Summary: Digital sleep therapy could be an effective method to treat insomnia and reduce the use of sleeping pills.
Approximately 500 000 Norwegians suffer from chronic sleep disorders, also called insomnia. Researchers have long known that cognitive behavioural therapy for insomnia is the best documented treatment, but few people have access to such therapy.
A fully automated digital version of this treatment has proven effective for many patients and can reduce the use of sleeping pills.
“Our results show that it’s possible to provide very effective and drug-free sleep treatment on a large scale. This can be done without meeting with health personnel,” says clinical psychologist Håvard Kallestad.
Kallestad is a researcher at St. Olav’s Hospital and at the Norwegian University of Science and Technology’s (NTNU) Department of Mental Health. He is also one of the first authors of a newly published article in The Lancet Digital Health.
Digital sleep support can help people identify the underlying causes of their sleep issues. The treatment addresses problematic sleep patterns, various stressors and other factors that interfere with sleep. Patients keep a journal that can provide insight into their own situation.
The new study in The Lancet Digital Health is encouraging.
The treatment study included 1721 participants, who received either digital sleep therapy or good sleep advice and digital information about sleep problems. All were Norwegian adults over the age of 18 who had difficulty sleeping. The findings are quite clear.
Approximately six of ten participants (58 percent) experienced substantial improvement from the digital sleep therapy. In the control group, which received good sleep advice and digital information, only around 20 percent experienced a similar effect. The digital sleep treatment was thus about three times as effective.
Thirty-eight percent of participants achieved normal sleep quality after undergoing the digital sleep therapy. Only eight percent of the control group had similar results.
“We also found that the participants who received digital sleep treatment were able to reduce their use of sleeping pills more than participants who only received sleep advice,” says Kallestad.
This form of psychological therapy for a significant public health problem could prove to be more accessible than sleep medication treatment.
Digital sleep therapy is fully automated, meaning that no appointment with a health care provider is needed for the treatment. The study interventions were also automated.
The sleep treatment takes about 6 to 8 weeks to complete.
Funding: The study is a collaborative project between the Norwegian Institute of Public Health, NTNU and St. Olavs Hospital. It is funded by the Research Council of Norway (FHI) and Samarbeidsorganet (The Liaison Committee for Education, Research and Innovation in Central Norway) between the Central Norway Regional Health Authority and NTNU.
Researcher Øystein Vedaa from FHI and NTNU and Kallestad shared first authorship in this study. Børge Sivertsen from FHI and NTNU was the last author. The digital sleep therapy programme used in the study was developed at the University of Virginia. About this autism research article
Source: NTNU Contacts: Håvard Kallestad – NTNU Image Source: The image is in the public domain.
Effects of digital cognitive behavioural therapy for insomnia on insomnia severity: a large-scale randomised controlled trial
Background Although several large-scale randomised controlled trials have shown the efficacy of digital cognitive behavioural therapy for insomnia (dCBT-I), there is a need to validate widespread dissemination of dCBT-I using recommended key outcomes for insomnia. We investigated the effect of a fully automated dCBT-I programme on insomnia severity, sleep–wake patterns, sleep medication use, and daytime impairment.
Methods We did a parallel-group superiority randomised controlled trial comparing dCBT-I with online patient education about sleep. The interventions were available through a free-to-access website, publicised throughout Norway, which incorporated automated screening, informed consent, and randomisation procedures, as well as outcome assessments. Adults (age ≥18 years) who had regular internet access and scored 12 or higher on the Insomnia Severity Index (ISI) were eligible for inclusion, and were allocated (1:1) to receive dCBT-I (consisting of six core interactive sessions to be completed over 9 weeks) or patient education (control group). Participants were masked to group assignment and had no contact with researchers during the intervention period. The primary outcome was the change in ISI score from baseline to 9-week follow-up, assessed in the intention-to-treat population. This trial is registered with ClinicalTrials.gov (NCT02558647) and is ongoing, with 2-year follow-up assessments planned.
Findings Between Feb 26, 2016, and July 1, 2018, 5349 individuals commenced the online screening process, of which 1497 were ineligible or declined to participate, 2131 discontinued the screening process, and 1721 were randomly allocated (868 to receive dCBT-I and 853 to receive patient education). At 9-week follow-up, 584 (67%) participants in the dCBT-I group and 534 (63%) in the patient education group completed the ISI assessment. The latent growth model showed that participants in the dCBT-I group had a significantly greater reduction in ISI scores from baseline (mean score 19·2 [SD 3·9]) to 9-week follow-up (10·4 [6·2]) than those in the patient education group (from 19·6 [4·0] to 15·2 [5·3]; estimated mean difference −4·7 (95% CI −5·4 to −4·1; Cohen’s d −1·21; p<0·001). Compared with patient education, the number needed to treat with dCBT-I was 2·7 (95% CI 2·4 to 3·2) for treatment response (ISI score reduction ≥8) and 3·2 (2·8 to 3·8) for insomnia remission (ISI score <8). No adverse events were reported to the trial team.
Interpretation dCBT-I is effective in reducing the severity of symptoms associated with the insomnia disorder. These findings support the widespread dissemination of dCBT-I. Future research is needed to identify the moderators of response and to improve targeting.
Funding Norwegian Research Council; Liaison Committee for Education, Research and Innovation in Central Norway.