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Previous research has shown the efficacy of (combinations of) individual components of cognitive behavioral therapy for insomnia (CBT-I), namely sleep hygiene education, sleep restriction, stimulus control therapy, deactivation/relaxation training, and cognitive therapy. However, their relative effects, i.e., their effects in direct comparison with each other, are yet to be assessed. By means of the Multiphase Optimization Strategy (MOST), this study aims to investigate the components' relative efficacy in order to identify the most effective component or combination of components for digitized treatment of chronic insomnia. A future study will verify this intervention's effect in a randomized controlled trial (RCT).
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The DOSE Project employs the Multiphase Optimization Strategy (MOST) to evaluate the relative efficacy of the individual cognitive behavioural therapy for insomnia (CBT-I) components. The present study represents the optimization phase of MOST, which aims to identify which combination of CBT-I components produces the best expected outcome, while taking constraints, such as economy, scalability, treatment complexity, and usability, into account.
The main objectives of the DOSE Project are
This study employs a fractional factorial experimental design conducted with individuals experiencing moderate-to-severe insomnia. With random allocation, participants will receive a version of the application in which one or more of the five core CBT-I components (i.e., sleep hygiene education, sleep restriction, stimulus control therapy, deactivation/relaxation training, cognitive therapy) are presented in various combinations. The intervention lasts 10 weeks, including an initial one-week assessment period.
Baseline group differences (concerning socio-demographic, disease-related, and psychosocial data) will be explored to test the success of the randomization. If differences are found, sensitivity analyses will be made to evaluate their possible influence on the results. Main effects will be analysed using Mixed Linear Models (MLMs) based on the intent-to-treat sample, comparing aggregated groups of N = 2 x 320 (e.g., plus/minus sleep restriction or plus/minus sleep hygiene etc.) on all outcome variables. MLMs account for the hierarchical, non-independent nature of the data (i.e., repeated measures nested within patients and treatment conditions), testing the time*group interaction effect, reflecting the effect of treatment. Moderation analyses will evaluate whether individual differences in various baseline variables (e.g., physical function, expectations, computer proficiency, chronotype, etc.) influence intervention effects.
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489 participants in 16 patient groups
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Ali Amidi, PhD, MSc; Sofie Møgelberg Knutzen, MSc
Data sourced from clinicaltrials.gov
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