BACKGROUND
Digital cognitive behavioral therapy for insomnia (dCBTi) is a scalable and effective intervention for treating insomnia. The findings regarding its efficacy compared to face-to-face CBTi are inconclusive but suggest that dCBTi might be inferior. The lack of human support and low treatment adherence are believed to be barriers to dCBTi achieving its optimal efficacy. However, there has yet to be a direct comparative trial of dCBTi with different types of coaching support.
OBJECTIVE
The present study examined whether adding virtual and human coaching would improve dCBTi’s efficacy and treatment adherence.
METHODS
129 participants (76% women; age = 34.09 ± 12.05) who had clinically significant insomnia symptoms (Insomnia Severity Index (ISI) ≥ 10) were recruited. A randomized controlled comparative trial with five arms was conducted: dCBTi with virtual coaching and therapist support (dCBTi-therapist), dCBTi with virtual coaching and research assistant support (dCBTi-assistant), dCBTi with virtual coaching only (dCBTi-virtual), dCBTi without any coaching (unguided-dCBTi), and digital sleep hygiene and self-monitoring control (dSH). Participants completed measures of insomnia (ISI, the Sleep Condition Indicator [SCI]), mood disturbances, fatigue, daytime sleepiness, quality of life, dysfunctional beliefs about sleep, and sleep-related safety behaviors, at baseline, post-treatment, and 4-week follow-up. Treatment adherence was measured by the completion of video sessions and sleep diaries. Intention to treat analysis was conducted using linear mixed models. Fisher’s exact tests was conducted to evaluate differences in treatment adherence across conditions.
RESULTS
Significant condition-by-time interaction effects showed that recipients of dCBTi, regardless of having any coaching or not, had greater improvements in insomnia measured by the SCI (Cohen’s d=.45), depressive symptoms (Cohen’s d=-.62), anxiety (d=-.40), fatigue (d=-.35), dysfunctional beliefs about sleep (d=-.53), and safety behaviors related to sleep (d=-.50), than those of dSH. The addition of virtual coaching and human support did not improve treatment efficacy. However, adding human support promoted greater reductions in fatigue (d=-.33), and sleep-related safety behavior (d=-.30) than dCBTI-virtual at 4-week follow-up. In particular, dCBTi-therapist promoted a greater reduction in fatigue than dCBTi-assistant at follow-up (d=-.41). As expected, dCBTi-therapist had the highest video and diary completion rates compared to other conditions (video: 60+% in dCBTi-therapist vs. <25% in dCBTi-unguided), indicating greater treatment adherence, especially in later treatment sessions.
CONCLUSIONS
The present findings support the efficacy of a fully automated, standalone dCBTi in treating insomnia, reducing thoughts and behaviors that perpetuate insomnia, reducing mood disturbances, fatigue, and improving quality of life. Adding virtual coaching and human support did not significantly improve dCBTi’s efficacy at post-treatment. Still, it may improve long-term efficacy given its effects on increasing treatment adherence and incremental benefits on reducing fatigue and behaviors that could perpetuate insomnia.
CLINICALTRIAL
ClinicalTrials.gov NCT05136638