The COVID-19 pandemic is a rare stressor that has precipitated an accompanying mental health crisis. Prospective studies traversing the pandemic's onset can elucidate how pre-existing disease vulnerabilities augured risk for later stress-related morbidity. We examined how pre-pandemic sleep reactivity predicted maladaptive stress reactions and depressive symptoms in response to, and during, the pandemic. This study is a secondary analysis of a randomised controlled trial from 2016 to 2017 comparing digital cognitive behavioural therapy for insomnia (dCBT-I) against sleep education (N = 208). Thus, we also assessed whether dCBT-I moderated the association between pre-pandemic sleep reactivity and pandemic-related distress. Pre-pandemic sleep reactivity was measured at baseline using the Ford Insomnia Response to Stress Test. In April 2020, participants were recontacted to report pandemic-related distress (stress reactions and depression). Controlling for the treatment condition and the degree of COVID-19 impact, higher pre-pandemic sleep reactivity predicted more stress reactions (β = 0.13, ± 0.07 SE, p = 0.045) and depression (β = 0.22, ± 0.07 SE, p = 0.001) during the pandemic. Further, the odds of reporting clinically significant stress reactions and depression during the pandemic were over twice as high in those with high pre-pandemic sleep reactivity. Notably, receiving dCBT-I in 2016-2017 mitigated the relationship between pre-pandemic sleep reactivity and later stress reactions (but not depression). Pre-pandemic sleep reactivity predicted psychological distress 3-4 years later during the COVID-19 pandemic, and dCBT-I attenuated its association with stress reactions, specifically. Sleep reactivity may inform prevention and treatment efforts by identifying individuals at risk of impairment following stressful events.
OBJECTIVE: This study examined the validity of a novel metric of circadian health, the Entrainment Signal Regularity Index (ESRI), and its relationship to changes in BMI during the school year and summer.
METHODS: In a longitudinal observational data set, this study examined the relationship between ESRI score and children's (n = 119, 5- to 8-year-olds) sleep and physical activity levels during the school year and summer, differences in ESRI score during the school year and summer, and the association of ESRI score during the school year and summer with changes in BMI across those time periods.
RESULTS: The ESRI score was higher during the school year (0.70 ± 0.10) compared with summer (0.63 ± 0.11); t(111) = 5.484, p 0.001. Whereas the ESRI score at the beginning of the school year did not significantly predict BMI change during the schoolyear (β = 0.05 ± 0.09 SE, p = 0.57), having a higher ESRI score during summer predicted smaller increases in BMI during summer (β = -0.22 ± 0.10 SE, p = 0.03).
CONCLUSIONS: Overall, children demonstrated higher entrainment regularity during the school year compared with the summer. During summer, having a higher entrainment signal was associated with smaller changes in summertime BMI. This effect was independent of the effects of children's sleep midpoint, sleep regularity, and physical activity on children's BMI.
BACKGROUND: Prevention of major depressive disorder (MDD) is a public health priority. Strategies targeting individuals at elevated risk for MDD may guide effective preventive care. Insomnia is a reliable precursor to depression, preceding half of all incident and relapse cases. Thus, insomnia may serve as a useful entry point for preventing MDD. Cognitive-behavioral therapy for insomnia (CBT-I) is recommended as the first-line treatment for insomnia, but widespread implementation is limited by a shortage of trained specialists. Innovative stepped-care approaches rooted in primary care can increase access to CBT-I and reduce rates of MDD.
METHODS/DESIGN: We propose a large-scale stepped-care clinical trial in the primary care setting that utilizes a sequential, multiple assignment, randomized trial (SMART) design to determine the effectiveness of dCBT-I alone and in combination with clinician-led CBT-I for insomnia and the prevention of MDD incidence and relapse. Specifically, our care model uses digital CBT-I (dCBT-I) as a first-line intervention to increase care access and reduce the need for specialist resources. Our proposal also adds clinician-led CBT-I for patients who do not remit with first-line intervention and need a more personalized approach from specialty care. We will evaluate negative repetitive thinking as a potential treatment mechanism by which dCBT-I and CBT-I benefit insomnia and depression outcomes.
DISCUSSION: This project will test a highly scalable model of sleep care in a large primary care system to determine the potential for wide dissemination and implementation to address the high volume of population need for safe and effective insomnia treatment and associated prevention of depression.
TRIAL REGISTRATION: ClinicalTrials.gov NCT03322774. Registered on October 26, 2017.