.

Relational Maintenance Behaviors (Post-Survey) 

Satisfaction (Post-Survey)

Due to our very low sample size, the inability to have face-to-face sessions, and the inability for us experimenters to monitor the relational maintenance behaviors of participants, we did not find what we had previously expected. We did, however, find what previous studies have found, as the participants reported more satisfaction when they used more relational maintenance behaviors in their romantic relationships.

Reflection                                                                                                                                 

Through this process, we gained some much needed insight on what was beneficial to the success of this study, as well as what kept the study from reaching its full potential. First, we believe this study aimed to measure important variables and believe that a replication or partial replication of this study could result in significant and useful findings. Considering the majority of our findings were insignificant, however, we noted a few different aspects of our study that, if changed, may have led to greater significance. For example, the outcome of our study might have been significantly different if everything did not have to be done through online surveys and Zoom sessions. Additionally, we believe that the pressing SONA credit requirement for Psychology students at Roanoke College may have encouraged students to complete our survey for the sake of completion, rather than to provide quality data. If this study were replicated in the future, it would be important to ensure that the participants take the study seriously.

Conclusion

While we found that an information session regarding relational maintenance behaviors given to some participants did not significantly increase satisfaction, we found that all participants seem to already implement these maintenance behaviors in their relationships. The main finding from our study suggests that the use of relational maintenance behaviors in college students’ romantic relationships is associated with their relationship satisfaction, even during a global pandemic.

References

Hendrick, S. S. (1988). A generic measure of relationship satisfaction. Journal of Marriage and the Family, 50(1), 93–98.

Stafford, L., & Canary, D. J. (1991). Maintenance strategies and romantic relationship type, gender and relational characteristics. Journal of Social and Personal Relationships, 8(2), 217–242.

Weigel, D.J., & Ballard-Reisch, D.S. (2001). The impact of relational maintenance behaviors on marital satisfaction: A longitudinal analysis. Journal of Family Communication, 1(4), 265-279.

Ethan Abbott, Sydney Caulder, & Morgan Hamilton (Advisor: Danielle Findley-Van Nostrand)

Background Info

Emerging adulthood is a highly exploratory and developmentally rich period of time in an individual’s life. Between the ages of 18 to 29 is a big transitional phase for young adults to develop their own identity and find their niche in society. There are frequent changes experienced through changing vocations, relationships, and living situations attributed to a significantly reduced sense of stability as compared to parts of life prior to and after emerging adulthood (Arnett 2000; Arnett et al., 2014). In order to properly evaluate how young adults are handling the transitional stressors of their lives coupled with the extenuating circumstances brought on by COVID-19 pandemic, we wanted to see if individual’s locus of control helped mitigate stress. Specifically, an internal locus of control refers to how much one believes their actions are the result of their own efforts, relative to the belief that outside events influence their future (external locus of control). If individuals perceive to have some form of control over a situation then they will find the aversive stimulus to be less threatening.

Another facet of stress management we wanted to measure is an individual’s intolerance of uncertainty. This term refers to the cognitive ability to compartmentalize unknown potentially negative events so that it won’t hinder mental health or physical actions. This anticipation of uncertainty derives from the desire for predictability and an active engagement in seeking certainty and paralysis of cognition and action in the face of uncertainty (Birrell, Meares, Wilkinson, & Freeston, 2011). Emerging adults will also employ various coping strategies for the sake of their physical and psychological well-being. Coping mechanisms are vital towards a young adult maintaining proper mental health because poor maintenance of mental thoughts and adjustment can lead to instability. The four types of core coping mechanisms that young adults utilize are problem-solving, support-seeking, escape, & accommodation (Skinner, Edge, Altman, & Sherwood, 2003). Given the current circumstances of the world at large, we thought it wise to conduct and evaluate a survey administered to the Roanoke College student body to see how these three facets of handling mental stressors are being employed amongst the young adult student population. For the sake of our study we used locus of control and intolerance of uncertainty as predictors of various coping mechanisms.

Methods

Participants in this study were recruited from current students at Roanoke College through the Psychology Department’s SONA system. Participants who were enrolled in psychology courses eligible for extra credit upon participation received one half credit. In total, 145 participants completed the study.

The survey was administered online through Qualtrics where participants were asked demographic information including gender, race, age, year in school, and impact of COVID-19. Previously constructed measurements were used for locus of control, intolerance of uncertainty, and coping. For locus of control, the 24-item Multidimensional Locus of Control Scale was used. Intolerance of uncertainty was measured using the 27-item Intolerance of Uncertainty Scale. Finally, coping was measured using the 60-item COPE inventory.

