A Vicious Cycle? Group-Level Analysis of Intra-Individual Dynamics in Mental Health Variables

Abstract

Abstract Background The network theory of mental disorders asserts the pivotal role of feedback loops in psychopathology. We investigated intra-individual dynamics and potential feedback loops in psychological networks and their association with long-term outcomes. Methods At the beginning of the COVID-19 pandemic, data from a population-based cohort (N = 2029) were collected every three days for six months on well-being, worries, fatigue, sleep quality, social integration, and activity. Subgrouping—Group Iterative Multiple Model Estimation -was used to estimate networks of time-series data on the individual, subgroup, and group levels. Subgroup networks were compared and associations of subgroup membership with sociodemographic and health status variables at baseline and outcomes at follow-up were examined. Results Despite the large heterogeneity between individuals, a potential feedback loop involving sleep quality, fatigue and well-being was identified. Furthermore, two subgroups were identified, whereby the edges of the potential feedback loop were more present in Subgroup 1 than in Subgroup 2. Membership to Subgroup 1 was associated with lower education and fewer people aged over 60 in their household at baseline as well as poorer well-being, more worries, and more frequent and earlier COVID-19 diagnoses at follow-up. Conclusions The identified feedback loop might indeed represent a vicious cycle and thus contribute to the development of psychopathology. However, limitations such as the limited measurement density made it difficult to find temporal associations and call for a cautious interpretation of results.