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Background: Sleep disturbance symptoms are common in major depressive disorder (MDD) and have been found to hamper the treatment effect of conventional face-to-face psychological treatments such as cognitive behavioral therapy. To increase the dissemination of evidence-based treatment, blended cognitive behavioral therapy (bCBT) consisting of web-based and face-to-face treatment is on the rise for patients with MDD. To date, no study has examined whether sleep disturbance symptoms have an impact on bCBT treatment outcomes and whether it affects bCBT and treatment-as-usual (TAU) equally. Objective: The objectives of this study are to investigate whether baseline sleep disturbance symptoms have an impact on treatment outcomes independent of treatment modality and whether sleep disturbance symptoms impact bCBT and TAU in routine care equally. Methods: The study was based on data from the E-COMPARED (European Comparative Effectiveness Research on Blended Depression Treatment Versus Treatment-as-Usual) study, a 2-arm, multisite, parallel randomized controlled, noninferiority trial. A total of 943 outpatients with MDD were randomized to either bCBT (476/943, 50.5%) or TAU consisting of routine clinical MDD treatment (467/943, 49.5%). The primary outcome of this study was the change in depression symptom severity at the 12-month follow-up. The secondary outcomes were the change in depression symptom severity at the 3- and 6-month follow-up and MDD diagnoses at the 12-month follow-up, assessed using the Patient Health Questionnaire-9 and Mini-International Neuropsychiatric Interview, respectively. Mixed effects models were used to examine the association of sleep disturbance symptoms with treatment outcome and treatment modality over time. Results: Of the 943 patients recruited for the study, 558 (59.2%) completed the 12-month follow-up assessment. In the total sample, baseline sleep disturbance symptoms did not significantly affect change in depressive symptom severity at the 12-month follow-up (β=.16, 95% CI –0.04 to 0.36). However, baseline sleep disturbance symptoms were negatively associated with treatment outcome for bCBT (β=.49, 95% CI 0.22-0.76) but not for TAU (β=–.23, 95% CI −0.50 to 0.05) at the 12-month follow-up, even when adjusting for baseline depression symptom severity. The same result was seen for the effect of sleep disturbance symptoms on the presence of depression measured with Mini-International Neuropsychiatric Interview at the 12-month follow-up. However, for both treatment formats, baseline sleep disturbance symptoms were not associated with depression symptom severity at either the 3- (β=.06, 95% CI −0.11 to 0.23) or 6-month (β=.09, 95% CI −0.10 to 0.28) follow-up. Conclusions: Baseline sleep disturbance symptoms may have a negative impact on long-term treatment outcomes in bCBT for MDD. This effect was not observed for TAU. These findings suggest that special attention to sleep disturbance symptoms might be warranted when MDD is treated with bCBT. Future studies should investigate the effect of implementing modules specifically targeting sleep disturbance symptoms in bCBT for MDD to improve long-term prognosis.