Results & Discussion

We decided to focus on intolerance of uncertainty and locus and control as predictors of coping in a multiple regression model. A multiple regression model demonstrates the strength of two individual predictors controlling for one another while also controlling for shared variance in a single outcome. The COPE inventory included different subscales focusing on specific forms of coping such as focus on venting of emotions or active coping. There were several significant associations found among the different subscales of coping when intolerance of uncertainty and locus of control were used as predictors. And, in each set of tests, there was a large effect size, meaning that these explained a fairly significant amount of the individual type of coping.

Having a higher internal locus of control was related to greater use of managing distress emotions rather than dealing with the stressor (positive reinterpretation) and less use of behavioral disengagement when controlling for intolerance of uncertainty which was related to less use of positive reinterpretation and more behavioral disengagement.

Internal locus of control was unrelated to, and intolerance of uncertainty positively related to both venting of emotions and mental disengagement.

There was one subscale, active coping, that was positively related to internal locus of control but unrelated to intolerance of uncertainty. See the figure below for an overview of regression results across models; the positive sign indicates as the level of the predictor increases the level of the outcome also increases, and the negative sign indicates that as the level of the predictor increases or decreases the outcome would do the opposite of that increase or decrease).

We also explored differences of mean scores between males and female participants. There were no significant differences based on gender in internal locus of control and intolerance of uncertainty scores, or coping subscales of use of instrumental social support, positive reinterpretation, active coping or behavioral disengagement. There were significant differences in scores based on gender for the coping subscales of focus on venting of emotions, use of emotional support, and mental disengagement.

Our data collection and analysis produced logical results that were mostly as expected. Our research can open the door to future research on how different forms of coping may indicate how individuals perceive changes within their life or the amount of control they feel they have over those changes. This research was especially meaningful given the current COVID-19 pandemic and associated mental health difficulties. Intolerance of uncertainty and internal locus of control may be influential in encouraging adaptive forms of coping.

Figure: Visual Representation of Regression Results: Intolerance of Uncertainty and Internal Locus of Control as Predictors of Forms of Coping.

Reflection

Creating a study which was interesting to all of us and able to be done efficiently through remote learning certainly posed a tough challenge to our group. Initially we thought a study more focused on the current challenges for emerging adults amidst the COVID-19 pandemic would be interesting, but we ultimately decided emerging adults face many challenges with uncertainty regardless of if they are enduring a pandemic or not. The beginning stages were relatively easy to manage by dividing up the work and checking in on each other periodically, but as we started using Jamovi our difficulties took a turn. One of the many challenges posed due to remote learning was the opportunity to learn an entirely new data analysis application, Jamovi. Although Jamovi is user friendly when conducting data, we struggled getting it to be compatible with Qualtrics, and those problems were difficult to work through together. Ultimately these issues were ironed out through many meetings with our group and Dr. Findley-Van Nostrand via Zoom trying to figure it out. Although ultimately our outcome of our research was largely unchanged, it was difficult to manage each challenge together while completing our tasks remotely, but I think we all understood the value of good communication and patience through completing this experience remotely.

References

Arnett, J.J. (2000). Emerging adulthood: a theory of development from the late teens through the twenties. American Psychologist, 55(5), 469–480.

Arnett, J.J. (2014). The new life stage of emerging adulthood at ages 18-29 years: implications for mental health. The Lancet Psychiatry, 1(7), 569–576.

Birrell, J., Meares, K., Wilkinson, A., & Freeston, M. (2011). Toward a definition of intolerance of uncertainty: A review of factor analytical studies of the Intolerance of Uncertainty Scale. Clinical Psychology Review, 31(7), 1198-1208. doi:10.1016/j.cpr.2011.07.009

Skinner, E.A., Edge, K., Altman, J., & Sherwood, H. (2003). Searching for the structure of coping: a review and critique of category systems for classifying ways of coping.. Psychological Bulletin, 129(2), 216-269.

Caelan DeMuth, Mason Wheeler, Maggie Lewis (Advisor: Dr. Findley Van-Nostrand)

Background Information

Many changes brought on by the COVID-19 pandemic have affected well-being of individuals, with college students being uniquely affected given the changes in their academic environment. Specifically, remote learning during the COVID-19 pandemic has changed the way students are expected to learn, potentially driving issues related to focus and to social isolation. Younger students with less experience in university level education may be at higher risk of struggling more than their older peers during the pandemic (Ledman, 2008). In this study, we students’ psychological well-being in relation to their individual need for structure (that is, the extent to which they desire structure and clarity and find ambiguity troubling), academic motivation (the extent to which they are motivated to remain in and do well in school), and academic year. We expected responses that underclassmen or younger students would report higher levels of a need for structure and lower levels of academic motivation, and that both motivation and need for structure would predict well-being. As motivation in academic settings during the ongoing pandemic had yet to be assessed this research may be used to provide insight into how to provide resources to students during upcoming academic terms.

