Alcohol, cannabis, and nicotine use have distinct associations with COVID-19 pandemic-related experiences: An exploratory Bayesian network analysis across two timepoints.

BACKGROUND: Substance use trends during the COVID-19 pandemic have been extensively documented. However, relatively less is known about the associations between pandemic-related experiences and substance use. METHOD: In July 2020 and January 2021, a broad U.S. community sample (N = 1123) completed online assessments of past month alcohol, cannabis, and nicotine use and the 92-item Epidemic-Pandemic Impacts Inventory, a multidimensional measure of pandemic-related experiences. We examined links between substance use frequency, and pandemic impact on emotional, physical, economic, and other key domains, using Bayesian Gaussian graphical networks in which edges represent significant associations between variables (referred to as nodes). Bayesian network comparison approaches were used to assess the evidence of stability (or change) in associations between the two timepoints. RESULTS: After controlling for all other nodes in the network, multiple significant edges connecting substance use nodes and pandemic-experience nodes were observed across both time points, including positive- (r range 0.07-0.23) and negative-associations (r range -0.25 to -0.11). Alcohol was positively associated with social and emotional pandemic impacts and negatively associated with economic impacts. Nicotine was positively associated with economic impact and negatively associated with social impact. Cannabis was positively associated with emotional impact. Network comparison suggested these associations were stable across the two timepoints. CONCLUSION: Alcohol, nicotine, and cannabis use had unique associations to a few specific domains among a broad range of pandemic-related experiences. Given the cross-sectional nature of these analyses with observational data, further investigation is needed to identify potential causal links.

Posttraumatic stress disorder symptom trajectories in a 16-month COVID-19 pandemic period.

COVID-19 pandemic presents an unheralded opportunity to better understand trajectories of posttraumatic stress disorder (PTSD) symptoms across a prolonged period of social disruption and stress. We tracked PTSD symptoms among trauma-exposed individuals in the United States and sought to identify population-based variability in PTSD symptom trajectories and understand what, if any, early pandemic experiences predicted membership in one trajectory versus others. As part of a longitudinal study of U.S. residents during the pandemic, participants who reported at least one potentially traumatic experience in their lifetime (N = 1,206) at Wave 1 (April 2020) were included in the current study. PTSD symptoms were assessed using the PCL-5 at four time points extending to July 2021. Latent growth mixture modeling was used to identify heterogeneous symptom trajectories. Trajectory membership was regressed on experiences from the early stage of the pandemic as measured using the Epidemic-Pandemic Impacts Inventory in a model that controlled for variables with documented associations to PTSD trajectories, including age, sex, income, and trauma history. Four trajectories were identified, categorized as resilient (73.0%), recurring (13.3%), recovering (8.3%), and chronic (5.5%). Emotional and physical health problems and positive changes associated with the early phase of the pandemic were each significant predictors of trajectory membership over and above all other variables in the model. Predictors primarily differentiated the resilient trajectory from each of the other three trajectories. Distinct PTSD symptom trajectories during the COVID-19 pandemic suggest a need for targeted efforts to help individuals at most risk for ongoing distress.

COVID-Dynamic: A large-scale longitudinal study of socioemotional and behavioral change across the pandemic.

The COVID-19 pandemic has caused enormous societal upheaval globally. In the US, beyond the devastating toll on life and health, it triggered an economic shock unseen since the great depression and laid bare preexisting societal inequities. The full impacts of these personal, social, economic, and public-health challenges will not be known for years. To minimize societal costs and ensure future preparedness, it is critical to record the psychological and social experiences of individuals during such periods of high societal volatility. Here, we introduce, describe, and assess the COVID-Dynamic dataset, a within-participant longitudinal study conducted from April 2020 through January 2021, that captures the COVID-19 pandemic experiences of >1000 US residents. Each of 16 timepoints combines standard psychological assessments with novel surveys of emotion, social/political/moral attitudes, COVID-19-related behaviors, tasks assessing implicit attitudes and social decision-making, and external data to contextualize participants' responses. This dataset is a resource for researchers interested in COVID-19-specific questions and basic psychological phenomena, as well as clinicians and policy-makers looking to mitigate the effects of future calamities.