COVID-19 and Social Isolation: Predicting Psychological Distress in High vs. Low Self-Monitors

Consistent with past pandemics and other infectious outbreaks, preliminary research on the COVID-19 pandemic has demonstrated exacerbated levels of mental health issues. These findings corroborate a large body of research on loneliness and mental well-being, suggesting that social isolation can be detrimental to our mental and psychological health. The present investigation explores Self-Monitoring as a predictor of psychological distress during extended periods of social isolation such as that of the COVID-19 pandemic. The Self-Monitoring construct captures systematic differences between individuals regarding their behavioral orientation. Low self-monitors generally base their behavior on their internal states, which tends to remain consistent across situations, whereas high self-monitors rely on external factors and are concerned with social appropriateness, so they often alter their behavior to control how others perceive them. As such, high self-monitors construct larger and less restrictive social networks that allow for behavioral adaptability, whereas low self-monitors tend to have more intimate relationships that are fewer in number. Previous research has demonstrated that self-monitors differ in the types of events that provoke affective states, with high self-monitors showing signs of depression with threats to their external presentation and low self-monitors with threats to their internal consistency. Given that the COVID-19 quarantine measures have primarily involved eliminating the external social environment that high self-monitors rely on, it was hypothesized that high self-monitors would report more salient symptoms of depression and anxiety compared to their low self-monitoring counterparts. In a sample of 185 Union College students, participants completed a series of eight questionnaires that measured their self-monitoring, loneliness, depression, anxiety, and overall well-being. Although the results were not conventionally significant, data analysis revealed an unexpected pattern of preliminary results that will help to fill gaps in the literature that may have implications on improving the psychological well-being of college students in the future.