A longitudinal network analysis of social connection and professional quality of life among healthcare workers during the COVID-19 pandemic.

BACKGROUND: Society depends on people willing to serve in high stress occupations, such as healthcare workers who served on the front lines during the COVID-19 pandemic. However, these roles can take a toll on psychological health, fueling turnover and staff shortages. This toll can be mitigated with social connection. Yet, little is known about how the multifaceted constructs of psychological health and social connection influence one another over time. Understanding these dynamics is critical for identifying effective intervention targets in high-stress professions.

METHODS: We conducted a three-wave survey of U.S. healthcare workers (N = 230) within the first year of the COVID-19 pandemic. Each wave assessed facets of social connection (loneliness, giving and receiving support, and social ties) and psychological health (positive mental health, work satisfaction, burnout, and secondary traumatic stress). To identify the direction of associations across time, we modeled a longitudinal network in the form of a Bayesian Directed Acyclic Graph (DAG).

RESULTS: Across waves, loneliness and positive mental health exerted the strongest downstream influence on all other psychological and social variables. Giving support had a mutually reinforcing relationship with positive mental health; giving support at wave 1 predicted positive mental health (and work satisfaction) at wave 2, which in turn predicted giving support at wave 3.

CONCLUSIONS: Findings highlight promising intervention points for healthcare workers during a public health crisis. Using a DAG network on longitudinal data, this study revealed unique insights into the dynamic relationships between psychological health and social connection in the context of occupational stress.