Randomized Controlled Trial to Test the Efficacy of an Unguided Online Intervention with Automated Feedback for the Treatment of Insomnia

Investigating the subjective and objective efficacy of a cognitive behavioural therapy for insomnia (CBT-I)-based smartphone app on sleep: A randomised controlled trial

Due to insufficient treatment options for insomnia, effective solutions are urgently needed. We evaluated the effects of a CBT-I-based app combining sleep training with subjective and objective sleep monitoring on (i) sleep and (ii) subjective-objective sleep discrepancies (SOSD). Fifty-seven volunteers (20-76 years; MAge = 45.67 ± 16.38; 39 female) suffering from sleep problems were randomly assigned to an experimental group (EG, n = 28) or a waitlist control group (CG, n = 29). During the 6-week app phase, the EG used the CBT-I-based programme and a heart rate sensor for daily sleep monitoring and -feedback, while the CG used sleep monitoring only. Sleep was measured (i) subjectively via questionnaires (Insomnia Severity Index, ISI; Pittsburgh Sleep Quality Index, PSQI), (ii) objectively via ambulatory polysomnography (PSG), and (iii) continuously via heart-rate sensor and sleep diaries. Data revealed interactions for ISI (p = 0.003, ƞ2 part = 0.11) and PSQI (p = 0.050, ƞ2 part = 0.05), indicating training-specific improvements in EG, yet not in CG. While PSG-derived outcomes appear to be less training-specific, a tendential reduction in wake after sleep onset (WASO) was found in EG (p = 0.061, d = 0.55). Regarding changes in SOSD, the results indicate improvements during the app phase (EG) for sleep efficiency, sleep onset latency, and WASO (p ≤ 0.022, d ≥ 0.46); for total sleep time both groups showed a SOSD reduction. The findings indicate beneficial effects of a novel smartphone app on sleep and SOSD. More scientific evaluation of such digital programmes is needed to ultimately help in reducing the gap in non-pharmacological insomnia treatment.

Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review

BACKGROUND

Chatbots, or conversational agents, have emerged as significant tools in health care, driven by advancements in artificial intelligence and digital technology. These programs are designed to simulate human conversations, addressing various health care needs. However, no comprehensive synthesis of health care chatbots' roles, users, benefits, and limitations is available to inform future research and application in the field.

OBJECTIVE

This review aims to describe health care chatbots' characteristics, focusing on their diverse roles in the health care pathway, user groups, benefits, and limitations.

METHODS

A rapid review of published literature from 2017 to 2023 was performed with a search strategy developed in collaboration with a health sciences librarian and implemented in the MEDLINE and Embase databases. Primary research studies reporting on chatbot roles or benefits in health care were included. Two reviewers dual-screened the search results. Extracted data on chatbot roles, users, benefits, and limitations were subjected to content analysis.

RESULTS

The review categorized chatbot roles into 2 themes: delivery of remote health services, including patient support, care management, education, skills building, and health behavior promotion, and provision of administrative assistance to health care providers. User groups spanned across patients with chronic conditions as well as patients with cancer; individuals focused on lifestyle improvements; and various demographic groups such as women, families, and older adults. Professionals and students in health care also emerged as significant users, alongside groups seeking mental health support, behavioral change, and educational enhancement. The benefits of health care chatbots were also classified into 2 themes: improvement of health care quality and efficiency and cost-effectiveness in health care delivery. The identified limitations encompassed ethical challenges, medicolegal and safety concerns, technical difficulties, user experience issues, and societal and economic impacts.

CONCLUSIONS

Health care chatbots offer a wide spectrum of applications, potentially impacting various aspects of health care. While they are promising tools for improving health care efficiency and quality, their integration into the health care system must be approached with consideration of their limitations to ensure optimal, safe, and equitable use.

Investigating the efficacy of digital cognitive behavioural therapy in comparison to a sleep-monitoring application via integrated diary and actigraphy: A randomised-controlled trial

Dissemination of digital cognitive behavioural therapy is a promising approach for treating insomnia in the broad population. Current evidence supports the effectiveness of the digital format, but clinical findings are often limited by the choice of control group and lack of in-depth therapeutic measures. This study was designed to investigate the specific effects of digital cognitive behavioural therapy in comparison to a self-monitoring application. Participants meeting criteria for insomnia were randomly allocated (1:1) to 8 weeks of digital cognitive behavioural therapy or 8 weeks of digital sleep monitoring (control application). The primary outcome, insomnia severity, was assessed at baseline, 8- and 16-weeks post-randomisation. Secondary outcomes included the assessment of sleep via application-integrated sleep diaries and actigraphy. Linear-mixed models were fitted to assess between-group differences. Fifty-six participants (48 females, mean age: M = 45.55 ± 13.70 years) were randomised to either digital cognitive behavioural therapy (n = 29) or digital sleep monitoring (n = 27). At 8- and 16-weeks post-randomisation, large treatment effects (d = 0.87-1.08) indicated robust reductions (-3.70 and -2.97, respectively; p ≤ 0.003) in insomnia severity in the digital cognitive behavioural therapy arm, relative to digital sleep monitoring. Treatment effects in favour of digital cognitive behavioural therapy were also found for self-reported and actigraphy-derived sleep continuity variables, indicating that sleep improved throughout the 8-week intervention period. Our study reinforces the role of digital cognitive behavioural therapy in achieving clinical improvements for patients with insomnia, affirming previous findings and supporting the specific effects of cognitive behavioural therapy.

Self-help interventions for persistent physical symptoms: a systematic review of behaviour change components and their potential effects

Persistent physical symptoms (PPS) remain a challenge in the healthcare system due to time-constrained consultations, uncertainty and limited specialised care capacity. Self-help interventions may be a cost-effective way to widen the access to treatment. As a foundation for future interventions, we aimed to describe intervention components and their potential effects in self-help interventions for PPS. A systematic literature search was made in PubMed, EMBASE, PsycINFO and CENTRAL. Fifty-one randomised controlled trials were included. Interventions were coded for effect on outcomes (standardised mean difference ≥0.2) related to symptom burden, anxiety, depression, quality of life, healthcare utilisation and sickness absence. The Behaviour Change Technique (BCT) Taxonomy v1 was used to code intervention components. An index of potential was calculated for each BCT within an outcome category. Each BCT was assessed as 'potentially effective' or 'not effective' based on a two-sided test for binomial random variables. Sixteen BCTs showed potential effect as treatment components. These BCTs represented the themes: goals and planning, feedback and monitoring, shaping knowledge, natural consequences, comparison of behaviour, associations, repetition and substitution, regulation, antecedents and identity. The results suggest that specific BCTs should be included in new PPS self-help interventions aiming to improve the patients' physical and mental health.

