Daily dynamics and mechanisms of anxious symptomatology in the general population: A network study during the COVID-19 pandemic.

To understand the interplay between anxiety symptoms and their maintaining psychological processes in the population, an analysis of longitudinal within-person relationships is required. A sample of 1706 individuals completed daily measures during a 40-day period with strict mitigation protocols. Data of 1368 individuals who completed at least 30 assessments were analyzed with the multilevel vector autoregressive (mlVAR) model. This model estimates a temporal, a contemporaneous, and a between-person network. Uncontrollability of worry, generalized worry, fear of being infected, fear of significant others being infected, and threat monitoring had the highest outstrength within the temporal network, indicating that daily fluctuations in these components were the most predictive of next-day fluctuations in other components. Of specific connections, both fear of self and fear of close others being infected predicted generalized worry and threat monitoring. In turn, generalized worry and threat monitoring engaged in several positive feedback loops with other anxiety symptoms and processes. Also, intolerance of uncertainty was predictive of other components. The findings align with the mechanisms both in the metacognitive therapy (MCT) model and in the intolerance of uncertainty model of generalized anxiety disorder (GAD).

Back to life, back to reality: A multi-level dynamic network analysis of student mental health upon return to campus during the COVID-19 pandemic.

Lockdown measures during the COVID-19 pandemic resulted in drastic disruptions of university students' everyday life and study mode, such as marked reductions in face-to-face teaching activities. Previous research on student mental health during the pandemic found that prolonged campus relocation had negative effects on students' mental well-being. However, these studies focussed on the initial lockdown period, or periods of active lockdown measures. This longitudinal study collected 456 observations of 23 undergraduate students in the Netherlands using ecological momentary assessment data on mental health related items (anxiety, stress, social context) during the first two weeks of on-campus teaching after prolonged lockdown measures. Using multi-level dynamic network modelling, we analysed the temporal and contemporaneous interplay of students' mental health factors following the return to campus in September 2021. On average, students reported low to medium scores on stress and anxiety both before and after the assessment period. Results of network analyses showed that students experienced social unease in relation to accumulating difficulties at university and vice versa. Furthermore, there were clusters of different states of social unease next to clusters of stress, anger, loss of control, and feeling upset. Lastly, we found beneficial effects of self-efficacy on experiencing social comfort in university. We discuss implications and concrete examples of interventions in universities, such as the promotion of self-efficacy, providing guidance in structuring study load, as well as help with stress management. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-022-03196-7.

Within- and across-day patterns of interplay between depressive symptoms and related psychopathological processes: a dynamic network approach during the COVID-19 pandemic.

BACKGROUND: In order to understand the intricate patterns of interplay connected to the formation and maintenance of depressive symptomatology, repeated measures investigations focusing on within-person relationships between psychopathological mechanisms and depressive components are required. METHODS: This large-scale preregistered intensive longitudinal study conducted 68,240 observations of 1706 individuals in the general adult population across a 40-day period during the COVID-19 pandemic to identify the detrimental processes involved in depressive states. Daily responses were modeled using multi-level dynamic network analysis to investigate the temporal associations across days, in addition to contemporaneous relationships between depressive components within a daily window. RESULTS: Among the investigated psychopathological mechanisms, helplessness predicted the strongest across-day influence on depressive symptoms, while emotion regulation difficulties displayed more proximal interactions with symptomatology. Helplessness was further involved in the amplification of other theorized psychopathological mechanisms including rumination, the latter of which to a greater extent was susceptible toward being influenced rather than temporally influencing other components of depressive states. Distinctive symptoms of depression behaved differently, with depressed mood and anhedonia most prone to being impacted, while lethargy and worthlessness were more strongly associated with outgoing activity in the network. CONCLUSIONS: The main mechanism predicting the amplifications of detrimental symptomatology was helplessness. Lethargy and worthlessness revealed greater within-person carry-over effects across days, providing preliminary indications that these symptoms may be more strongly associated with pushing individuals toward prolonged depressive state experiences. The psychopathological processes of rumination, helplessness, and emotion regulation only exhibited interactions with the depressed mood and worthlessness component of depression, being unrelated to lethargy and anhedonia. The findings have implications for the impediment of depressive symptomatology during and beyond the pandemic period. They further outline the gaps in the literature concerning the identification of psychopathological processes intertwined with lethargy and anhedonia on the within-person level.