Associations of Youth Well-Being Trajectories During COVID-19 and Distal Outcomes

Abstract

Introduction: Subjective well-being impacts individuals across the lifespan and is associated with physical health, longevity, and fewer psychosocial issues (Park 2004; Diener, 2012). However, well-being has been on a continuous decline in the last decade, particularly during the COVID-19 pandemic when youth collectively experienced a global crisis (UNICEF Canada, 2022). Despite rapid changes incurred by the pandemic, a subpopulation of youth flourished, demonstrating enhanced well-being, but little is known about factors that influence well-being over time (Cost et al., 2022). Objectives: The current study aims to identify the major trajectories of youth well-being during the COVID-19 pandemic; examine risk and protective factors associated with trajectory trends; and examine whether trajectory classes predict distal outcomes post-pandemic. Hypotheses: We hypothesized that three well-being trajectories would be observed: (a) a trend with increased well-being; (b) a trend with decreased well-being; and (c) a trend where youth show persistent and stable well-being over time. We also hypothesized that protective factors (e.g., optimism, social supports, community engagement, emotional regulation, and resiliency) would be associated with increased and stable youth well-being trajectories, whereas risk factors (e.g., child mental health difficulties, bullying, parental psychopathology, and maternal ACEs) would be associated with decreased youth well-being trajectories. We hypothesized youth trajectories will predict individual distal outcomes (well-being, depression, and anxiety). Study Population: This study is a secondary data analysis utilizing youth participant data (Time 1: Ages 8-11), from the All Our Families (AOF) longitudinal cohort (McDonald et al., 2013). The final sample consisted of 1285 youth, in which the majority of participants were cisgender, white, and came from high income families. Methods: Using latent class growth analyses (LCGA), this study examines youth well-being trajectories from three timepoints during COVID-19 to determine the best model of fit. Regressions and chi-square analyses were used to explore the effects of different risk and protective factors on trajectory growth and predict distal outcomes. Results: Four trajectories were identified: “Decreasing Well-being” (9.6% of sample), “High Stable Well-being” (71.7% of sample), “Low Stable Well-being” (5.5% of sample), and “Increasing Well-being” (13.2% of sample). Class composition significantly differed by age and gender, but not ethnicity nor family income. Among the “Decreasing Well-being” group, risk factors such as child depression (p = .032) and cyberbullying (p < .001) significantly influenced the rate of decrease in youth well-being. Among youth in the “Increasing Well-being” group, optimism (p = .001) and social connections (adult connections: p = .013; peer relationships: p = .008) were associated with slower increases in well-being, while resiliency (p = .025) at the start of COVID-19 was associated with more rapid increase for this group. When examining post-pandemic distal outcomes, youth well-being, depressive, and anxiety symptoms significantly differed between distinct pairs of trajectories during comparison. This indicates that trajectory classes were predictive of distal outcomes in youth. Conclusion: The findings show that youth uniquely responded to adversity posed by the pandemic. Focus on resiliency, optimism, social connections, child depression, and cyberbullying intervention will be important for pandemic-recovery efforts and promoting well-being in the future.