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 European Insomnia Guideline: An update on the diagnosis and treatment of insomnia 2023

Progress in the field of insomnia since 2017 necessitated this update of the European Insomnia Guideline. Recommendations for the diagnostic procedure for insomnia and its comorbidities are: clinical interview (encompassing sleep and medical history); the use of sleep questionnaires and diaries (and physical examination and additional measures where indicated) (A). Actigraphy is not recommended for the routine evaluation of insomnia (C), but may be useful for differential-diagnostic purposes (A). Polysomnography should be used to evaluate other sleep disorders if suspected (i.e. periodic limb movement disorder, sleep-related breathing disorders, etc.), treatment-resistant insomnia (A) and for other indications (B). Cognitive-behavioural therapy for insomnia is recommended as the first-line treatment for chronic insomnia in adults of any age (including patients with comorbidities), either applied in-person or digitally (A). When cognitive-behavioural therapy for insomnia is not sufficiently effective, a pharmacological intervention can be offered (A). Benzodiazepines (A), benzodiazepine receptor agonists (A), daridorexant (A) and low-dose sedating antidepressants (B) can be used for the short-term treatment of insomnia (≤ 4 weeks). Longer-term treatment with these substances may be initiated in some cases, considering advantages and disadvantages (B). Orexin receptor antagonists can be used for periods of up to 3 months or longer in some cases (A). Prolonged-release melatonin can be used for up to 3 months in patients ≥ 55 years (B). Antihistaminergic drugs, antipsychotics, fast-release melatonin, ramelteon and phytotherapeutics are not recommended for insomnia treatment (A). Light therapy and exercise interventions may be useful as adjunct therapies to cognitive-behavioural therapy for insomnia (B).

Digital Health Applications in the Area of Mental Health

BACKGROUND

The introduction of digital health applications (DiGA) is a fundamental innovation in Germany. In the field of mental health, numerous applications are already available whose efficacy has been tested in clinical trials. We investigated whether, and to what extent, the use of DiGA can be recommended on the basis of the available evidence.

METHODS

In this scoping review, we summarize the evidence supporting the use of DiGA in the mental health field through an examination of relevant publications that were retrieved by a systematic literature search. We provide an annotated tabular listing and discuss the current advantages of, and obstacles to, the care of mentally ill patients with the aid of DiGA.

RESULTS

We identified 17 DiGA for use in depression, anxiety disorders, addiction disorders, sleep disorders, stress/burnout, vaginismus, and chronic pain. These DiGA have been evaluated to date in 3 meta-analyses, 39 randomized controlled trials (RCTs), and two single-armed intervention trials. 23 of the 36 published trials were carried out with the direct participation of the manufacturers. 29 of the 39 RCTs were not blinded or contained no information regarding blinding. Active controls were used in 6 of the 39 RCTs. The reported effect sizes, with the exclusion of pre-post analyses, ranged from 0.16 to 1.79.

CONCLUSION

Most of the published studies display a high risk of bias, both because of the manufacturers' participation and because of methodological deficiencies. DiGA are an increasingly important therapeutic modality in psychiatry. The available evidence indicates that treatment effects are indeed present, but prospective comparisons with established treatments are still entirely lacking.

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.

[New Therapeutic Approaches for Chronic Insomnia]

Insomnia represents one of the most common syndromes with far-reaching health and socioeconomic consequences. After a long period of stagnation, recent years have seen promising advances in the nonpharmacological and pharmacological treatment of patients with chronic insomnia. This article highlights these new therapeutic approaches in the context of established treatment options.

Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours

Chatbots (also known as conversational agents and virtual assistants) offer the potential to deliver healthcare in an efficient, appealing and personalised manner. The purpose of this systematic review and meta-analysis was to evaluate the efficacy of chatbot interventions designed to improve physical activity, diet and sleep. Electronic databases were searched for randomised and non-randomised controlled trials, and pre-post trials that evaluated chatbot interventions targeting physical activity, diet and/or sleep, published before 1 September 2022. Outcomes were total physical activity, steps, moderate-to-vigorous physical activity (MVPA), fruit and vegetable consumption, sleep quality and sleep duration. Standardised mean differences (SMD) were calculated to compare intervention effects. Subgroup analyses were conducted to assess chatbot type, intervention type, duration, output and use of artificial intelligence. Risk of bias was assessed using the Effective Public Health Practice Project Quality Assessment tool. Nineteen trials were included. Sample sizes ranged between 25-958, and mean participant age ranged between 9-71 years. Most interventions (n = 15, 79%) targeted physical activity, and most trials had a low-quality rating (n = 14, 74%). Meta-analysis results showed significant effects (all p < 0.05) of chatbots for increasing total physical activity (SMD = 0.28 [95% CI = 0.16, 0.40]), daily steps (SMD = 0.28 [95% CI = 0.17, 0.39]), MVPA (SMD = 0.53 [95% CI = 0.24, 0.83]), fruit and vegetable consumption (SMD = 0.59 [95% CI = 0.25, 0.93]), sleep duration (SMD = 0.44 [95% CI = 0.32, 0.55]) and sleep quality (SMD = 0.50 [95% CI = 0.09, 0.90]). Subgroup analyses showed that text-based, and artificial intelligence chatbots were more efficacious than speech/voice chatbots for fruit and vegetable consumption, and multicomponent interventions were more efficacious than chatbot-only interventions for sleep duration and sleep quality (all p < 0.05). Findings from this systematic review and meta-analysis indicate that chatbot interventions are efficacious for increasing physical activity, fruit and vegetable consumption, sleep duration and sleep quality. Chatbot interventions were efficacious across a range of populations and age groups, with both short- and longer-term interventions, and chatbot only and multicomponent interventions being efficacious.

Evidence requirements of permanently listed digital health applications (DiGA) and their implementation in the German DiGA directory: an analysis

BACKGROUND

With its digital health application (DiGA)-system, Germany is considered one of Europe's pioneers in the field of evidence-based digital health. Incorporating DiGA into standard medical care must be based on evidence-based success factors; however, a comprehensive overview of the evidence required of scientific studies for their approval is lacking.

OBJECTIVE

The study aims to, (1) identify specific requirements defined by the Federal Institute for Drugs and Medical Devices (German: Bundesinstitut für Arzneimittel- und Medizinprodukte; BfArM) to design adequate studies, proving a positive healthcare effect, and (2) to assess the evidence given for applications permanently listed in the DiGA directory.

METHODS

A multi-step approach was used: (1) identification of the evidence requirements for applications permanently listed in the DiGA directory, (2) identification of the evidence available supporting them.

RESULTS

All DiGA permanently listed in the DiGA directory (13 applications) are included in the formal analysis. Most DiGA addressed mental health (n = 7), and can be prescribed for one or two indications (n = 10). All permanently listed DiGA have demonstrated their positive healthcare effect through a medical benefit, and most of them provide evidence for one defined primary endpoint. All DiGA manufacturers conducted a randomized controlled trial.

DISCUSSION

It is striking that- although patient-relevant structural and procedural improvements show high potential for improving care, especially in terms of processes - all DiGA have provided a positive care effect via a medical benefit. Although BfArM accepts study designs with a lower level of evidence for the proof of a positive healthcare effect, all manufacturers conducted a study with a high level of evidence.

CONCLUSION

The results of this analysis indicate that permanently listed DiGA meet higher standards than required by the guideline.