Background: Sleep disturbance symptoms are common in major depressive disorder (MDD) and have been found to hamper the treatment effect of conventional face-to-face psychological treatments such as cognitive behavioral therapy. To increase the dissemination of evidence-based treatment, blended cognitive behavioral therapy (bCBT) consisting of web-based and face-to-face treatment is on the rise for patients with MDD. To date, no study has examined whether sleep disturbance symptoms have an impact on bCBT treatment outcomes and whether it affects bCBT and treatment-as-usual (TAU) equally. Objective: The objectives of this study are to investigate whether baseline sleep disturbance symptoms have an impact on treatment outcomes independent of treatment modality and whether sleep disturbance symptoms impact bCBT and TAU in routine care equally. Methods: The study was based on data from the E-COMPARED (European Comparative Effectiveness Research on Blended Depression Treatment Versus Treatment-as-Usual) study, a 2-arm, multisite, parallel randomized controlled, noninferiority trial. A total of 943 outpatients with MDD were randomized to either bCBT (476/943, 50.5%) or TAU consisting of routine clinical MDD treatment (467/943, 49.5%). The primary outcome of this study was the change in depression symptom severity at the 12-month follow-up. The secondary outcomes were the change in depression symptom severity at the 3- and 6-month follow-up and MDD diagnoses at the 12-month follow-up, assessed using the Patient Health Questionnaire-9 and Mini-International Neuropsychiatric Interview, respectively. Mixed effects models were used to examine the association of sleep disturbance symptoms with treatment outcome and treatment modality over time. Results: Of the 943 patients recruited for the study, 558 (59.2%) completed the 12-month follow-up assessment. In the total sample, baseline sleep disturbance symptoms did not significantly affect change in depressive symptom severity at the 12-month follow-up (β=.16, 95% CI –0.04 to 0.36). However, baseline sleep disturbance symptoms were negatively associated with treatment outcome for bCBT (β=.49, 95% CI 0.22-0.76) but not for TAU (β=–.23, 95% CI −0.50 to 0.05) at the 12-month follow-up, even when adjusting for baseline depression symptom severity. The same result was seen for the effect of sleep disturbance symptoms on the presence of depression measured with Mini-International Neuropsychiatric Interview at the 12-month follow-up. However, for both treatment formats, baseline sleep disturbance symptoms were not associated with depression symptom severity at either the 3- (β=.06, 95% CI −0.11 to 0.23) or 6-month (β=.09, 95% CI −0.10 to 0.28) follow-up. Conclusions: Baseline sleep disturbance symptoms may have a negative impact on long-term treatment outcomes in bCBT for MDD. This effect was not observed for TAU. These findings suggest that special attention to sleep disturbance symptoms might be warranted when MDD is treated with bCBT. Future studies should investigate the effect of implementing modules specifically targeting sleep disturbance symptoms in bCBT for MDD to improve long-term prognosis.

Additional file 1. The four different expressions of the virtual coach: friendly, smiling, compassionate, questioning (left to right).

Additional file 2. Additional information about the variables used in the conversation tree excerpt depicted in Fig. 3.

Additional file 3. Screenshot of the Moodbuster smartphone application.

Background Depression and anxiety are highly prevalent and often co-occur. Several studies indicate the potential of disorder-specific psychological interventions for the prevention of each of these disorders. To treat comorbidity, transdiagnostic treatment concepts seem to be a promising approach, however, evidence for transdiagnostic concepts of prevention remains inconclusive. Internet- and mobile-based interventions (IMIs) may be an effective means to deliver psychological interventions on a large scale for the prevention of common mental disorders (CMDs) such as depression and anxiety. IMIs have been shown to be effective in treating CMDs, e.g. in reducing symptoms of depression and anxiety. However, there is a lack of studies examining the efficacy of interventions reducing the incidence of CMDs. Moreover, the comparative cost-effectiveness of guided versus unguided IMIs for the prevention of depression and anxiety has not been studied yet. Hence, this study aims at investigating the (cost-) effectiveness of guided and unguided internet- and mobile-based transdiagnostic individually tailored indicated prevention of depression and anxiety. Methods A multi-country three-armed randomized controlled trial will be conducted to compare a guided and unguided intervention to treatment as usual (TAU). Both active conditions are based on the same intervention, ICare Prevent, and differ only with regard to guidance format. Altogether, 954 individuals with subclinical symptoms of depression (CES-D ≥ 16) and anxiety (GAD-7 ≥ 5) who do not have a full-blown disorder will be recruited in Germany, Switzerland, Spain and the Netherlands, and randomized to one of three conditions (guided intervention, unguided intervention, or TAU). The TAU arm will receive access to the training after a 12-month waiting period. The primary outcome will be time to CMD onset (any depression/anxiety disorder) within a follow-up period of 12 months after baseline. Secondary outcomes will include disorder-specific symptom severity (depression/anxiety) assessed by diagnostic raters blinded to intervention condition at post-intervention, self-reports, acceptability, health related quality of life, and psychosocial variables associated with developing a CMD. Assessments will take place at baseline, mid-intervention (5 weeks into the intervention), post-intervention (8 weeks after randomization) and follow-up (6 and 12 months after randomization). Data will be analyzed on an intention-to-treat basis and per protocol. Cost-effectiveness will be evaluated from a public health and a societal perspective, including both direct and indirect costs. Discussion The present study will further enhance the evidence-base for transdiagnostic preventive interventions and provide valuable information about optimal trade-off between treatment outcome and costs. Trial registration German Clinical Trial Registration (DRKS - http://www.drks.de/drks_web/): DRKS00011099., Highlights • Depression and anxiety are highly comorbid, but often not treated together. • Transdiagnostic treatment provides potential to reduce comorbidity. • Individual tailoring can help adapt treatment to individual profiles. • Large multi-country transdiagnostic prevention trial in a subclinical population. • Cost-effectiveness for a guided and unguided internet- and mobile-based intervention will be investigated.

