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

1. Internet-delivered cognitive-behavioral therapy for insomnia and comorbid symptoms
2. 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

1. The effect of sleep-wake intraindividual variability in digital cognitive behavioral therapy for insomnia: a mediation analysis of a large-scale RCT
2. The effect of sleep-wake intraindividual variability in digital cognitive behavioral therapy for insomnia: a mediation analysis of a large-scale RCT
3. Digital cognitive behaviour therapy for insomnia (dCBT-I): Chronotype moderation on intervention outcomes
4. Effects of digital cognitive behavioural therapy for insomnia on insomnia severity: a large-scale randomised controlled trial
5. 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

Digital cognitive-behavioural therapy for insomnia compared with digital patient education about insomnia in individuals referred to secondary mental health services in Norway: protocol for a multicentre randomised controlled trial

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

1. Mood and motor activity in euthymic bipolar disorder with sleep disturbance
2. 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

1. The long-term outcomes of an effectiveness trial of group versus individual psychoeducation for bipolar disorders

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.

The project

Individuals with mental disorders are admitted to acute inpatient care for three main reasons: acute distress associated with risk of suicide, significant increase in illness severity, or major impairment in day-to-day functioning arising from mental or behavioral dysregulation. Hospitalization allows detailed clinical assessment and monitoring of progress, and intensive treatments, to be provided in a safe and structured environment.

Although the quality and fabric of inpatient facilities have improved over recent decades with more attention to providing a homely environment and better quality accommodation, little attention has been given to how to use the environment of the unit to optimize treatment and improve the mental state and social functioning of the patients. There has been a lack of innovation in treatments, observation techniques or environments over the last 50 years. This project specifically focuses on the development of an innovative program to enhance the environment within an acute inpatient unit to try to reduce time to stabilization of mental state, improve observation at night, and to enable patients to achieve earlier discharge back to their home and community.

Background

This project is based on two important empirical findings

1. First, poor sleep quality and circadian dysrhythmia are significantly associated with relapse or worsening of major mental disorders (e.g. psychotic, bipolar and major depressive disorders) and with increased suicidality; whilst improvement in sleep and circadian rhythmicity are associated with early improvement in mental state. Thus, an important target for all acute psychiatric treatment is stabilization of the sleep-wake cycle.
2. Second, recent findings from basic physiology and treatment research has elucidated how light at specific frequencies can have a profound impact on arousal, sleep, circadian disruption. Moreover, blocking these specific light frequencies can be a highly effective treatment for severe mental disorders, leading to early improvement in symptoms and functioning. This is a potential breakthrough in our understanding of how severe mental disorders are maintained and offers the opportunity for the development of innovative non-pharmacological interventions.

Based on these findings, we have incorporated new light and radar technologies into a ‘new-build’ psychiatric inpatient unit to create a hospital environment and infrastructure that we hypothesize will: decrease arousal, promote sleep-wake cycle and circadian stability, and lead to a shortening of the average length of admissions. Also, it may allow a reduction in the number or dosages of medications used to achieve improvements in mental state and functioning.

Further, the new technologies employed allow improve non-invasive observation of the patients at night, allowing more accurate monitoring of sleep and symptomatic improvement. There is a critical need to evaluate all aspects of the approach to determine the benefits (and to identify if there are any drawbacks or adverse effects).

Aims

The specific aims of this project are to test these hypotheses in four research avenues:

1. A randomized cross-over study to test the positive impacts and any side-effects or adverse effects of the new hospital light environment on physiological and psychological factors (e.g. related to levels of arousal and circadian rhythmicity), and to determine its acceptability to the participants.
2. Validation studies on a novel contact-free, ultra-wide band radar technology which can be used for real-time assessment of sleep, movement, and respiration.
3. A randomized controlled treatment trial of 400+ patients admitted to the new hospital. The trial will test the effects on duration of admissions, medication use, sleep and circadian stability, and potential side-effects, of this environment compared to patients admitted to an inpatient environment that lacks the new lighting technology.
4. Studies on how the hospital staff experience working in the new light environment.

Articles on the project

1. The evening light environment in hospitals can be designed to produce less disruptive effects on the circadian system and improve sleep
2. Evening light environments can be designed to consolidate and increase the duration of REM-sleep
3. Sleep and work functioning in nurses undertaking inpatient shifts in a blue-depleted light environment
4. A more detailed description of the unit and background (pdf)
5. Søvn 1. utgave 2019 
6. The chronotherapeutic treatment of bipolar disorders: A systematic review and practice recommendations from the ISBD task force on chronotherapy and chronobiology
7. A pragmatic effectiveness randomized controlled trial of the duration of psychiatric hospitalization in a trans-diagnostic sample of patients with acute mental illness admitted to a ward with either blue-depleted evening lighting or normal lighting conditions

Our research implement new technologies to assess and understand sleep and wakefulness.

Contact free sleep assessment

Our research investigates the potential of an impulse radio ultra-wideband (IR-UWB) radar as tool for contact-free objective sleep assessment and monitoring. The radar can be placed on a nightstand or permanently embedded in the ceiling of a hospital room, and is capable of detecting a large range of movements from a person in a room without requiring them to wear equipment on their body; from the big movements of limbs to the very small motions induced by respiration.

We have installed radars in 40 hospital rooms at the acute psychiatric ward at St. Olavs Hospital. We are working on methods to interpret this radar data in a clinically useful way, and comparing the results to commonly used objective measures like polysomnography (PSG) and actigraphy.

Contact-free sleep monitoring could be used to provide information to aid diagnosis and clinical decision-making as well as important feedback to the patients, without the downsides related to on-body sensors or staff observation.

Done in real-time, it could also be used to provide hospital night staff with information about the patients’ current sleep-wake state, e.g. as displayed on monitors in the staff rooms or sent to hand-held devices. In turn this could improve patient safety, reduce the number of nocturnal awakenings due to disturbance from night staff, and lead to more efficient use of limited staff resources at night.

Articles on the project

1. Distinguishing sleep from wake with a radar sensor: a contact-free real-time sleep monitor
2. Contact-free radar recordings of body movement can reflect ultradian dynamics of sleep
3. Søvn 1. utgave 2019​​​​​​​