Digital cognitive behavioral therapy for insomnia on depression and anxiety: a systematic review and meta-analysis

Despite research into the development of digital cognitive behavioral therapy for insomnia (dCBT-I), research into the outcomes of dCBT-I on insomnia and the associated clinical conditions of depression and anxiety have been limited. The PubMed, PsycINFO (Ovid), Embase, and Cochrane databases were searched for randomized controlled trials (RCTs) on adult patients with insomnia also having reported measures of depressive or anxiety symptoms. In total, 2504 articles were identified after duplicate removal, and 22 RCTs were included in the final meta-analysis. At the post-treatment assessment, the dCBT-I group had a small to moderate effect in alleviating depressive (standardized mean difference (SMD) = -0.42; 95% CI: -0.56, -0.28; p < 0.001; k = 21) and anxiety symptoms (SMD = -0.29; 95% CI: -0.40, -0.19; p < 0.001; k = 18), but had a large effect on sleep outcome measures (SMD = -0.76; 95% CI: -0.95, -0.57; p < 0.001; k = 22). When considering treatment adherence, the treatment effects of those in the high adherent groups identified a more robust outcome, showing greater effect sizes than those in the low adherent groups for depression, anxiety, and sleep outcomes. Furthermore, additional subgroup analysis on studies that have used the fully automated dCBT-I treatment without the support of human therapists reported significant treatment effects for depression, anxiety, and sleep outcomes. The results demonstrated that digital intervention for insomnia yielded significant effects on alleviating depressive and anxiety symptoms as well as insomnia symptoms. Specifically, the study demonstrated significant effects on the above symptoms when considering treatment adherence and implementing fully automated dCBT-I.

Effectiveness of an App-Based Short Intervention to Improve Sleep: Randomized Controlled Trial

BACKGROUND

A growing body of evidence for digital interventions to improve sleep shows promising effects. The interventions investigated so far have been primarily web-based; however, app-based interventions may reach a wider audience and be more suitable for daily use.

OBJECTIVE

This study aims to evaluate the intervention effects, adherence, and acceptance of an unguided app-based intervention for individuals who wish to improve their sleep.

METHODS

In a randomized controlled trial, we evaluated the effects of an app-based short intervention (Refresh) to improve sleep compared with a waitlist condition. Refresh is an 8-week unguided intervention covering the principles of cognitive behavioral therapy for insomnia (CBT-I) and including a sleep diary. The primary outcome was sleep quality (insomnia symptoms) as self-assessed by the Regensburg Insomnia Scale (RIS). The secondary outcomes were depression (9-item Patient Health Questionnaire [PHQ-9] score) and perceived insomnia-related impairment.

RESULTS

We included 371 participants, of which 245 reported poor sleep at baseline. About 1 in 3 participants who were allocated to the intervention group never accessed the intervention. Active participants completed on average 4 out of 8 chapters. Retention rates were 67.4% (n=250) at postassessment and 57.7% (n=214) at the 6-month follow-up. At postintervention, insomnia symptoms in the intervention group had improved more than those in the waitlist group, with a small effect (d=0.26) in the whole sample and a medium effect (d=0.45) in the subgroup with poor sleep. Effects in the intervention group were maintained at follow-up. Perceived insomnia-related impairment also improved from pre- to postassessment. No significant intervention effect on depression was detected. Working alliance and acceptance were moderate to good.

CONCLUSIONS

An app-based, unguided intervention is a feasible and effective option to scale-up CBT-I-based treatment, but intervention uptake and adherence need to be carefully addressed.

TRIAL REGISTRATION

ISRCTN Registry ISRCTN53553517; https://www.isrctn.com/ISRCTN53553517.

eHealth-Based Psychosocial Interventions for Adults With Insomnia: Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND

Worldwide, insomnia remains a highly prevalent public health problem. eHealth presents a novel opportunity to deliver effective, accessible, and affordable insomnia treatments on a population-wide scale. However, there is no quantitative integration of evidence regarding the effectiveness of eHealth-based psychosocial interventions on insomnia.

OBJECTIVE

We aimed to evaluate the effectiveness of eHealth-based psychosocial interventions for insomnia and investigate the influence of specific study characteristics and intervention features on these effects.

METHODS

We searched PubMed, Embase, Web of Science, PsycINFO, and the Cochrane Central Register of Controlled Trials from database inception to February 16, 2021, for publications investigating eHealth-based psychosocial interventions targeting insomnia and updated the search of PubMed to December 6, 2021. We also screened gray literature for unpublished data. Eligible studies were randomized controlled trials of eHealth-based psychosocial interventions targeting adults with insomnia. Random-effects meta-analysis models were used to assess primary and secondary outcomes. Primary outcomes were insomnia severity and sleep quality. Meta-analyses were performed by pooling the effects of eHealth-based psychosocial interventions on insomnia compared with inactive and in-person conditions. We performed subgroup analyses and metaregressions to explore specific factors that affected the effectiveness. Secondary outcomes included sleep diary parameters and mental health-related outcomes.

RESULTS

Of the 19,980 identified records, 37 randomized controlled trials (13,227 participants) were included. eHealth-based psychosocial interventions significantly reduced insomnia severity (Hedges g=-1.01, 95% CI -1.12 to -0.89; P<.001) and improved sleep quality (Hedges g=-0.58, 95% CI -0.75 to -0.41; P<.001) compared with inactive control conditions, with no evidence of publication bias. We found no significant difference compared with in-person treatment in alleviating insomnia severity (Hedges g=0.41, 95% CI -0.02 to 0.85; P=.06) and a significant advantage for in-person treatment in enhancing sleep quality (Hedges g=0.56, 95% CI 0.24-0.88; P<.001). eHealth-based psychosocial interventions had significantly larger effects (P=.01) on alleviating insomnia severity in clinical samples than in subclinical samples. eHealth-based psychosocial interventions that incorporated guidance from trained therapists had a significantly greater effect on insomnia severity (P=.05) and sleep quality (P=.02) than those with guidance from animated therapists or no guidance. Higher baseline insomnia severity and longer intervention duration were associated with a larger reduction in insomnia severity (P=.004). eHealth-based psychosocial interventions significantly improved each secondary outcome.

CONCLUSIONS

eHealth interventions for insomnia are effective in improving sleep and mental health and can be considered a promising treatment for insomnia. Our findings support the wider dissemination of eHealth interventions and their further promotion in a stepped-care model. Offering blended care could improve treatment effectiveness. Future research needs to elucidate which specific intervention components are most important to achieve intervention effectiveness. Blended eHealth interventions may be tailored to benefit people with low socioeconomic status, limited access to health care, or lack of eHealth literacy.

[Critical Evaluation of Permanently Listed Psychosocial Digital Health Applications into the Directory for Reimbursable Digital Health Applications of the BfArM]

Digital health applications (DiGA) delivered as psychosocial therapeutic interventions entail a huge potential through their proven medical benefit or patient-relevant structure and process improvements. Their usage as first-line or concomitant therapy is refunded by the German health insurances. Therefore, the digital health applications have to pass a complex evidence process as requested by the Federal Institute for Drugs and Medical Services. The present article aimed at critically evaluating the available evidence of the permanently registered DiGA using the Critically Appraised Topic method. In conclusion, all studies fulfil at least two thirds of the evaluation criteria, implying that the overall evidence is of sufficient quality.