BACKGROUND: Successfully implementing eMental health (eMH) interventions in routine mental health care constitutes a major challenge. Reliable instruments to assess implementation progress are essential. The Normalization MeAsure Development (NoMAD) study developed a brief self-report questionnaire that could be helpful in measuring implementation progress. Based on the Normalization Process Theory, this instrument focuses on 4 generative mechanisms involved in implementation processes: coherence, cognitive participation, collective action, and reflexive monitoring. OBJECTIVE: The aim of this study was to translate the NoMAD questionnaire to Dutch and to confirm the factor structure in Dutch mental health care settings. METHODS: Dutch mental health care professionals involved in eMH implementation were invited to complete the translated NoMAD questionnaire. Confirmatory factor analysis (CFA) was conducted to verify interpretability of scale scores for 3 models: (1) the theoretical 4-factor structure, (2) a unidimensional model, and (3) a hierarchical model. Potential improvements were explored, and correlated scale scores with 3 control questions were used to assess convergent validity. RESULTS: A total of 262 professionals from mental health care settings in the Netherlands completed the questionnaire (female: 81.7%; mean age: 45 [SD=11]). The internal consistency of the 20-item questionnaire was acceptable (.62≤alpha≤.85). The theorized 4-factor model fitted the data slightly better in the CFA than the hierarchical model (Comparative Fit Index=0.90, Tucker Lewis Index=0.88, Root Mean Square Error of Approximation=0.10, Standardized Root Mean Square Residual=0.12, χ22=22.5, P≤.05). However, the difference is small and possibly not outweighing the practical relevance of a total score and subscale scores combined in one hierarchical model. One item was identified as weak (λCA.2=0.10). A moderate-to-strong convergent validity with 3 control questions was found for the Collective Participation scale (.47≤r≤.54, P≤.05). CONCLUSIONS: NoMAD's theoretical factor structure was confirmed in Dutch mental health settings to acceptable standards but with room for improvement. The hierarchical model might prove useful in increasing the practical utility of the NoMAD questionnaire by combining a total score with information on the 4 generative mechanisms. Future research should assess the predictive value and responsiveness over time and elucidate the conceptual interpretability of NoMAD in eMH implementation practices.

Doel Zorggebruik onderzoeken bij patiënten met een depressie, en nagaan welke demografische kenmerken en ernstkenmerkenpatiënten die vroegtijdig gebruikmaken van zorg, patiënten die afwachten met zorggebruik en patiënten die geen gebruikmakenvan zorg van elkaar onderscheiden. Opzet Longitudinaal, observationeel en prospectief onderzoek.MethodeWe gebruikten gegevens van de ‘Netherlands mental health survey and incidence study-2’ (NEMESIS-2). Patiënten die eendepressie rapporteerden in de 12 maanden voorafgaand aan de ‘baseline’-meting, werden geïncludeerd. Hun zorggebruik indiezelfde periode werd gerapporteerd. Na 3 jaar keken we opnieuw naar hun zorggebruik. Om verschillen te onderzoeken tussenvroege zorggebruikers (in het jaar dat ze een depressie hadden gebruikten ze ook zorg), afwachtende en niet-zorggebruikersgebruikten we een multinomiale logistische regressieanalyse. Resultaten Meer dan de helft van de respondenten was een vroege zorggebruiker (62%). Vroege zorggebruikers hadden ernstigere enpersisterende depressieve symptomen en vaker geen partner dan niet-zorggebruikers (dat wil zeggen: noch zorg in jaar waarindepressie begon, noch in 3 jaar daarna). De meerderheid van de niet-zorggebruikers (89%) was hersteld na 3 jaar. Afwachtendezorggebruikers (geen zorg in jaar waarin depressie begon, wel in 3 jaar daarna) hadden relatief geringe klachten en rapporteerdenvaker een nieuwe of aanhoudende depressieve episode na 3 jaar dan vroege zorggebruikers. Conclusie Zorggebruik door patiënten met een depressie lijkt vooral samen te hangen met ernstkenmerken en niet zozeer met demografischekenmerken zoals leeftijd, opleidingsniveau of geslacht.

