Background
Depressive disorders are among the leading causes of worldwide disability [
1]. Mild to moderate forms of depression are even more common than severe depression. While 29% of primary care patients reported mild to moderate depressive symptoms in one study only 9.5% reported moderate to severe symptoms [
2]. However, subclinical forms of depression are associated with considerable impairment, economic costs, and increased risk for developing major depression [
3‐
5].
Consequently, preventing depression and increasing access to treatment are among the most urgent global health care priorities [
6,
7]. Unfortunately, many individuals with depression remain untreated, even in countries with well-developed health care systems. The global mental health treatment gap has been estimated at 50% for all mental disorders [
7,
8]. To bridge this treatment gap and improve depression prevention and treatment, a wide array of innovative methods are needed [
9]. These can be employed in a stepped-care model where the intensity of the intervention is tailored to patients’ current symptom severity [
10].
Stepped-care models have been adopted in some national treatment guidelines, such as those by the National Institute of Clinical Excellence in the United Kingdom [
10,
11]. In such guidelines, low-intensity interventions are regarded as an appropriate first option for patients with mild to moderate depressive symptoms [
10] p. 16. The spectrum of low-intensity treatments spans from self-help books to brief counseling. It includes interventions delivered by phone, mail, or SMS; or guided and unguided online psychological treatments [
12]. Research on online depression treatments has garnered particular momentum in recent years, and a number of meta- analyses and systematic reviews attest to their efficacy [
13‐
19].
Online psychological treatments have been noted to have several advantages, including easy accessibility and scalability, such that vast segments of the population can potentially be reached at low cost [
20]. Not all internet interventions are easily scalable, though. Broadly speaking, the internet can be used as a communication channel as well as an information medium [
20,
21]. Used as a communication medium (in chat-therapy, for instance), it makes treatment more accessible for patients. However, in this form of internet-mediated intervention, therapists are still required to devote considerable time to each patient. When used as a pure information medium (i.e. unguided online self-help), treatment is both easily accessible and can be scaled up because demands on therapist time are minimized.
Meta-analyses have shown that self-guided programs, which do not require therapist support, are effective in the treatment of depressive symptoms, albeit with small effect sizes [
22]. The effectiveness of unguided self-help programs can also be compromised by a high drop-out rate. In guided forms of online self-help, therapists motivate and support patients regularly, for example via brief weekly e-mail contacts. Guided online depression interventions have been shown to achieve medium to large effect sizes [
13,
16]. One meta-analysis even demonstrated that guided self-help can be as effective as face-to-face treatment [
15]. Contacting patients prior to the onset of treatment for diagnostic purposes may increase the effect of unguided self-help programs to a medium effect size [
16]. Online psychological treatments have also successfully been studied in the prevention of depressive disorders [
23] and the prevention of relapse [
24,
25].
Even though the evidence base supporting the efficacy of online depression treatments has grown in recent years, previous studies are limited by various methodological factors. Firstly, many studies relied solely on self-reports and lacked interview-based instruments to establish diagnoses and measure symptom severity [
22]. Secondly, recruitment was often carried out via advertisements or the internet rather than through clinical settings, which may introduce a bias towards more internet-savvy or motivated participants. Thirdly, most previous studies were carried out by single study sites, and the researchers were also frequently the developers of the online intervention, which may limit generalizability and foster allegiance effects. Fourthly, sample sizes in many previous studies were too small to examine moderator effects. Finally, no study to date has investigated the effect of internet-based depression treatment on subsequent help-seeking behavior. Furthermore, there is no published study known to the authors which examines the health economic consequences of internet-based treatment of depression in the German context.
We will therefore conduct a large multicenter trial to test the effectiveness of an online-based psychological treatment, compared to a care as usual control condition, among adults suffering from mild to moderate depressive symptoms, the EVIDENT trial (EffectiVeness of Internet-based DEpressioN Treatment). In this trial, mild to moderate depressive symptoms are operationalized as a score between 5 and 14 on the Patient Health Questionnaire (PHQ-9) [
26]. Whereas participants with mild depressive symptoms (PHQ-9 score 5–9) will receive an unguided version of an online treatment, those with moderate symptoms (PHQ-9 score 10–14) will receive additional e-mail-support. Subjects will be recruited from a broad array of settings, including in- and outpatient medical and psychological services but also online-forums for depression, health-insurance companies and the general media (e.g., coverage in newspaper and radio reports). We will thus also be able to examine if and how online psychological treatments can be integrated into regular in- and outpatient settings.