[Digital health applications in otorhinolaryngology]

BACKGROUND

With the passing of the "Digital Care Act" by the German Bundestag at the end of 2019, it was made possible, among other things, for digital health applications to be reimbursed by statutory health insurance companies under certain conditions. The aim of this work is to identify digital health applications related to ear, nose, and throat medicine and to describe the underlying evidence.

MATERIALS AND METHODS

The digital health applications register was analyzed to identify digital health applications with an indication area relating to an otorhinolaryngologic disease. Digital health applications were included that were either permanently or provisionally included, or currently deleted if further information was available. The underlying evidence was assessed according to the recommendations of the Oxford Center for Evidence-Based Medicine for therapeutic studies.

RESULTS

A total of six digital health applications with a direct or indirect connection to otorhinolaryngology were identified, three of which were permanently and two provisionally included in the directory. One digital health application has currently been withdrawn by the manufacturer. The permanently recorded digital health applications are based on evidence level 1b.

CONCLUSION

The introduction of digital health applications is sometimes also discussed critically, but they represent an innovative approach and various digital health applications with a high level of underlying evidence are already available, especially for the ear, nose, and throat area.

Comparative efficacy of onsite, digital, and other settings for cognitive behavioral therapy for insomnia: a systematic review and network meta-analysis

Given the limited availability and accessibility of onsite cognitive behavioral therapy for insomnia (CBT-I), other CBT-I settings, such as internet-delivered CBT-I (iCBT-I), have been proposed. The primary aim of the study was to compare the efficacy of available CBT-I settings on insomnia severity. A systematic review and frequentist network meta-analysis of available CBT-I settings was performed. PsycINFO, PsycARTICLES, MEDLINE, PubMed, and CINAHL were searched for randomized controlled trials (RCTs) investigating any CBT-I settings in adults with insomnia disorder. The systematic literature search (3851 references) resulted in 52 RCTs. For the primary outcome insomnia severity, all examined CBT-I settings except smartphone-delivered CBT-I yielded significant effects when compared to WL. Large standardized mean differences were found for individual onsite CBT-I (- 1.27;95%CI - 1.70, - 0.84), group-delivered CBT-I (- 1.00;95%CI - 1.42. - 0.59), telehealth (- 1.28;95%CI - 2.06, - 0.50), and guided bibliotherapy (- 0.99;95%CI - 1.67, - 0.32). Both guided iCBT-I (- 0.71;95%CI - 1.18, - 0.24) and unguided iCBT-I (- 0.78;95%CI - 1.18, - 0.38) yielded medium effect sizes. The results underline that health care systems should intensify their efforts to provide synchronously-delivered CBT-I (individual onsite, group-delivered, and telehealth), and particularly individual onsite CBT-I, given its solid evidence base. Medium to large effect sizes for iCBT-I and guided bibliotherapy indicate that self-help settings may be a viable alternative when synchronously-delivered CBT-I is not available.

Help for insomnia from the app store? A standardized rating of mobile health applications claiming to target insomnia

A large number of mobile health applications claiming to target insomnia are available in commercial app stores. However, limited information on the quality of these mobile health applications exists. The present study aimed to systematically search the European Google Play and Apple App Store for mobile health applications targeting insomnia, and evaluate the quality, content, evidence base and potential therapeutic benefit. Eligible mobile health applications were evaluated by two independent reviewers using the Mobile Application Rating Scale-German, which ranges from 1 - inadequate to 5 - excellent. Of 2236 identified mobile health applications, 53 were included in this study. Most mobile health applications (68%) had a moderate overall quality. Concerning the four main subscales of the Mobile Application Rating Scale-German, functionality was rated highest (M = 4.01, SD = 0.52), followed by information quality (M = 3.49, SD = 0.72), aesthetics (M = 3.31, SD = 1.04) and engagement (M = 3.02, SD = 1.03). While scientific evidence was identified for 10 mobile health applications (19%), only one study employed a randomized controlled design. Fifty mobile health applications featured sleep hygiene/psychoeducation (94%), 27 cognitive therapy (51%), 26 relaxation methods (49%), 24 stimulus control (45%), 16 sleep restriction (30%) and 24 sleep diaries (45%). Mobile health applications may have the potential to improve the care of insomnia. Yet, data on the effectiveness of mobile health applications are scarce, and this study indicates a large variance in the quality of the mobile health applications. Thus, independent information platforms are needed to provide healthcare seekers and providers with reliable information on the quality and content of mobile health applications.

The Role of Dysfunctional Sleep Beliefs in Mediating the Outcomes of Web-Based Cognitive Behavioral Therapy for Insomnia in Community-Dwelling Older Adults: Protocol for a Single-Group, Nonrandomized Trial

BACKGROUND

Sleeping well is an essential part of good health. Older adult populations report a high rate of sleep problems, with recent studies suggesting that cognitive processes as well as behavioral and hyperarousal-related mechanisms could be important factors in the development and maintenance of insomnia. Individuals who have an asynchronous or uncoupled sleep pattern and sleep appraisal-those who complain about their sleep but do not have poor sleep quality, and vice versa-might show differences in subjective sleep and sleep perceptions and other characteristics that could impact their treatment outcomes following cognitive behavioral therapy for insomnia (CBT-I).

OBJECTIVE

The purpose of this protocol is to describe the rationale and methods for a nonrandomized, single-arm trial assessing objective and subjective sleep quality in community-dwelling older adults aged 60-80 years with synchronous sleep patterns and sleep appraisal compared to those in older adults with asynchronous sleep patterns and sleep appraisal. The trial will further examine the role of cognitive, behavioral, and hyperarousal processes in mediating the treatment outcomes of web-based CBT-I.

METHODS

This trial aims to recruit a sample of 60 participants, who will be assigned to 1 of 4 sleep groups based on their sleep pattern and sleep appraisal status: complaining good sleepers, complaining poor sleepers, noncomplaining good sleepers, and noncomplaining poor sleepers, respectively. The trial will be completed in 2 phases: phase 1 will assess objective sleep (measured via wrist actigraphy) and subjective (self-reported) sleep. Phase 2 will investigate the impact of a web-based CBT-I program on the sleep outcomes of individuals with uncoupled sleep compared to that of individuals without uncoupled sleep, as well as the mediators of CBT-I.

RESULTS

Recruitment began in March 2020, and the last participants were recruited by March 2021. A total of 65 participants completed phases 1 and 2. Data analysis for phase 1 was finished in December 2021, and data analysis for phase 2 was finalized in July 2022. The results for phase 1 were submitted for publication in March 2022, and those for phase 2 will be submitted by the end of December 2022.

CONCLUSIONS

This trial will provide guidance on factors that contribute to the variability of sleep in older adults and their sleep outcomes following CBT-I. The outcomes of this study could be valuable for future research attempting to tailor CBT-I to individual needs.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12619001509156; https://tinyurl.com/69hhdu2w.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/32705.

