Self-efficacy in Insomnia Symptom Management after Digital CBT-I Mediates Insomnia Severity during the COVID-19 Pandemic
Year: 2021
Type: article
Abstract: STUDY OBJECTIVES: Digital cognitive behavioral therapy for insomnia (dCBT-I) can reduce acute insomnia and depressive symptoms and prevent symptom recurrence. The current study evaluated self-efficacy in managing insomnia symptoms as a potential mediator of the relationship between prior dCBT-I and subsequent insomnia and depressive symptoms assessed during the coronavirus 2019 (COVID-19) pandemic. METHOD: Participants were 208 adults who completed a randomized controlled trial of dCBT-I versus sleep education in 2016-2017 and also completed self-report assessments of insomnia, depression, and self-efficacy in managing insomnia symptoms. Data were collected in May 2020, five weeks into state-wide COVID-19 stay-at-home orders. Regression and mediation analyses were used to evaluate the extent to which self-efficacy accounted for the relationship between treatment condition and improvement in insomnia and depressive symptoms from pre-treatment to COVID-19 follow-up. RESULTS: Prior dCBT-I predicted greater self-efficacy in managing insomnia symptoms. Self-efficacy accounted for 49% and 67% of the protective effect of dCBT-I against COVID-era insomnia and depressive symptoms, respectively. CONCLUSIONS: This study affirms the importance of self-efficacy as a key intervention outcome and potential mechanism by which dCBT-I predicts future sleep and mental health. Future studies that evaluate the role of self-efficacy in treatment effectiveness and resilience can provide additional clues about how to optimize dCBT-I for maximum benefit to public health.
Source: Behavioral Sleep Medicine
Institutions: Henry Ford Health, University of Oregon
Language: English
Topic: Sleep and related disorders
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
Awards: G4899745771, G5924165898, G82555732
OpenAlex ID: W3201640738
