Worries about the COVID-19 pandemic and the dynamic regulation of emotions in the general population: A network analysis study

Stella D. Voulgaropoulou*, Wolfgang Viechtbauer, Sjacko Sobczak, Thérèse van Amelsvoort, Dennis Hernaus

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background: The impact of the COVID-19 pandemic on mental health has been widely reported. Yet, little remains known about the psychological mechanisms associated with changes in mental well-being during the currently ongoing pandemic. Methods: Here, we use a network analysis to unravel complex relationships between COVID-19 related stressors and emotional states during the initial phase of the COVID-19 (April 2020). Adults living in the Netherlands and Belgium (N = 1145, age 16 and older) (repeatedly) completed an online survey (approximate survey completion rate = 66.2%) about COVID-19 (over a 5-day maximum sampling period). Results: Partial correlations and contemporaneous networks illustrated that worries about the impact of the COVID-19 pandemic were primarily associated with distress and mood ratings, which were subsequently associated with other indicators of well-being. Temporal network analysis revealed that COVID-19 worries were selectively associated with the reciprocal interplay between high distress and low positive mood (https://osf.io/vtdkr/). Limitations: Short-term temporal intervals were evaluated. A small percentage of participants completed the survey repeatedly (35.63% of the total sample), yielding to a relatively small sample size for repeated measures online research. The sample was self-selected. Conclusion: These results may point to potential mechanisms by which initial worries about the COVID-19 pandemic may have impacted psychological well-being.
Original languageEnglish
Article number100618
JournalJournal of Affective Disorders Reports
Volume14
DOIs
Publication statusPublished - 1 Dec 2023

Keywords

  • COVID-19
  • Distress
  • Emotional states
  • Mood
  • Network analyses

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