Efficacy of the Digital Therapeutic sinCephalea in the prophylaxis of migraine in patients with episodic migraine: study protocol for a digital, randomized, open-label, standard treatment controlled trial

BACKGROUND

The German government implemented the Digital Healthcare Act in order to bring Digital Therapeutics into standard medical care. This is one of the first regulatory pathways to reimbursement for Digital Therapeutics (DTx). The Digital Therapeutic sinCephalea is intended to act as a prophylactic treatment of migraine by reducing the migraine days. For this, sinCephalea determines personalized nutritional recommendations using continuous glucose monitoring (CGM) data and enables the patients to follow a personalized low-glycemic nutrition. Migraine is a headache disorder with the highest socioeconomic burden. Emerging evidence shows that CGM-based personalized nutritional recommendations are of prophylactic use in episodic migraine. However, prospective data are yet missing to demonstrate clinical effectiveness. This study is designed to fill this gap.

METHODS

Patients between 18 and 65 years of age with proven migraine and a minimal disease severity of 3 migraine days per month are included. After a 4-week baseline phase as a pre-study, patients are randomized to the DTx intervention or a waiting-list control. The objective of the study is to show differences between the intervention and control groups regarding the change of migraine symptoms and of effects of migraine on daily life.

DISCUSSION

To our knowledge, this is the first systematic clinical trial with a fully digital program to enable patients with migraine to follow a personalized low-glycemic nutrition in order to reduce their number of migraine days and the migraine-induced impact on daily life. Designing a clinical study using a digital intervention includes some obstacles, which are addressed in this study approach.

TRIAL REGISTRATION

German Registry of Clinical Studies (Deutsches Register Klinischer Studien) DRKS-ID DRKS00024657. Registered on March 8, 2021.

[How robust are studies of currently permanently included digital health applications (DiGA)? Methodological quality of studies demonstrating positive health care effects of DiGA]

INTRODUCTION

Since September 2020 digital health applications (DiGA) can be prescribed by physicians and psychotherapists and are reimbursed within the German Statutory Health Insurance (SHI) system for the first time worldwide. For full reimbursement, the manufacturers have to provide evidence based on scientific studies that the DiGA can provide 'positive health care effects'. This study aims to analyze and evaluate the methodological quality of efficacy studies of DiGA in the categories 'Nervensystem' and 'Psyche' of the DiGA register that are permanently accepted.

METHODS

The methodological quality was assessed using the revised Cochrane risk-of-bias tool for randomized trials (RoB 2). The risk of bias was assessed for the primary endpoint of each study according to an intention-to-treat analysis.

RESULTS

Six DiGA were assessed for their methodological quality. Randomized controlled trials were conducted for all 6 DiGA that showed a high risk of bias, which was, in particular, due to a lack of blinding of the studies. In addition, drop-outs were significantly higher in the intervention group than in the control group in most studies. For most of the DiGA no published study protocol was available in advance so an analysis of a potential selective choice of the evaluation methodology was not possible.

DISCUSSION

For reasons of transparency, verifiability, and comprehensibility of the study results, registration in a study registry and, more importantly, the publication of study protocols should be mandatory before the start of the studies. In addition, studies should be blinded by comparing the DiGA with a 'sham application' to reduce the high risk of bias. Differences in the drop-out rates of the investigated studies could indicate a lack of efficacy of the treatment in the intervention group, (technical) problems in the application of the DiGA, or a lack of motivation of the participants.

CONCLUSION

The interim results 18 months after the introduction of DiGA in the German SHI system show that the studies on the evidence of the benefits of DiGA have a high potential for bias in certain areas. However, it should be positively emphasized that the manufacturers submitted randomized controlled trials to prove the medical benefit of the DiGAs investigated.

Network meta-analysis comparing the effectiveness of a prescription digital therapeutic for chronic insomnia to medications and face-to-face cognitive behavioral therapy in adults

OBJECTIVE

The purpose of this study was to compare the effectiveness of the only Food and Drug Administration-authorized prescription digital therapeutic (PDT) Somryst versus face-to-face cognitive behavioral therapy for insomnia (CBT-I), or FDA-approved prescription medications for insomnia.

METHODS

A systematic literature review was undertaken to identify relevant studies. A Bayesian network meta-analysis (NMA) was conducted to examine (1) mean change in insomnia severity index (ISI); (2) proportional change in ISI remitters; (3) mean change in wake after sleep onset (WASO); and (4) mean change in sleep onset latency (SOL).

RESULTS

Twenty studies provided data on the PDT, CBT-I, CBT-I in combination with self-help (SH), or two prescription medications (eszopiclone and zolpidem). The PDT was associated with significant mean change in ISI (-5.77, 95% Credible Interval [CrI] - 8.53, -3.07) and ISI remitters (OR 12.33; 95% CrI 2.28, 155.91) compared to placebo, and had the highest probability of being the most effective treatment overall for ISI mean change (56%), and ISI remitters (64%). All evaluated interventions significantly outperformed placebo for WASO but no significant differences were observed for SOL (five interventions). Sensitivity analyses excluding medications and meta-regression (assessing type, duration, delivery method for CBT-I) did not affect NMA results.

CONCLUSIONS

This network meta-analysis demonstrated that a PDT delivering CBT-I had the highest probability of being most effective compared to face-to-face CBT-I, prescription sleep medications, or placebo, as measured by reductions in mean ISI score from baseline and ISI-determined remittance.

Digital health applications and the fast-track pathway to public health coverage in Germany: challenges and opportunities based on first results

Objectives

Evidence-based decision-making is the sine qua non for safe and effective patient care and the long-term functioning of health systems. Since 2020 Digital Health Applications (DiHA) in Germany have been undergoing a systematic pathway to be reimbursed by statutory health insurance (SHI) which is attracting attention in other European countries. We therefore investigate coverage decisions on DiHA and the underlying evidence on health care effects, which legally include both medical outcomes and patient-centred structural and procedural outcomes.

Methods

Based on publicly available data of the Institute for Medicines and Medical Devices searched between 08/2021 and 02/2022, all DiHA listed in the corresponding registry and thus reimbursable by the SHI were systematically investigated and presented descriptively on the basis of predefined criteria, such as clinical condition, and costs. The clinical trials on DiHA permanently included in the registry were reviewed with regard to their study design, endpoints investigated, the survey instruments used, and whether an intention-to-treat analysis was performed. Risk of bias was assessed using the ROB II tool.

Results

By February 2022, 30 DiHA had been included in the DiHA registry, one third of them permanently and two thirds conditionally. Most DiHA were therapeutic applications for mental illness based on cognitive behavioural therapy. For all permanently included DiHA, randomised controlled trials were conducted to demonstrate the impact on health care effects. While medical outcomes were investigated for all of these DiHA, patient-centred structural and procedural outcomes were rarely investigated. The majority of clinical trials showed a high risk of bias, mainly due to insufficient reporting quality. Overall, the prices for DiHA covered by SHI are on average around € 150 per month (min. € 40; max. € 248).

Conclusions

Evidence-based decision-making on coverage of DiHA leaves room for improvements both in terms of reporting-quality and the use of patient-centred structural and procedural outcomes in addition to medical outcomes. With appropriate evidence, DiHA can offer an opportunity as an adjunct to existing therapy while currently the high risk of bias of the trials raises doubts about the justification of its high costs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08500-6.

Physicians' Attitudes Toward Prescribable mHealth Apps and Implications for Adoption in Germany: Mixed Methods Study

Background

In October 2020, Germany became the first country, worldwide, to approve certain mobile health (mHealth) apps, referred to as DiGA (Digitale Gesundheitsanwendungen, in German, meaning digital health applications), for prescription with costs covered by standard statutory health insurance. Yet, this option has only been used to a limited extent so far.