Methods and Measures

Participants for this research were individuals currently enrolled at Roanoke College. There were 115 participants, of which 39 were freshmen, 39 were sophomores, 21 were juniors, and 16 were seniors; 30 identified as male, 83 identified as female, and 2 identified as nonbinary.  Participants were recruited via the Roanoke College Psychology Department through SONA and led to an external survey using Qualtrics. Participants answered a combination of questions pertaining to their academic year, gender, and demographics in addition to questions intended to assess individual needs for structure, academic motivation and well-being. Questions pertaining to structure were taken from the Personal Need for Structure scale. Academic motivation was assessed via questions in the Academic Motivation scale. Psychological Well-Being scale was used to gauge the well-being of participants. Ultimately the three scales demonstrated relationships between individualized preferences for structure, mental health and motivation to remain focused and engaged in coursework during COVID-19.

Results and Discussion

This study was facilitated successfully, especially given the challenges of a nontraditional semester. Contrary to the initial expectation for this study, participants enrolled in their senior year reported the lowest scores for perceived wellness whereas underclassmen reported the highest scores for this criteria. Although students in lower academic years reported higher values of perceived wellness, responses from first years did have the largest standard deviation, suggesting that there was more variation among participants in lower academic years. However, it was found that there was no statistically significant differences when separating between  the psychological well-being subscales (autonomy, environmental mastery, personal growth, positive relations, purpose in life, self-acceptance) between academic years.

Personal need for structure was unrelated to academic motivation. Academic motivation was positively related to psychological well-being in the era of COVID-19 learning. Academic motivation is the voluntary engagement with coursework in terms of intrinsic and extrinsic variables (Cerino, 2014), suggesting that those who can maintain high levels of motivation are likely also experiencing higher well-being in other areas. It was found that personal need for structure statistically significantly predicted the psychological well-being subscale of purpose in life, while academic motivation as a whole statistically significantly predicted the psychological well-being subscale of personal growth, and somewhat significantly predicted the psychological well-being subscale of autonomy. Overall, results suggest that need for structure and academic motivation during the pandemic are related to well-being, but this depends on type of well-being.

Reflection

This research study challenged each of us extensively throughout the duration of the semester. The first and largest obstacle we as a group encountered was transitioning Research Seminar class typically taught in person to a fully remote and functional formatt. We were given the additional task to complete the workload together across time zones via Zoom rather than have the ease of access to be able to meet whenever necessary in person. Our initial research topic was a much broader version of our final product, with the first intent to be to examine COVID-19 impact on wellness in all of its dimensions and definitions. This was evidently too broad as the eight clinical dimensions of wellness (Stoewen, 2017) would have introduced a myriad of confounds to our research. The goal of our work was to examine if academic motivation and perceived wellness had been impacted during a semester of exclusively remote learning.

As our study was conducted via online survey, the ease in accessibility for participants was likely beneficial to the recruitment process. The convenience of the survey being administered online allowed for more people to complete it on their own time. An additional positive to the survey being conducted online eliminated the risk of observer bias and made participants more comfortable by removing the risk of potential exposure to COVID-19. Despite the challenges of conducting research in a fully remote manner, our group was able to find significant associations within our data and report conclusive findings.

Conclusion

The main findings of this study indicate that college underclassmen are experiencing higher perceived wellness than upperclassmen in the era of COVID-19, and that personal need for structure and academic motivation only significantly correlate with three of the six psychological well-being subscales (purpose in life, autonomy, and personal growth). COVID-19 has caused significant changes to what is defined as a normal academic setting. With this knowledge moving forward, academic institutions may use this information to provide adequate mental health resources for students as well as modify course plans to proceed in more academically efficient means.

References

Cerino, Eric. S. (2014). Relationships between academic motivation, self-efficacy, and academic procrastination. Psi Chi Journal of Psychological Research, 19(4).

Ledman, R. (2008). Comparing student learning in online and classroom formats of the same course. Retrieved September 15, 2020, from https://absel-ojs-ttu.tdl.org/absel/index.php/absel/article/view/424/390.

Stoewen, D. (2017). Dimensions of wellness: Change your habits, change your life. Retrieved September 15, 2020, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5508938/.