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.

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.

Working alliance with an avatar: How far can we go with internet interventions?

OBJECTIVE

To examine the working alliance between users and an avatar and users' treatment expectations in an unguided Internet intervention for the treatment of insomnia.

METHODS

The sample included participants from the treatment condition (N = 29) of a randomised controlled trial. The task and goal subscales of the Working Alliance Inventory Short Revised (WAI-SR) were applied in week three. Five items of the Bern Post-Session Report and one question about the extent to which users had missed a human therapist were administered after each session. Treatment expectations were measured with the Credibility Expectancy Questionnaire (CEQ), and the Insomnia Severity Index (ISI) was used as the primary outcome measure.

RESULTS

The mean scores for the WAI-SR task and goal subscales were relatively high (M = 3.24, SD = 0.79; M = 3.16, SD = 0.91, respectively). The mean score of the five Bern Post-Session Report items remained stable over time, but some users increasingly indicated that they missed a real therapist over the course of the intervention, with a strong linear effect (t(87) = 3.16, p < 0.01). ISI chance score was predicted by the mean score of the Bern Post-Session Report (b = -0.3.83, t(21.80) = -2.97, p < 0.01), missing a human therapist (b = -0.0.13, t(20.47) = -2.72, p = 0.01) and the CEQ (b = 0.18, t(19.03) = -2.69, p = 0.01), but not by WAI-SR task and goal subscales.

CONCLUSIONS

Results indicate that users established a working alliance with the avatar. The affective bond remained stable over time, but towards the end of the intervention some users indicated that they missed having a human therapist. Affective bond and missing a real therapist predicted symptom change.

Translational research studies of erbB oncogenes: selection strategies for breast cancer treatment

Specific gene families, e.g. encoding members of signal transduction pathways, show a gene dosage sensitivity. We report on the determination of the gene dosages of egfr and c-erbB-2 in relation to the intratumoral concentration of the tyrosine kinase receptor protein EGFR and p185c-erbB-2 and the clinical outcome of breast cancer patients in a retrospective study. Prognostic unfavorable subgroups were determined in a life-table analysis by (a) an average gene copy number of egfr of less than 0.4 and greater than 1.6 and an intratumoral EGFR concentration of more than 56 fmol/mg, (b) an intratumoral p185c-erbB-2 concentration above 26 HNU/mg and (c) a quotient of egfr and c-erbB-2 average gene copy numbers of less than 0.15 and greater than 4.35.