DoelZorggebruik onderzoeken bij patiënten met een depressie, en nagaan welke demografische kenmerken en ernstkenmerkenpatiënten die vroegtijdig gebruikmaken van zorg, patiënten die afwachten met zorggebruik en patiënten die geen gebruikmakenvan zorg van elkaar onderscheiden.OpzetLongitudinaal, observationeel en prospectief onderzoek.MethodeWe gebruikten gegevens van de ‘Netherlands mental health survey and incidence study-2’ (NEMESIS-2). Patiënten die eendepressie rapporteerden in de 12 maanden voorafgaand aan de ‘baseline’-meting, werden geïncludeerd. Hun zorggebruik indiezelfde periode werd gerapporteerd. Na 3 jaar keken we opnieuw naar hun zorggebruik. Om verschillen te onderzoeken tussenvroege zorggebruikers (in het jaar dat ze een depressie hadden gebruikten ze ook zorg), afwachtende en niet-zorggebruikersgebruikten we een multinomiale logistische regressieanalyse.ResultatenMeer dan de helft van de respondenten was een vroege zorggebruiker (62%). Vroege zorggebruikers hadden ernstigere enpersisterende depressieve symptomen en vaker geen partner dan niet-zorggebruikers (dat wil zeggen: noch zorg in jaar waarindepressie begon, noch in 3 jaar daarna). De meerderheid van de niet-zorggebruikers (89%) was hersteld na 3 jaar. Afwachtendezorggebruikers (geen zorg in jaar waarin depressie begon, wel in 3 jaar daarna) hadden relatief geringe klachten en rapporteerdenvaker een nieuwe of aanhoudende depressieve episode na 3 jaar dan vroege zorggebruikers.ConclusieZorggebruik door patiënten met een depressie lijkt vooral samen te hangen met ernstkenmerken en niet zozeer met demografischekenmerken zoals leeftijd, opleidingsniveau of geslacht.

Background The integration of digital treatments into national mental health services is on the agenda in the European Union. The E-COMPARED consortium conducted a survey aimed at exploring stakeholders' knowledge, acceptance and expectations of digital treatments for depression, and at identifying factors that might influence their opinions when considering the implementation of these approaches. Method An online survey was conducted in eight European countries: France, Germany, Netherlands, Poland, Spain, Sweden, Switzerland and The United Kingdom. Organisations representing government bodies, care providers, service-users, funding/insurance bodies, technical developers and researchers were invited to participate in the survey. The participating countries and organisations reflect the diversity in health care infrastructures and e-health implementation across Europe. Results A total of 764 organisations were invited to the survey during the period March–June 2014, with 175 of these organisations participating in our survey. The participating stakeholders reported moderate knowledge of digital treatments and considered cost-effectiveness to be the primary incentive for integration into care services. Low feasibility of delivery within existing care services was considered to be a primary barrier. Digital treatments were regarded more suitable for milder forms of depression. Stakeholders showed greater acceptability towards blended treatment (the integration of face-to-face and internet sessions within the same treatment protocol) compared to standalone internet treatments. Organisations in countries with developed e-health solutions reported greater knowledge and acceptability of digital treatments. Conclusion Mental health stakeholders in Europe are aware of the potential benefits of digital interventions. However, there are variations between countries and stakeholders in terms of level of knowledge about such interventions and their feasibility within routine care services. The high acceptance of blended treatments is an interesting finding that indicates a gradual integration of technology into clinical practice may fit the attitudes and needs of stakeholders. The potential of the blended treatment approach, in terms of enhancing acceptance of digital treatment while retaining the benefit of cost-effectiveness in delivery, should be further explored. Funding The E-COMPARED project has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement no. 603098., Highlights • Digital treatments were rated as more acceptable for milder forms of depression. • Stakeholders demonstrated greater acceptability towards blended treatment compared to standalone digital treatment. • Cost-effectiveness was identified as the primary incentive for integrating of treatments into routine care. • Care systems being viewed as unprepared for internet-based treatments was identified as the primary barrier. • Stakeholders in countries with developed e-health solutions demonstrated higher knowledge towards digital treatments.

