Major depressive disorder (MDD) is highly prevalent and burdensome for individuals and society. While there are psychological interventions able to prevent and treat MDD, uptake remains low. To overcome structural and attitudinal barriers, an indirect approach of using online insomnia interventions seems promising because insomnia is less stigmatized, predicts MDD onset, is often comorbid and can outlast MDD treatment. This individual-participant-data meta-analysis evaluated the potential of the online insomnia intervention GET.ON Recovery as an indirect treatment to reduce depressive symptom severity (DSS) and potential MDD onset across a range of participant characteristics.

Efficacy on depressive symptom outcomes was evaluated using multilevel regression models controlling for baseline severity. To identify potential effect moderators, clinical, sociodemographic, and work-related variables were investigated using univariable moderation and random-forest methodology before developing a multivariable decision tree.

IPD were obtained from four of seven eligible studies (N = 561); concentrating on workers with high work-stress. DSS was significantly lower in the intervention group both at post-assessment (d = −0.71 [95% CI−0.92 to −0.51]) and at follow-up (d = −0.84 [95% CI −1.11 to −0.57]). In the subsample (n = 121) without potential MDD at baseline, there were no significant group differences in onset of potential MDD. Moderation analyses revealed that effects on DSS differed significantly across baseline severity groups with effect sizes between d = −0.48 and −0.87 (post) and d = − 0.66 to −0.99 (follow-up), while no other sociodemographic, clinical, or work-related characteristics were significant moderators.

An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.

Safety planning-type interventions (SPTIs) for patients at risk of suicide are often used in clinical practice, but it is unclear whether these interventions are effective.

This article reports on a meta-analysis of studies that have evaluated the effectiveness of SPTIs in reducing suicidal behaviour and ideation.

We searched Medline, EMBASE, PsycINFO, Web of Science and Scopus from their inception to 9 December 2019, for studies that compared an SPTI with a control condition and had suicidal behaviour or ideation as outcomes. Two researchers independently extracted the data. To assess suicidal behaviour, we used a random-effects model of relative risk based on a pooled measure of suicidal behaviour. For suicidal ideation, we calculated effect sizes with Hedges’ g. The study was registered at PROSPERO (registration number CRD42020129185).

Of 1816 unique abstracts screened, 6 studies with 3536 participants were eligible for analysis. The relative risk of suicidal behaviour among patients who received an SPTI compared with control was 0.570 (95% CI 0.408–0.795, P = 0.001; number needed to treat, 16). No significant effect was found for suicidal ideation.

To our knowledge, this is the first study to report a meta-analysis on SPTIs for suicide prevention. Results support the use of SPTIs to help preventing suicidal behaviour and the inclusion of SPTIs in clinical guidelines for suicide prevention. We found no evidence for an effect of SPTIs on suicidal ideation, and other interventions may be needed for this purpose.

Traditionally, health technology assessment (HTA) focuses on assessing the impact of pharmaceutical technologies on health and care. Resources are scarce and policy makers aim to achieve effective, accessible health care. eHealth innovations are increasingly more integrated in all healthcare domains. However, how eHealth is assessed prior to its implementation in care practices is unclear. To support evidence-informed policy making, this study aimed to identify frameworks and methods for assessing eHealth's impact on health care.

The scientific literature in five bibliographical databases was systematically reviewed. Articles were included if the study was conducted in a clinical setting, used an HTA framework and assessed an eHealth service. A systematic qualitative narrative approach was applied for analysis and reporting.

Twenty-one HTA frameworks were identified in twenty-three articles. All frameworks addressed outcomes related to the technical performance and functionalities of eHealth service under assessment. The majority also addressed costs (n = 19), clinical outcomes (n = 14), organizational (n = 15) and system level aspects (n = 13). Most frameworks can be classified as dimensional (n = 13), followed by staged (n = 3), hybrid (n = 3), and business modeling frameworks (n = 2). Six frameworks specified assessment outcomes and methods.

