Childhood Adversity Moderates Change in Latent Patterns of Psychological Adjustment during the COVID-19 Pandemic: Results of a Survey of U.S. Adults

Emerging evidence suggests that the consequences of childhood adversity impact later psychopathology by increasing individuals’ risk of experiencing difficulties in adjusting to stressful situations later in life. The goals of this study were to: (a) identify sociodemographic factors associated with subgroups of psychological adjustment prior to and after the onset of the COVID-19 pandemic and (b) examine whether and to what extent types of childhood adversity predict transition probabilities. Participants were recruited via multiple social media platforms and listservs. Data were collected via an internet-based survey. Our analyses reflect 1942 adults (M = 39.68 years); 39.8% reported experiencing at least one form of childhood adversity. Latent profile analyses (LPAs) and latent transition analyses (LTAs) were conducted to determine patterns of psychological adjustment and the effects of childhood adversity on transition probabilities over time. We identified five subgroups of psychological adjustment characterized by symptom severity level. Participants who were younger in age and those who endorsed marginalized identities exhibited poorer psychological adjustment during the pandemic. Childhood exposure to family and community violence and having basic needs met as a child (e.g., food, shelter) significantly moderated the relation between latent profile membership over time. Clinical and research implications are discussed

The road to deterministic matrices with the restricted isometry property

The restricted isometry property (RIP) is a well-known matrix condition that provides state-of-the-art reconstruction guarantees for compressed sensing. While random matrices are known to satisfy this property with high probability, deterministic constructions have found less success. In this paper, we consider various techniques for demonstrating RIP deterministically, some popular and some novel, and we evaluate their performance. In evaluating some techniques, we apply random matrix theory and inadvertently find a simple alternative proof that certain random matrices are RIP. Later, we propose a particular class of matrices as candidates for being RIP, namely, equiangular tight frames (ETFs). Using the known correspondence between real ETFs and strongly regular graphs, we investigate certain combinatorial implications of a real ETF being RIP. Specifically, we give probabilistic intuition for a new bound on the clique number of Paley graphs of prime order, and we conjecture that the corresponding ETFs are RIP in a manner similar to random matrices.Comment: 24 page