A Digital Therapeutic to Improve Insomnia in Multiple Sclerosis: A Randomized Controlled Trial.

The goal of this randomized controlled trial is to test the effectiveness of digital cognitive behavioral therapy for insomnia (dCBT-I) compared with digital patient education about insomnia for people with Multiple Sclerosis (MS). The main questions it aims to answer are whether dCBT-I is effective in reducing insomnia severity in people with MS, whether dCBT-I is effective in reducing daytime fatigue, psychological distress, cognitive problems, medication use (hypnotic, sedative/anxiolytic and antidepressant), resource utilization and if these changes are mediated by improvements in insomnia severity and whether dCBT-I is feasible for people with MS

Insomnia is prevalent among individuals with Multiple Sclerosis (MS). Improving sleep is an important therapeutic goal, but there is currently a lack of effective treatment options. Cognitive Behavioral Therapy for Insomnia (CBT-I) has been widely studied in other patient groups and is currently recommended as first- line treatment for chronic insomnia.

Overall, the availability of CBT-I has been limited, as the number of patients in need of treatment far exceeds the number of available therapists. Therefore, fully automated digital adaptations of CBT-I (dCBT-I) have been developed that contain both screening and intervention. Whether this treatment is effective for a clinical sample of patients diagnosed with MS, or if improved sleep can lead to improved daytime functioning in MS, is however, currently unknown.

This is a novel approach to a digital treatment of a common disorder in MS, and that may result in improved implementation of a low-threshold intervention.

Update August 28th, 2024

We aim to increase the target sample size from 260 to 550 to increase the statistical power to detect differences between the intervention group and control group on the secondary outcomes, e.g., fatigue, cognitive functioning, mental health, and movement measures measured with actigraphy. Few treatment options have shown effects on these outcomes for people with MS but are a significant problem for this patient group. Small effects from this trial may have substantial scientific and clinical value and are important to test with adequate statistical power.

Based on previous RCTs investigating the effectiveness of dCBT-I we aim to have a sample size large enough to detect small to moderate effects (Cohen's d = 0.3 til 0.5) on the secondary outcome measures fatigue, cognitive function, mental health and movement measures measured with actigraphy. As the planned RCT involves limited contact between researchers and participants, we have predicted that the study dropout rate will likely reach about 50%. Therefore, we aim to recruit 550 participants, to enable us to retain 275 participants (137 in each treatment arm) at the end of the RCT. For a two-sample t-test with alpha=0.05, this sample size gives a power of 90% of detecting a difference of Cohen's d = 0.40.

Eligibility Criteria:
Inclusion Criteria:

1. Having an established diagnosis of Multiple Sclerosis (MS) and being included in the Norwegian MS registry
2. Being 18 years or older
3. Scoring at least 12 points on the Insomnia Severity Index
4. Willing and able to provide written informed consent

Exclusion Criteria:

1. Self-reported symptoms of sleep apnea: Positive endorsement of a screening question for sleep apnoea (the item asks if they 'usually or everyday snore and stop breathing and have difficulties staying awake during the day')
2. Self-reported surgery for heart disease the last two months
3. Currently in an attack phase of MS and/or on treatment with steroids,
4. Self-reported night shifts in their work schedule,
5. Inadequate opportunity to sleep or living in circumstances that prevent modification of sleep pattern (e.g. having an infant residing at home),
6. Pregnant in the last two trimesters
7. Unable to get into bed or out of bed without human assistance.
8. Concomitant psychological treatment for sleep problems