Heterogeneity in trajectories of traumatic distress at the start of the COVID-19 pandemic.

OBJECTIVE: The COVID-19 outbreak has led to an increase in posttraumatic stress symptoms (PTSSs; Prout et al., 2020) for some individuals, whereas others appeared to be more resilient. It remains relatively unclear what characterizes these potentially different response trajectories ( Chen & Bonanno, 2020). This study sought to (a) assess individuals' PTSS levels at the start of the pandemic and at two subsequent timepoints 3 and 6 months later, (b) identify different trajectories of PTSSs over time, and (c) describe which individual characteristics influenced the likelihood of each of these different trajectories to occur. METHOD: A community sample (n = 317) responded to an online survey during the first weeks of the pandemic, 3 and 6 months later. RESULTS: Among those who reported acute levels of PTSSs, latent class growth analyses identified three different resilience trajectories-resilient (low baseline PTSSs and a slight decrease over time), chronic (severe PTSSs at baseline and no change over time), and recovered (severe PTSSs at baseline but a sharp improvement over time). Baseline childhood adversity, depression, anxiety, defensive functioning, and somatization predicted trajectories. Demographics (age, gender, preexisting chronic illness) and COVID-related factors (knowing someone diagnosed with or who died of COVID-19) were unrelated to trajectories. CONCLUSIONS: Results suggest that although high PTSS levels decreased over time on average, heterogenous change trajectories can be identified based on baseline psychological characteristics. This implies that mental health, including past and present experiences, as well as adaptational mechanisms may shape individuals' experiences with pandemic-related ongoing stress. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Identifying Predictors of Psychological Distress During COVID-19: A Machine Learning Approach.

Scientific understanding about the psychological impact of the COVID-19 global pandemic is in its nascent stage. Prior research suggests that demographic factors, such as gender and age, are associated with greater distress during a global health crisis. Less is known about how emotion regulation impacts levels of distress during a pandemic. The present study aimed to identify predictors of psychological distress during the COVID-19 pandemic. Participants (N = 2,787) provided demographics, history of adverse childhood experiences, current coping strategies (use of implicit and explicit emotion regulation), and current psychological distress. The overall prevalence of clinical levels of anxiety, depression, and post-traumatic stress was higher than the prevalence outside a pandemic and was higher than rates reported among healthcare workers and survivors of severe acute respiratory syndrome. Younger participants (<45 years), women, and non-binary individuals reported higher prevalence of symptoms across all measures of distress. A random forest machine learning algorithm was used to identify the strongest predictors of distress. Regression trees were developed to identify individuals at greater risk for anxiety, depression, and post-traumatic stress. Somatization and less reliance on adaptive defense mechanisms were associated with greater distress. These findings highlight the importance of assessing individuals' physical experiences of psychological distress and emotion regulation strategies to help mental health providers tailor assessments and treatment during a global health crisis.