ABSTRACT
Introduction: While the negative consequences of insomnia are welldocumented, a strengths-based understanding of how sleep can promote health promotion is still emerging and much-needed. Correlational evidence has connected sleep and insomnia to resilience;however, this relationship has not yet been experimentally tested. This talk will examine resilience as an ingredient and outcome of insomnia treatment Methods: Participants were randomized to either digital Cognitive Behavioral Therapy for insomnia (dCBT-I;n = 358) or sleep education control (n = 300), and assessed at pre-treatment, post-treatment, and one-year follow-up. Change in self-reported resilience was tested across the time points, and also examined as a mechanism driving insomnia and depression as outcomes. A follow-up study during the COVID-19 pandemic further examined the protective effect of dCBT-I. Result(s): DCBT-I resulted in greater improvements in resilience compared to the sleep education control. The improved resilience was a significant mediator of reduced insomnia and depression severity following treatment. Furthermore, improved resilience following dCBT-I also reduced insomnia and depression at one-year follow-up by lowering latent risk. Sensitivity analyses indicated that each point improvement in resilience following treatment reduced the odds of insomnia relapse and incident depression one year later by 76% and 65% respectively. Finally, those who previously received dCBT-I demonstrated greater resilience via protection from insomnia, depression, and COVID-19 specific stress. Conclusion(s): Improved resilience is a contributing mechanism to treatment gains following dCBT-I and may further protect against longer-term insomnia and depression by reducing risk.
ABSTRACT
Introduction: The 2019 coronavirus disease (COVID-19) pandemic is a protracted stressor with far-reaching effects on daily life. Although most individuals exhibit resilience in the wake of adversity, it is not clear which characteristics reliably predict resilience versus longstanding distress. It is vital to delineate predictors of pandemic-related distress to highlight modifiable risk factors that can be targeted to enhance psychological resilience. Sleep reactivity may be an important predictor of pandemic reactions because it reflects a vulnerability to experience pronounced sleep disturbances in response to stress, which serve as barriers to healthy adjustment to adversity. Therefore, this study tested sleep reactivity as a prospective predictor of pandemic-related distress. Methods: Participants were recruited from a previous randomized controlled trial (RCT) comparing self-guided digital CBT-I against a sleep education control in treating insomnia and preventing depression. Participants in the RCT were enrolled between 2016-2017 and were eligible for this follow-up study conducted between April and May 2020 (N = 208;dCBT-I: n = 102;control: n = 106). Pre-treatment sleep reactivity was measured in 2016-2017 (T1) using the Ford Insomnia Response to Stress Test (FIRST). COVID-19 distress was measured in April 2020 (T2) using the Impact of Events Scale (IES) and Quick Inventory of Depressive Symptomatology (QIDS). All analyses controlled for treatment condition and COVID-19 impact. Results: T1 FIRST predicted T2 IES (b = 0.29, + 0.14 SE, p < .05) and QIDS (b = 0.16, + 0.04 SE, p < .001), such that higher sleep reactivity pre-pandemic predicted more severe stress responses and depressive symptoms during the pandemic 3-4 years later. Exploratory analyses revealed T1 FIRST was a predictor of the IES subscales arousal and intrusions (bs = 0.02, + 0.01 SEs, ps < .05), but not avoidance. Conclusion: These findings build on evidence that sleep reactivity prospectively predicts reactions to trauma and demonstrate its predictive utility generalizes to pandemic responses. Sleep reactivity is a modifiable risk factor that may be targeted using cognitivebehavioral or mindfulness-based approaches, and thus may offer a new pathway to resilience.