Our projects on
sleep and chronobiology

Our research encompasses a wide range of areas, including large randomized controlled trials (RCT) on digital Cognitive Behavioral Therapy for Insomnia (dCBTI), also in connection with mental and neurological diseases.

We explore chronotherapy, employ technologies like actigraphy and radar to measure and analyze sleep objectively, and study the use of explainable AI (XAI) in sleep research.

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The overarching aim of the different projects of TSG is to generate knowledge and methods that can directly be translated to and implemented in the clinic.

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From www to zzz: Digital Sleep Treatment for People with Multiple Sclerosis 

Insomnia is common among people with Multiple Sclerosis (MS). Improving sleep is an important therapeutic goal, but there are few effective treatments available. Cognitive Behavioral Therapy for Insomnia (CBT-I) has been studied in other patient groups and is the recommended treatment for insomnia. Access to CBT-I is limited as the number of patients is much higher than the number of available therapists. Therefore, digital versions of CBT-I (dCBT-I) have been developed. Whether this type of treatment is effective for people with MS or if improved sleep can lead to improvements in fatigue, mental health, and cognitive functioning is not known. The main goal of this study is to test whether dCBT-I is effective in reducing insomnia severity, fatigue, psychological distress, and cognitive functioning, medication use, and resource use in healthcare, and the feasibility of dCBT-I. This is a new approach with digital treatment for a common problem in MS, which can lead to increased availability of a low-threshold treatment form.

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Timeframe 

November 2023 - December 2034

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Method 

Quantitative analysis methods

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Project participants

Håvard Kallestad

Knut Langsrud

Lars Bø

Simen Berg Saksvik

Kristine Ytrehus-Lynum

Liv Marie Rønhovde

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Insomnia and Alcohol Use Disorder: A Randomized Controlled Study of Digital Sleep Treatment 

Sleep problems are a common issue among individuals with alcohol use disorder. Cognitive Behavioral Therapy for Insomnia (CBT-I) is the recommended treatment for insomnia. However, few healthcare professionals are trained in this method, and the treatment is not widely available. Therefore, a digital version of CBT-I (dCBT-I) has been developed, where both assessment and treatment occur without direct contact with the healthcare system. In previous studies, we have shown that this intervention can yield excellent results, but it has not been used as a treatment for patients with alcohol use disorder. The purpose of this study is to investigate whether dCBT-I leads to a reduction in insomnia severity, alcohol use, and other clinical outcomes in patients referred for treatment of alcohol use disorder in addiction clinics in Norway. This will be one of the larger treatment studies conducted with non-pharmacological interventions in the field of addiction. The results could form the basis for new practices and provide new knowledge about the significance of sleep problems for patients with substance abuse issues.

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Timeframe 

October 2024 - December 2036

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Method 

Quantitative analysis methods

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Project Participants

Håvard Kallestad

Guro Welander Angenete

Simen Berg Saksvik

Knut Langsrud

Olav Spigset

Kristin Tømmervik

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The Sleep Clinic Outcome and Practice Study (SUP Study) 

The purpose of the study is to describe the practice and outcomes of sleep treatments 1) Cognitive Behavioral Therapy for insomnia and 2) Chronotherapy for sleep-wake rhythm disorders. All patients referred to the Sleep Clinic will be invited to participate before their first consultation with a clinician. The patients will be clinically assessed, diagnosed, and treated as usual. The main outcome of the study will be questionnaires filled out by patients before and after treatment, as well as the timing and duration of specific treatment components and treatment effectiveness logged by the clinician during treatment. The findings from this research project will provide opportunities to improve the treatment for sleep and wakefulness disorders by tailoring treatment differently for respective subgroups. The findings will also contribute to new knowledge on how we treat patients with sleep and wake rhythm disorders and to what extent they benefit from the treatment in a sleep clinic.

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Timeframe 

April 2024 - April 2040

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Method 

Quantitative analysis methods

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Project participants

Håvard Kallestad

Knut Langsrud

Cecilie Lund Vestergaard

Daniel Vethe

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Exploring Contactless or Contact-Minimal Solutions for Sleep Studies 

Polysomnography (PSG) is the gold standard for sleep studies. In cases of suspected obstructive sleep apnea, a simpler variant called respiratory polygraphy is often used. Both methods require several sensors to be attached to the patient. The simplest variant for sleep studies, actigraphy, is an accelerometer packaged like a wristwatch and uses the amount of arm movement to estimate sleep and wakefulness. Sleep studies with many electrodes and wires can be unsafe for unstable/suicidal patients, difficult to perform on children due to their size and reduced cooperation, and problematic for severely somatic patients because they cannot tolerate having so many sensors attached. We will now test a contactless sleep study method in the form of a motion sensor/radar and compare it with traditional methods. This new method is unlikely to surpass PSG in quality but could become the next best option in terms of accessibility/feasibility.