HTA frameworks are available for a-priori impact assessment of eHealth services. The frameworks vary in assessment outcomes, methods, and specificity. Demonstrated applicability in practice is limited. Recommendations include standardization of: (i) reporting characteristics of eHealth services, and (ii) specifying assessment outcomes and methods following a stepped-approach tailored to the functional characteristics of eHealth services. Standardization might improve the quality and comparability of eHTA assessments.

Little is known about potential harmful effects as a consequence of self-guided internet-based cognitive behaviour therapy (iCBT), such as symptom deterioration rates. Thus, safety concerns remain and hamper the implementation of self-guided iCBT into clinical practice. We aimed to conduct an individual participant data (IPD) meta-analysis to determine the prevalence of clinically significant deterioration (symptom worsening) in adults with depressive symptoms who received self-guided iCBT compared with control conditions. Several socio-demographic, clinical and study-level variables were tested as potential moderators of deterioration.

Randomised controlled trials that reported results of self-guided iCBT compared with control conditions in adults with symptoms of depression were selected. Mixed effects models with participants nested within studies were used to examine possible clinically significant deterioration rates.

Thirteen out of 16 eligible trials were included in the present IPD meta-analysis. Of the 3805 participants analysed, 7.2% showed clinically significant deterioration (5.8% and 9.1% of participants in the intervention and control groups, respectively). Participants in self-guided iCBT were less likely to deteriorate (OR 0.62, p < 0.001) compared with control conditions. None of the examined participant- and study-level moderators were significantly associated with deterioration rates.

Self-guided iCBT has a lower rate of negative outcomes on symptoms than control conditions and could be a first step treatment approach for adult depression as well as an alternative to watchful waiting in general practice.

Web-based interventions are effective in reducing depression. However, the evidence for the cost-effectiveness of these interventions is scarce.

The aim is to assess the cost-effectiveness of a web-based intervention (GET.ON M.E.D.) for individuals with diabetes and comorbid depression compared with an active control group receiving web-based psychoeducation.

We conducted a cost-effectiveness analysis with treatment response as the outcome and a cost-utility analysis with quality-adjusted life-years (QALYs) alongside a randomised controlled trial with 260 participants.

At a willingness-to-pay ceiling of €5000 for a treatment response, the intervention has a 97% probability of being regarded as cost-effective compared with the active control group. If society is willing to pay €14 000 for an additional QALY, the intervention has a 51% probability of being cost-effective.

This web-based intervention for individuals with diabetes and comorbid depression demonstrated a high probability of being cost-effective compared with an active control group.

S.N., D.D.E., D.L., M.B. and B.F. are stakeholders of the Institute for Online Health Trainings, which aims to transfer scientific knowledge related to this research into routine healthcare.

Subthreshold depression is a highly prevalent condition and a risk factor for developing a major depressive episode. Internet-based cognitive behaviour therapy may be a promising approach for the treatment of subthreshold depression. The current study had two aims: (1) to determine whether an internet-based cognitive behaviour therapy intervention and a group cognitive behaviour therapy intervention are more effective than a waiting-list control group; and (2) to determine whether the effect of the internet-based cognitive behaviour therapy differs from the group cognitive behaviour therapy intervention.

A total of 191 women and 110 men with subthreshold depression were randomized into internet-based treatment, group cognitive behaviour therapy (Lewinsohn's Coping With Depression course), or a waiting-list control condition. The main outcome measure was treatment response after 10 weeks, defined as the difference in pre- and post-treatment scores on the Beck Depression Inventory (BDI). Missing data, a major limitation of this study, were imputed using the Multiple Imputation (MI) procedure Data Augmentation.

In the waiting-list control group, we found a pre- to post-improvement effect size of 0·45, which was 0·65 in the group cognitive behaviour therapy condition and 1·00 within the internet-based treatment condition. Helmert contrasts showed a significant difference between the waiting-list condition and the two treatment conditions (p=0·04) and no significant difference between both treatment conditions (p=0·62).

An internet-based intervention may be at least as effective as a commonly used group cognitive behaviour therapy intervention for subthreshold depression in people over 50 years of age.