Identifying Psychological Distress Patterns during the COVID-19 Pandemic using an Intersectional Lens

Objective. We inform an intersectional understanding of differences in psychological distress across the U.S. population during the early months of the COVID-19 pandemic by examining the unique and interactive influences of multiple social variables on levels of psychological distress.

Methods. The March and April 2020 waves of the American Trends Panel (N = 4,560) were analyzed using conditional inference trees and random forests to examine how complex interactions among social status variables influence psychological distress levels.

Results. Age, gender, socioeconomic status, and community attachment most influenced distress in March 2020, while race and ethnicity emerged as influential in April 2020, especially among older men.

Conclusions. The results provide insights into how multiple social statuses interact to shape psychological distress levels. By analyzing distress as a result of multiple pathways, we address theoretical mandates to consider the intersecting influence of social statuses on mental health. Targeted interventions by mental health specialists are discussed.

Contribution. This study builds upon the extensive and ever-growing literature on the effects that the COVID-19 pandemic has had on health, while specifically approaching the analysis with an intersectional lens and using tree-based statistical modeling to better visualize the differential impact the early months of the pandemic had on mental health.