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Timeframe 

April 2017 - March 2025

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Project participants

Morten Engstrøm

Tora Skeidsvoll Solheim

Hanne Siri Amdahl Heglum

Jannicke Syltern

Håvard Kallestad

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A Multi-Center Randomized Controlled Treatment Study Comparing the Effectiveness of Digital Cognitive Behavioral Therapy for Insomnia and Digital Psychoeducation on Sleep for Individuals Referred for Outpatient Treatment in Mental Health Services in Norway 

Sleep is a fundamental need for humans and is significant for our mental and physical health. In individuals with mental disorders, sleep problems are one of the most common issues, and this occurs across all types of disorders. Studies have shown that by treating sleep problems in patients with mental disorders using "cognitive behavioral therapy for insomnia" (CBT-I), patients experience improved sleep. One problem is that few therapists are trained in CBT-I, so patients instead receive sleeping medications, although CBT-I is considered the best treatment. To provide more access to CBT-I, a fully automated internet version of the treatment has been developed (digital CBT-I or dCBT-I). We have tested this in three previous studies in Norway. In the latest study we conducted, we also created a fully automated assessment, allowing us to potentially assess and treat patients with sleep problems using dCBT-I without contact with healthcare personnel. The main objective of this project is to investigate whether dCBT-I can be implemented for patients while they are on the waiting list for regular treatment in mental health services and what effects dCBT-I has on sleep, mental and physical health, and functioning levels. A secondary objective is to investigate whether improving sleep quality early in the treatment process for mental disorders will also lead to better outcomes from regular treatment in DPS (District Psychiatric Centers), shorter treatment times for mental disorders, and less prescription of medications. The study is a randomized controlled multi-center treatment trial where 800 waiting list patients will be offered either dCBT-I or good sleep advice (sleep psychoeducation). Questionnaire timepoints are before randomization, nine weeks, six months, and twelve months after randomization. Data from national registers will be used to address secondary objectives. The project represents a new way of organizing treatment processes in mental health services and can provide a new, low-threshold treatment offer to a large patient group.

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Timeframe 

August 2020 - December 2040

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Method 

Quantitative analysis methods

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Project participants

Håvard Kallestad

Knut Langsrud

Janine Linda Scott

Gunnar Morken

Øystein Vedaa

Børge Sivertsen

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Use of Light in Psychiatric Hospital Buildings to Reduce Hospital Stay and Stabilize Sleep Rhythms during Acute Admission. A Randomized Controlled Trial. 

In recent years, new knowledge has emerged about the significance of light and dark for sleep and mental health. Specifically, it has been shown that blue light in the evening is disruptive to the circadian rhythm, while blocking blue light in the evening can be a new and effective non-drug treatment for severe mental disorders. In this project, we will use a light technology that allows us to adjust the color of the light throughout the day. Thus, we can create a light environment where there is no blue light in the evening and night, while there is normal light for the rest of the day. The main goal is to investigate whether this can reduce the time until patients' condition improves and whether patients can be discharged home more quickly. We will investigate this in a study at St. Olavs Hospital, Østmarka, where 500 patients will be randomly assigned to either a ward with a blue-light-blocking light environment from 6:30 PM to 7:00 AM or an identical ward with normal light throughout the day. All other treatments are as usual.

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Timeframe 

September 2018 - June 2038

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Project participants

Håvard Kallestad

Knut Langsrud

Janine Linda Scott

Gunnar Morken

Daniel Vethe

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Development of a Therapeutic Hospital Building 

This project is based on new research on how light with specific frequencies (blue light) can negatively impact sleep and circadian rhythm. A light technology has been installed in the new psychiatric emergency unit at St. Olavs Hospital, Østmarka, where half of the department can be blocked from blue light in the evening and at night. In this pilot project, we aim to investigate how it feels to be in this building and whether it affects physiological and psychological processes, as well as whether a new type of contactless sleep monitoring is reliable. Ten healthy individuals will be included in a study where they stay for 4 days with blocked blue light in the evening/night and 4 days with normal lighting in a randomized cross-over design. The main goal is to investigate if there are differences between the two conditions regarding circadian rhythm and the experience of the building. The study will provide new information on whether it is possible to design hospitals that facilitate good sleep and factors that influence this, as well as reliable sleep monitoring.

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Timeframe 

August 2017 - April 2040

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Project participants

Håvard Kallestad

Knut Langsrud

Gunnar Morken

Trond Halfdan Sand

Morten Engstrøm

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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 IE and Trondheim Sleep and Chronobiology Research group (SACR) at IPH/St. Olavs Hospital cooperate in the studies.

Subjective sleep data from randomized controlled trials (2500 participants) are analyzed to find baseline predictors for response/non-response to treatment for an eight-week behavioral intervention to improve sleep in people suffering from sleep disturbances. The aim is to find participants in the studies that with a high probability will respond or not to the treatment, based on baseline information from each individual. By doing this, we will establish models that can be used in predicting response to psychological treatments for other disorders. One PhD, Stuart Gallina Ottersen, is working with these data together with the rest of the group. Stuart presented the project for the prime minister and the rector at the opening of the governments National Strategy for Digitalization June 6, 2023. 

The second set of aims are to improve and simplify diagnostics of sleep disorders and improve observation of and prediction of behavior in psychiatric hospital services using radar data with movement registration. We use objective radar data to observe patients in an acute psychiatric department (2500 nights). In addition, radar data is collected from smaller samples where the observations also include polysomnography and actigraphy. The datasets are of unprecedented size and quality, and are ideal for training machine learning algorithms and to develop new analysis methods. The project has a significant potential to change existing treatment and observation strategies in psychiatry. It may lead to easier, more cost-effective, and more precise diagnosing of sleep disorders, in addition to opening up a whole new field of using movement patterns as a tool to predict behavior. 

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Timeframe

January 2023 - June 2027 

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Project participants

Gunnar Morken

Ingvild Ulsaker-Janke

Stuart Gallina Ottersen

Sophia Sylvester

Hanne Siri Amdahl Heglum

Simen Berg Saksvik

Knut Langsrud

Håvard Kalestad

Kerstin Bach

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