The authors regret the fact that a typographical error affected a p-value, which was mentioned in the manuscript. Specifically, in Section “3.7. Subgroup and sensitivity analyses” The original manuscript states: “The effect size decreased to a marginal extent for PA (g=0.37), but bordered now on significance, (p=0.007)”. However, the p-value of PA was actually 0.07 instead of 0.007. The authors would like to apologise for any inconvenience caused. DOI of original article: http://dx.doi.org/10.1016/j.jad.2016.05.019.

Objective: Problematic video-gaming or social media use may seriously affect adolescents' health status. However, it is not very well known which health-related problems are most strongly related to these issues. To inform the development of prevention and intervention strategies, this study aims to gain a better understanding of the healthrelated problems and demographical factors associated with problematic video-gaming or social media use in early adolescence. Method: A cross-sectional analysis was performed on data collected by two Municipal Health Services in the Netherlands in 2013-2014. In this survey among youth, 21,053 students from secondary schools (mean age 14.4 years) completed a web-based questionnaire. Multivariate analyses were carried out to assess the strength of the associations between mental health problems, life-events, lifestyle and substance use as independent variables, and problematic video-gaming and problematic social media use as dependent variables. Results: Of the participating students, 5.7% reported problematic video-gaming and 9.1% problematic social media use. Problematic video-gaming was most strongly associated with conduct problems, suicidal thoughts (all medium effect sizes, OR = 2, p

Importance: Self-guided internet-based cognitive behavioral therapy (iCBT) has the potential to increase access and availability of evidence-based therapy and reduce the cost of depression treatment. Objectives: To estimate the effect of self-guided iCBT in treating adults with depressive symptoms compared with controls and evaluate the moderating effects of treatment outcome and response. Data Sources: A total of 13 384 abstracts were retrieved through a systematic literature search in PubMed, Embase, PsycINFO, and Cochrane Library from database inception to January 1, 2016. Study Selection: Randomized clinical trials in which self-guided iCBT was compared with a control (usual care, waiting list, or attention control) in individuals with symptoms of depression. Data Extraction and Synthesis: Primary authors provided individual participant data from 3876 participants from 13 of 16 eligible studies. Missing data were handled using multiple imputations. Mixed-effects models with participants nested within studies were used to examine treatment outcomes and moderators. Main Outcomes and Measures: Outcomes included the Beck Depression Inventory, Center for Epidemiological Studies–Depression Scale, and 9-item Patient Health Questionnaire scores. Scales were standardized across the pool of the included studies. Results: Of the 3876 study participants, the mean (SD) age was 42.0 (11.7) years, 2531 (66.0%) of 3832 were female, 1368 (53.1%) of 2574 completed secondary education, and 2262 (71.9%) of 3146 were employed. Self-guided iCBT was significantly more effective than controls on depressive symptoms severity (β = −0.21; Hedges g = 0.27) and treatment response (β = 0.53; odds ratio, 1.95; 95% CI, 1.52-2.50; number needed to treat, 8). Adherence to treatment was associated with lower depressive symptoms (β = −0.19; P = .001) and greater response to treatment (β = 0.90; P