Objective

The aim of this study was to investigate physicians’ and psychotherapists’ current attitudes toward mHealth apps, barriers to adoption, and potential remedies.

Methods

We conducted a two-stage sequential mixed methods study. In phase one, semistructured interviews were conducted with physicians and psychotherapists for questionnaire design. In phase two, an online survey was conducted among general practitioners, physicians, and psychotherapists.

Results

A total of 1308 survey responses by mostly outpatient-care general practitioners, physicians, and psychotherapists from across Germany who could prescribe DiGA were recorded, making this the largest study on mHealth prescriptions to date. A total of 62.1% (807/1299) of respondents supported the opportunity to prescribe DiGA. Improved adherence (997/1294, 77.0%), health literacy (842/1294, 65.1%), and disease management (783/1294, 60.5%) were most frequently seen as benefits of DiGA. However, only 30.3% (393/1299) of respondents planned to prescribe DiGA, varying greatly by medical specialty. Professionals are still facing substantial barriers, such as insufficient information (1135/1295, 87.6%), reimbursement for DiGA-related medical services (716/1299, 55.1%), medical evidence (712/1298, 54.9%), legal uncertainties (680/1299, 52.3%), and technological uncertainties (658/1299, 50.7%). To support professionals who are unsure of prescribing DiGA, extended information campaigns (1104/1297, 85.1%) as well as recommendations from medical associations (1041/1297, 80.3%) and medical colleagues (1024/1297, 79.0%) were seen as the most impactful remedies.

Conclusions

To realize the benefits from DiGA through increased adoption, additional information sharing about DiGA from trusted bodies, reimbursement for DiGA-related medical services, and further medical evidence are recommended.

Comparative efficacy of digital cognitive behavioral therapy for insomnia: A systematic review and network meta-analysis

The comparative efficacy of various approaches of digital cognitive behavioral therapy for insomnia (CBTi) is still unclear. This network meta-analysis explored the comparative efficacy of digital CBTi approaches in adults with insomnia. Four electronic databases were searched from inception to June 27, 2020. Primary outcomes were self-reported total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), sleep efficiency (SE), and insomnia symptoms; these were measured using sleep diaries or valid questionnaires. A random-effects network meta-analysis in a frequentist framework was used. Fifty-four randomized controlled trials comprising 11,815 participants were included. Compared with usual care, web-based CBTi with a therapist demonstrated significantly longer TST (mean difference [MD]: 23.19 min, 95% confidence interval [CI]: 18.98-27.39 min), shorter SOL (MD: -18.76 min, 95% CI -24.20 to -13.31 min), lower WASO (MD: -31.40 min, 95% CI: -36.26 to -26.55 min), and greater SE (MD: 10.37%, 95% CI: 8.08%-12.65%). The surface under the cumulative ranking curve indicates that web-based CBTi with therapists is most likely to be ranked the highest among all treatments, and thus, this network meta-analysis suggests that such a treatment is the optimal intervention for improving sleep duration and SE as well as the reductions in SOL and WASO. PROSPERO REGISTRATION NUMBER: CRD42020171134.

A Review of Virtual Coaching Systems in Healthcare: Closing the Loop With Real-Time Feedback

This review focuses on virtual coaching systems that were designed to enhance healthcare interventions, combining the available sensing and system-user interaction technologies. In total, more than 1,200 research papers have been retrieved and evaluated for the purposes of this review, which were obtained from three online databases (i.e.,PubMed, Scopus and IEEE Xplore) using an extensive set of search keywords. After applying exclusion criteria, the remaining 41 research papers were used to evaluate the status of virtual coaching systems over the past 10 years and assess current and future trends in this field. The results suggest that in home coaching systems were mainly focused in promoting physical activity and a healthier lifestyle, while a wider range of medical domains was considered in systems that were evaluated in lab environment. In home patient monitoring with IoT devices and sensors was mostly limited to activity trackers, pedometers and heart rate monitoring. Real-time evaluations and personalized patient feedback was also found to be rather lacking in home coaching systems and this is the most alarming find of this analysis. Feasibility studies in controlled environment and an ongoing active research on Horizon 2020 funded projects, show that the future trends in this field are aiming to close the loop with automated patient monitoring, real-time evaluations and more precise interventions.

Do non-pharmacological sleep interventions affect anxiety symptoms? A meta-analysis

Research indicates a bidirectional relationship between sleep and anxiety, with findings suggesting anxiety can precede poor sleep and vice versa. Evidence suggests sleep-related thought processes associated with anxiety are involved in the maintenance of insomnia. Previous meta-analyses provide some evidence to suggest cognitive behavioural therapy for insomnia moderately improves anxiety, yet little research has investigated the effect of other sleep interventions on anxiety symptoms. The aim of this meta-analysis was to review whether non-pharmacological sleep interventions have an impact on anxiety symptoms immediately post-intervention. A systematic search of electronic databases was conducted to identify all randomized control trials (RCTs) investigating non-pharmacological sleep interventions that included anxiety symptoms as an outcome. Forty-three RCTs (n = 5945) met full inclusion criteria and were included in a random-effects meta-analysis model. The combined effect size of non-pharmacological sleep interventions on anxiety symptoms was moderate (Hedges' g = -0.38), indicating a reduction in symptoms. Subgroup analyses found a moderate effect for those with additional physical health difficulties (g = -0.46), a moderate effect for those with additional mental health difficulties (g = -0.47) and a moderate effect for those with elevated levels of anxiety at baseline (g = -0.43). A secondary meta-analysis found a large effect of non-pharmacological sleep interventions on sleep-related thought processes (g = -0.92). These findings indicate non-pharmacological sleep interventions are effective in reducing anxiety and sleep-related thought processes, and these effects may be larger in patients with anxiety. This has clinical implications for considering sleep interventions in the treatment of anxiety.

An investigation and replication of sleep-related cognitions, acceptance and behaviours as predictors of short- and long-term outcome in cognitive behavioural therapy for insomnia

The objectives were to investigate the potential for sleep-related behaviours, acceptance and cognitions to predict outcome (insomnia severity) of cognitive behavioural therapy for insomnia (CBT-I). Baseline and outcome data from four randomised controlled trials (n = 276) were used. Predictors were the Dysfunctional Beliefs and Attitudes about Sleep-10 (DBAS-10), Sleep-Related Behaviours Questionnaire (SRBQ), and Sleep Problems Acceptance Questionnaire (SPAQ), and empirically derived factors from a factor analysis combining all items at baseline (n = 835). Baseline values were used to predict post-treatment outcome, and pre-post changes in the predictors were used to predict follow-up outcomes after 3-6 months, 1 year, or 3-10 years, measured both as insomnia severity and as better or worse long-term sleep patterns. A majority (29 of 52) of predictions of insomnia severity were significant, but when controlling for insomnia severity, only two (DBAS-10 at short-term and SRBQ at mid-term follow-up) of the 12 predictions using established scales, and three of the 40 predictions using empirically derived factors, remained significant. The strongest predictor of a long-term, stable sleep pattern was insomnia severity reduction during treatment. Using all available predictors in an overfitted model, 21.2% of short- and 58.9% of long-term outcomes could be predicted. We conclude that although the explored constructs may have important roles in CBT-I, the present study does not support that the DBAS-10, SRBQ, SPAQ, or factors derived from them, would be unique predictors of outcome.

