Dynamic patterns of COVID stress syndrome among university students during an outbreak: a time-series network analysis.

Abstract

Objective: Assessing the progression of COVID stress syndrome (CSS) and understanding how cognitive and emotional factors play a role in the dynamic system is critical for prevention and intervention during the COVID-19 pandemic. We investigated the dynamic relationship between self-reported COVID stress syndrome, cognitive factors, and emotional factors through time-series network analysis.

Methods and measures: Participants were 188 university students involved in an experience sampling method study that lasted 14 days, three times a day, during the COVID-19 pandemic period following a shift in pandemic prevention and control policy.

Results: CSS symptoms are usually present simultaneously, and xenophobia is the most central node of the network. There is a complex mutual predictive relationship between CSS symptoms, in which traumatic stress symptoms are crucial in developing and maintaining the CSS symptom network. Negative affect was associated with CSS symptoms at the same time, and subjective health cognition was a significant predictor of CSS symptoms the next time.

Conclusions: Traumatic stress symptoms are essential nodes in the CSS symptom network, and negative emotions and subjective health influence the occurrence and development of CSS symptoms.