The clinical effect of digital cognitive behavioural therapy for insomnia in subgroups with depressive and anxiety symptoms: A secondary analysis of a randomized-controlled trial.

Insomnia is a highly prevalent mental disorder, and is often co-occurring with depression and anxiety disorders. Cognitive behavioural therapy for insomnia as treatment of choice for insomnia can also be applied digitally (digital cognitive behavioural therapy for insomnia), making it more accessible. This is a secondary data analysis of a two-armed parallel randomized-controlled trial. In the primary publication, N = 238 participants meeting criteria for the 5th edition of Diagnostic and Statistical Manual of Mental Disorders chronic insomnia disorder were randomly assigned to either 8 weeks of digital cognitive behavioural therapy for insomnia + treatment-as-usual, or waitlist + treatment-as-usual. To determine the clinical effects of digital cognitive behavioural therapy for insomnia in populations with comorbid anxiety and depression symptoms, this secondary analysis focused on two subgroups: (1) participants with high initial depressive symptoms; and (2) participants with high initial anxiety symptoms. Symptoms of insomnia, depression and anxiety as primary outcome measures were obtained at baseline, 8 weeks post-randomization and, in the intervention group only, at 6- and 12-months follow-up. At 8 weeks post-randomization, the use of digital cognitive behavioural therapy for insomnia in both subgroups was associated with large reductions in insomnia severity in comparison to control (depression subgroup: d = 2.37; anxiety subgroup: d = 2.13). Between-group treatment effects were also observed for symptoms of depression in the depression subgroup (d = 1.59), and for symptoms of anxiety in the anxiety subgroup (d = 1.28). Within-group effects were stable over time (d = 0.64-1.63). This secondary analysis shows that digital cognitive behavioural therapy for insomnia reduces insomnia and comorbid symptoms in participants with high initial symptoms of either depression or anxiety with sustained long-term effects.

Nightmare distress is related to traumatic childhood experiences, critical life events and emotional appraisal of a dream rather than to its content.

Nightmares are a substantial burden for sleep quality. Previous studies have shown that traumatic experiences can increase the probability of nightmares, and also waking-life distress can enhance this effect. There is evidence that the intensity of negative dream emotions is more responsible for rating a dream as a nightmare than threatening dream contents. However, there is still a lack of research concerning effects on nightmare distress. We hypothesise that traumatic childhood experiences (such as emotional abuse, obtained by the Childhood Trauma Questionnaire), critical life events (obtained by the Social Readjustment Rating Scale) and threatening dream contents are associated with nightmare distress. A sample of N = 103 participants kept a dream diary over 28 consecutive days. About 60% of the sample were frequent nightmare dreamers. The participants recorded their violent dream contents and dream emotions in their diary. To predict nightmare distress, regression models were constructed; nightmare distress was measured with the Nightmare Distress Questionnaire. Results showed that emotional abuse in childhood and critical life events predicted nightmare distress. Moreover, violent dream contents were associated with nightmare distress but, after we controlled for nightmare frequency and the intensity of negative dream emotions, the significant impact of violent dream contents decreased. The results suggest that the emotional appraisal of a dream has a substantial influence on nightmares in addition to traumatic childhood experiences and critical life events.

The clinical effects of digital cognitive behavioral therapy for insomnia in a heterogenous study sample: results from a randomized controlled trial.

STUDY OBJECTIVES: Numerous studies worldwide have reported the beneficial effects of digital cognitive behavioral therapy for insomnia (dCBT-I). However, few focus on real-world study samples that reflect people in regular care. To test whether dCBT-I is suitable within German regular care, we designed a randomized controlled trial recruiting a heterogenous insomnia population. METHODS: Participants aged ≥18 who met the criteria for insomnia disorder were randomized to 8-weeks dCBT-I + care-as-usual (CAU) or they were set on a waitlist + CAU. The intervention group was followed-up at 6- and 12-months. The primary outcome was self-reported insomnia severity, assessed with the Insomnia Severity Index (ISI) at 8-weeks post-randomization. A one-way ANCOVA with baseline score as a covariate was fitted to determine group differences. Secondary outcomes included measures of daytime functioning, quality of life, depression, anxiety, dreams, and nightmares. RESULTS: Of the N = 238 participants (67.6% female), age range 19-81 years, n = 118 were randomized to dCBT-I and n = 120 to the control group. At posttreatment, the use of dCBT-I was associated with a large reduction in the ISI (Diffadj = -7.60) in comparison to WLC (d = -2.08). This clinical improvement was also reflected in responder and remission rates. Treatment effects were also observed for daytime functioning, quality of life, symptoms of depression and anxiety (ds = 0.26-1.02) and at long-term follow-up (intervention group only; ds = 0.18-1.65). No effects were found for dream and nightmare frequency. CONCLUSIONS: This study showed that dCBT-I reduces insomnia symptoms and improves daytime functioning in a heterogenous insomnia population in Germany with sustained long-term treatment effects in the intervention group. Our results underscore the potential of digital health applications, their suitability within regular care, and their role in facilitating widespread implementation of CBT-I as a first-line treatment for insomnia.