Effectiveness of online psychological and psychoeducational interventions to prevent depression: Systematic review and meta-analysis of randomized controlled trials

Although evidence exists for the efficacy of interventions to prevent depression, little is known about its prevention through online interventions. We aim to assess the effectiveness of online psychological and psychoeducational interventions to prevent depression in heterogeneous populations. A systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted based on literature searches in eight electronic data bases and other sources from inception to 22 July 2019. Of the 4181 abstracts reviewed, 501 were selected for full-text review, and 21 RCTs met the inclusion criteria, representing 10,134 participants from 11 countries and four continents. The pooled SMD was -0·26 (95%CI: -0·36 to -0·16; p < 0.001) and sensitivity analyses confirmed the robustness of this result. We did not find publication bias but there was substantial heterogeneity (I² = 72%; 95%CI, 57% to 82%). A meta-regression including three variables explained 81% of the heterogeneity. Indicated prevention and interactive website delivery were statistically associated with higher effectiveness, and no association was observed with risk of bias. Online psychological and psychoeducational interventions have a small effect in reducing depressive symptoms in non-depressed and varied populations, and the quality of evidence is moderate. Given that these types of interventions are very accessible and can be applied on a wide scale, they should be further developed and implemented. Registration details: Registration number (PROSPERO): CRD42014014804.

Does cognitive behaviour therapy for insomnia reduce repetitive negative thinking and sleep-related worry beliefs? A systematic review and meta-analysis

Repetitive negative thinking (RNT), i.e., worry, rumination, and transdiagnostic repetitive thinking, is thought to exacerbate and perpetuate insomnia in cognitive models. Moreover, RNT is a longitudinal precursor of depression and anxiety, which are often co-present alongside insomnia. Whilst accumulating evidence supports the efficacy of cognitive behavioural therapy for insomnia (CBT-I) in reducing depression and anxiety symptoms, the literature on the effects of CBT-I on RNT has never been systematically appraised. Importantly, preliminary evidence suggests that reduction of RNT following CBT-I may be associated with reduction of depression and anxiety. Therefore, we aimed to conduct a systematic review and meta-analysis on the effects of CBT-I on RNT. Seven databases were searched, and 15 randomised controlled trials were included. Results showed moderate-to-large effects of CBT-I on worry (Hedge's g range: -0.41 to g = -0.71) but small and non-reliable effects on rumination (g = -0.13). No clear evidence was found for an association between post-treatment reduction in RNT and post-treatment reduction in depression and anxiety. Although the literature is small and still developing, CBT-I seems to have a stronger impact on sleep-related versus general measures of RNT. We discuss a research agenda aimed at advancing the study of RNT in CBT-I trials.

Efficacy of digital cognitive behavioural therapy for insomnia: a meta-analysis of randomised controlled trials

OBJECTIVES

Although cognitive behavioural therapy for insomnia (CBT-I) has been recommended the initial therapy for insomnia, its clinical usage remains limited due to the lack of therapists. Digital CBT-I (dCBT-I) can potentially circumvent this problem. This meta-analysis aims to evaluate the short-term and long-term efficacy of dCBT-I for adults with insomnia.

METHODS

Systematic search of PubMed, EMBASE, PsycINFO, and CENTRAL from inception till 5 March 2020 was conducted. Randomised controlled trials (RCTs) comparing dCBT-I with controls (wait-list/treatment-as-usual/online education) in adults with insomnia were eligible. The primary outcome was insomnia severity index (ISI) at post-intervention, short-term follow-up (ranging 4 weeks to 6 months) and 1-year follow-up. Mean differences were pooled using the random-effects model.

RESULTS

94 articles were assessed full-text independently by two team members and 33 studies were included in this meta-analysis. 4719 and 4645 participants were randomised to dCBT-I and control respectively. dCBT-I significantly reduces ISI at post-intervention with mean difference -5.00 (95% CI -5.68 to -4.33, p < 0.0001) (I² = 79%) compared to control. The improvements were sustained at short-term follow-up, -3.99 (95% CI -4.82 to -3.16, p < 0.0001) and 1-year follow-up, -3.48 (95% CI -4.21 to -2.76, p < 0.0001). Compared to dCBT-I, face-to-face CBT-I produced greater improvement in ISI, 3.07 (95% CI 1.18 to 4.95, p = 0.001). However, this was within the non-inferiority interval of 4 points on ISI.

CONCLUSION

This meta-analysis provides strong support for the effectiveness of dCBT-I in treating insomnia. dCBT-I has potential to revolutionise the delivery of CBT-I, improving the accessibility and availability of CBT-I content for insomnia patients worldwide.

The Clinical Effectiveness of Cognitive Behavioral Therapy for Patients with Insomnia and Depression: A Systematic Review and Meta-Analysis

BACKGROUND

Insomnia and depression often co-occurr. However, there is lack of effective treatment for such comorbidity. CBT-I has been recommended as the first-line treatment for insomnia; whether it is also effective for comorbidity of insomnia and depression is still unknown. Therefore, we conducted this meta-analysis of randomized controlled trials to assess the clinical effectiveness and safety of CBT-I for insomnia comorbid with depression. Data Sources. Seven electronic databases, including China National Knowledge Infrastructure (CNKI), Wanfang Database, China Science Technology Journal Database, SinoMed Database, PubMed, the Cochrane Library, and EMBASE, as well as grey literature, were searched from the beginning of each database to July 1, 2019. Study Eligibility Criteria. Randomized controlled trials that compared CBT-I to no treatment or hypnotics (zopiclone, estazolam, and benzodiazepine agonist) for insomnia comorbid with depression and reported both insomnia scales and depression scales. Study Assessment and Synthesis Methods. Cochrane Reviewer's Handbook was used for evaluating the risk of bias of included studies. Review Manager 5.3 software was used for meta-analysis. Online GRADEpro was used to assess the quality of evidence.

RESULTS

The pooled data showed that CBT-I was superior to no treatment for insomnia, while it was unsure whether CBT-I was better than no treatment for depression. And the effectiveness of CBT-I was comparable to hypnotics for both insomnia and depression. CBT-I was likely to be safe due to its noninvasive nature. The methodological quality varied across these trials. The evidence quality varied from moderate to very low, and the recommendation level was low.

CONCLUSIONS

Currently, findings support that CBT-I seems to be effective and safe for insomnia comorbid with depression to improve the insomnia condition, while it is unsure whether CBT-I could improve depression condition. More rigorous trials are needed to confirm our findings.

Temporal Associations of Daily Changes in Sleep and Depression Core Symptoms in Patients Suffering From Major Depressive Disorder: Idiographic Time-Series Analysis

BACKGROUND

There is a strong link between sleep and major depression; however, the causal relationship remains unclear. In particular, it is unknown whether changes in depression core symptoms precede or follow changes in sleep, and whether a longer or shorter sleep duration is related to improvements of depression core symptoms.

