Insomnia interventions
Insomnia interventions
We have conducted extensive trials of digital adaptations of Cognitive Behavior Therapy for Insomnia (dCBT-I), in which participants can receive treatment for their insomnia from the comfort of their own homes. These digital treatments have yielded positive effects in both the general population and in outpatient care settings.
We have conducted several trials of Cognitive Behavior Therapy for Insomnia (CBT-I). CBT-I is considered the gold standard treatment for people experiencing chronic insomnia, but due to the high prevalence of insomnia in the general population, the demand for treatment exceeds the capacity of the healthcare-system to deliver such treatment. To tackle this obstacle, we have conducted extensive trials of digital adaptations of Cognitive Behavior Therapy for Insomnia (dCBT-I), in which participants can receive treatment for their insomnia from the comfort of their own homes. These digital treatments have yielded positive effects in both the general population and in outpatient care settings.
The Norse Trials
The Norse trials are a collection of randomized controlled trials that test the effectiveness of digital CBT-I. Currently, there are four Norse trials where we use a fully automated, self-guided, internet-delivered CBT-I. The program, SHUTi, was developed at the University of Virginia.
Norse 1
A pilot randomized controlled trial (n=181) testing the effectiveness of dCBT-I compared to online patient education control in terms of sleep improvement, daytime functioning, and psychological wellbeing after the intervention period and at 18-months follow-up.
Published articles from Norse 1
- Internet-delivered cognitive-behavioral therapy for insomnia and comorbid symptoms
- Long-Term Effects of an Unguided Online Cognitive Behavioral Therapy for Chronic Insomnia
Norse 2
A randomized controlled trial (n=101) to study whether dCBT-I is non-inferior to Face-to-face CBT-I. The study aims to estimate rates of clinical response and remission of insomnia, to test if there are group differences in psychological distress, fatigue and sleep patterns, and to report the acceptability of dCBT-I compared to Face-to-Face therapy.
Norse 3
A two-arm randomized controlled trial (n=1721) that assess the benefits of dCBT-I compared to an alternative, active control intervention of online patient education about sleep. The trial test the short- and long-term effectiveness of dCBT-I in the general population, with outcome variables such as insomnia severity, changes in symptoms of physical and mental health and sick leave.
Published articles from Norse 3
- The effect of sleep-wake intraindividual variability in digital cognitive behavioral therapy for insomnia: a mediation analysis of a large-scale RCT
- The effect of sleep-wake intraindividual variability in digital cognitive behavioral therapy for insomnia: a mediation analysis of a large-scale RCT
- Digital cognitive behaviour therapy for insomnia (dCBT-I): Chronotype moderation on intervention outcomes
- Effects of digital cognitive behavioural therapy for insomnia on insomnia severity: a large-scale randomised controlled trial
- Overcoming insomnia: protocol for a large-scale randomised controlled trial of online cognitive behaviour therapy for insomnia compared with online patient education about sleep
Norse 4
A large, multicenter randomized controlled trial comparing the effectiveness of dCBT-I to an online control-condition of sleep hygiene advice for 800 patients referred to community mental health care centers for outpatient treatment for any mental disorder. The aim for this project is to test if online treatment for insomnia is feasible and if it will improve treatment outcomes in the specialist services. Secondly, we wish to include subgroup analyses to test if there are patient groups who are more likely to benefit from the treatment and cost-benefit analyses.
Published article from Norse 4
Other clinical trials
Machine learning to tailor treatments in mental health (AI-MENT)
In psychiatry there is an urgent need for (i) reliable analytic tools to predict response/non-response to psychological treatment and (ii) to develop objective observational and diagnostic tools. Our ambitious aims are to (i) develop novel analyses and methods to predict response to psychological treatment using machine learning in order to avoid over-treatment and to offer personalized treatment, and (ii) improve observation and diagnosis in mental health wards, leading to better treatment and patient safety.
The Data and Artificial Intelligence (DART) group at Department of Computer Science and Trondheim Sleep and Chronobiology Research group (SACR) at the Department of Mental Health/St. Olavs hospital will cooperate in analyzing existing (i) subjective sleep data from randomized controlled trials and (ii) objective radar data used to observe patients in an acute psychiatric department (2500 nights).
More on Machine learning to tailor treatments in mental health (AI-MENT)
Sleep-BP
A randomized controlled trial to test the effectiveness of CBT-I for patients with bipolar disorder and insomnia.
Articles from the study
- Mood and motor activity in euthymic bipolar disorder with sleep disturbance
- Cognitive behavioral therapy for insomnia in euthymic bipolar disorder: study protocol for a randomized controlled trial
Psychoeducation for bipolar disorder
Randomized controlled trial to test the effectiveness for group based psychoeducation on hospital admissions for patients with bipolar disorder.
Article from the study
Chronotherapy
Research theme
Sleep problems are ubiquitous in hospital settings, especially in mental health care. We have developed a hospital infrastructure with an aim to improve the observation of patients at night and improve treatment outcomes using knowledge about the human circadian system. At St. Olavs Hospital, research is integrated in the clinic.
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