OBJECTIVE

The aim of this study was to investigate temporal associations between sleep and depression in patients suffering from major depressive disorder using an idiographic research approach.

METHODS

Time-series data of daily sleep assessments (time in bed and total sleep time) and self-rated depression core symptoms for an average of 173 days per patient were analyzed in 22 patients diagnosed with recurrent major depressive disorder using a vector autoregression model. Granger causality tests were conducted to test for possible causality. Impulse response analysis and forecast error variance decomposition were performed to quantify the temporal mutual impact of sleep and depression.

RESULTS

Overall, 11 positive and 5 negative associations were identified between time in bed/total sleep time and depression core symptoms. Granger analysis showed that time in bed/total sleep time caused depression core symptoms in 9 associations, whereas this temporal order was reversed for the other 7 associations. Most of the variance (10%) concerning depression core symptoms could be explained by time in bed. Changes in sleep or depressive symptoms of 1 SD had the greatest impact on the other variable in the following 2 to 4 days.

CONCLUSIONS

Longer rather than shorter bedtimes were associated with more depression core symptoms. However, the temporal orders of the associations were heterogeneous.

The effect of self-help cognitive behavioral therapy for insomnia on depressive symptoms: An updated meta-analysis of randomized controlled trials

BACKGROUND

Sleep disturbances commonly occur in patients with depression. Insomnia is considered not only a symptom of but also a risk factor for depression. Psychological treatments for insomnia have been demonstrated to be efficacious in alleviating depressive symptoms. This meta-analysis examined the effect of self-help cognitive behavioral therapy for insomnia (CBT-I) in treating depressive symptoms.

METHODS

A systematic review was performed up to April 2019 in 6 major electronic databases. The literature search retrieved 4190 potentially relevant citations; 30 randomized controlled trials (total N = 5945) that compared self-help CBT-I vs. waiting-list (WL), routine care, no treatment, individual cognitive behavioral therapy (CBT), group CBT and placebo were included in the current review.

RESULTS

Random effects models showed significant reduction in self-report depressive symptoms (Hedges' g = 0.35; 95% CI: -0.47, -0.23) and insomnia symptoms (Hedges' g = 0.79; 95% CI: -0.56, -1.03) in the self-help CBT-I group when compared to the WL/routine care/no treatment/psychoeducation control group.

LIMITATIONS

The findings should be interpreted with caution due to potential publication bias.

CONCLUSIONS

CBT-I appears to be efficacious in treating depressive symptoms. Given the current results and study limitations, large-scale, high-quality trials that specifically target individuals with a clinical diagnosis of depression are warranted in the future.

Digitale Behandlungsangebote für Insomnie – eine Übersichtsarbeit

Digital angebotene psychologische Interventionen gegen Schlafstörungen sind aktuell ein sehr intensiv bearbeitetes Forschungsthema. In dieser Übersichtsarbeit werden Originalarbeiten und Metaanalysen zu diesem Thema zusammengefasst. Hierbei zeigt sich, dass die internetbasierte kognitive Verhaltenstherapie für Insomnie (KVT-I) bei Erwachsenen durchweg sehr effektiv ist mit allenfalls leicht geringeren Effektstärken als die gleiche Behandlung mit physischer Präsenz von Therapeuten und Patienten. Behandlungseffekte zeigen sich dabei auch für sekundäre Outcome-Parameter wie Depressivität, Angst, Fatigue und Lebensqualität. Hingegen lassen die Forschung zur Wirksamkeit der internetbasierten KVT‑I bei Erwachsenen mit komorbiden psychischen Störungen oder körperlichen Erkrankungen sowie die Forschung zur Frage, wieviel Therapeutenkontakt in die Behandlung integriert werden sollte, anscheinend noch keine abschließenden Antworten zu. In diesen Bereichen scheint weitere Forschung notwendig zu sein scheint.

Changes in dysfunctional beliefs about sleep after cognitive behavioral therapy for insomnia: A systematic literature review and meta-analysis

Cognitive behavioral therapy for insomnia (CBT-I) is the preferred treatment for chronic insomnia and sleep-related cognitions are one target of treatment. There has been little systematic investigation of how sleep-related cognitions are being assessed in CBT-I trials and no meta-analysis of the impact of CBT-I on dysfunctional beliefs about sleep, a core cognitive component of treatment. Academic Search Complete, Medline, CINAHL and PsychInfo from 1990 to 2018 were searched to identify randomized controlled trials of CBT-I in adults (≥18 years) reporting some measure of sleep-related cognitions. Sixteen randomized controlled trials were identified comparing 1134 CBT-I and 830 control subjects. The Dysfunctional Beliefs and Attitudes about Sleep Scale was utilized almost exclusively to assess sleep-related cognitions in these trials. Hedge's g at 95% confidence interval (CI) was calculated to assess CBT-I effect size at post-treatment compared to controls. CBT-I significantly reduced dysfunctional beliefs about sleep (g = -0.90, 95% CI -1.19, -0.62) at post-treatment. Three trials contributed data to estimate effect size for long-term effects (g = -1.04, 95% CI -2.07, -0.02) with follow up time ranging from 3 to 18 mo. We concluded that cognitive behavioral therapy for insomnia has moderate to large effects on dysfunctional beliefs about sleep.

[Internet-based cognitive behavioral therapy of insomnia and nightmare disorder]

Cognitive behavioral therapeutic interventions are considered to be one of the most effective forms of treatment of various mental disorders. Besides being very frequent, sleep disorders, such as insomnia and nightmare disorder are often not treated effectively and guideline-conform, mainly due to the lack of qualified psychotherapists. Implementation of modern technical options, such as web-based psychotherapy can help to overcome this problem. This article presents the current situation in the treatment of insomnia and nightmare disorders as particularly well-suited fields of application. For insomnia there are several English language and also recently German language options, which for example were also evaluated for the application to work-related stress and sleep disorders. In this respect, procedures with and without contact to a therapist or multicomponent procedures and single interventions can be differentiated. For nightmare disorders imagery rehearsal therapy provides a structure, which can also easily be transferred to an internet-based therapy program. The currently beginning use of internet-based treatment of sleep disorders does not yet utilize all theoretically available technical possibilities. The potential of internet-based therapy is extremely versatile and it remains for medical sleep experts to consider which method can be used for which indications.

Digital Delivery of Cognitive Behavioral Therapy for Insomnia

PURPOSE OF REVIEW

Digital cognitive behavioral therapy (dCBT) has been available for over a decade. We reviewed the evidence that accumulated over the past 5 years and discuss the implications for introducing dCBT into standard healthcare.

RECENT FINDINGS

Studies have consistently supported the use of dCBT to treat insomnia. Evidence is now demonstrating large short-term effects and smaller long-term effects up to 1.5 years after treatment across populations with various co-occurring health problems. The effects also extend into a range of psychological well-being factors. Mediators and moderators have been studied to understand mechanisms and create new opportunities to enhance effectiveness and reduce dropout. Incorporating personalized guidance in dCBT may further enhance effectiveness. The evidence for dCBT for insomnia is strong and suggests that dCBT is ready for application in standard healthcare. Further research, digital innovation, and development of effective implementation methods are required to ensure dCBT fulfills its potential.