We hypothesize that online psychological treatment will be superior to a care as usual control condition in reducing mild-to-moderate depressive symptoms. We will also analyze the effect of the intervention on the risk of developing a depressive episode in the treatment phase and in the follow-up period, which will extend to one year. We will thus be able to ascertain the effect of the intervention on the prevention of a depressive episode. Further outcome parameters include quality of life and attitude towards online psychological treatments. Moreover a cost-of-illness analysis will be conducted to determine the consumption of resources of patients with depression symptoms – separately analysed by different health care sectors.
Discussion
This randomized-controlled multicenter study examines the effectiveness of an online psychological intervention in controlling mild to moderate depressive symptoms and preventing emergence and relapse of depression. It is one of the first large trials examining the impact of online self-help interventions on health economic measures [
58]. We will also gain valuable experiences in implementing an online psychological intervention into routine clinical care.
As a major strength of this study, it has a low-threshold of entry as anyone suffering from depressive symptoms can sign up through the study website without further requirements. We will therefore be able to draw inferences with regard to the effectiveness of online-psychological treatments, i.e. the extent to which the treatment achieves its intended effect in the usual clinical setting [
59]. To this end, we will include patients with other comorbid disorders including substance abuse and dependence, anxiety disorders and personality disorders. Also, acute suicidality will be assessed clinically by trained interviewers rather than based on a more rigid exclusion of all patients who cross a certain threshold on a self-rating. These measures will improve the external validity of our study results as the great majority of patients with depression suffer from at least one comorbid mental disorder (41). This strength of the study may also be regarded as a limitation, as it may result in a relatively heterogeneous group of patients. Another weakness of our design is the liberal acceptance of concomitant treatments in our study, which again will increase the external validity of our findings while possibly reducing internal validity.
In addition to the main analysis described in the methods section, our study will be able to address a number of other important research questions, some of which have not been addressed before. To this end, we will conduct subgroup analyses of the influence of pre-specified baseline characteristics on the main outcome measure [
60] and analyses of secondary outcomes. One subgroup analysis will concern the influence of referral source (medical and psychological services versus other) and primary motivation for study participation (self versus other) on the main outcome as many trials of online-based psychological interventions have been conducted outside routine clinical practice [
22] and the applicability of the results to routine clinical practice has therefore been debated [
61]. Other subgroup analysis will concern the influence of baseline severity [
14], presence of depressive episode at baseline, chronicity [
62], parallel treatment [
24] and attitude to online psychological intervention [
63] on the main outcome.
We also plan to undertake a wide range of additional analyses. Weekly PHQ assessments in the intervention group will allow us to identify meaningful patterns of early change in depression during online treatment that are shared by many individual patients and examine whether these patterns predict outcomes at treatment termination and over the follow-up period as well as drop-out or time patients participate in online treatment [
64,
65]. Also we may be able to assess whether e-mail support affects working alliance scores and attitudes towards online psychological interventions. The results of this analysis will be biased by depression severity however as only more severely depressed participants receive e-mail support. Finally, this study will be the first to use the Computer-adaptive test for depression (D-CAT) [
45,
46] in a prospective randomized controlled trial and will allow the comparison with more established outcome measures.
The present trial will probably be the largest multicentric study conducted thus far of an online depression treatment in which validated diagnostic interviews and symptom severity measures are used and participants are followed for a full year (without those in the control group receiving the intervention). It is hoped that the study will yield meaningful answers to the question of whether the internet-based intervention studied here can contribute to the effective and efficient prevention and treatment of mild to moderate depression on a population level. The results of this trial are expected to influence policy decisions with regard to whether such interventions ought to be implemented more widely in order to meet the challenge posed by the global depression treatment gap.
Acknowledgements
Funding body for the study: German Federal Ministry of Health, II A 5–2512 FSB 052. The funding body had no role in the design of the study or the writing of the manuscript. It will not have a role in the collection, analysis or interpretation of the data. Additional funding is given by the GAIA AG which provided the licenses for the internet based psychological intervention for all participants in the trial. The investigators are independent of the GAIA AG with regards to analysis of the data and publication of the results. We acknowledge support of the publication fee by Deutsche Forschungsgemeinschaft and the Open Access Publication Funds of Bielefeld University.
Complete list of collaborators
Principal Investigator: Fritz Hohagen, Lübeck. External Advisors: Gerhard Andersson, Linköping; Franz Caspar, Bern; Bernd Löwe; Hamburg. Coordinating Investigators: Philipp Klein, Lübeck; Steffen Moritz, Hamburg. Steering Comittee: Thomas Berger, Bern; Philipp Klein, Lübeck; Björn Meyer, Hamburg; Steffen Moritz, Hamburg. Coordinator Recruitment: Christina Späth, Lübeck. Recruitment Team: Bielefeld University (Wolfgang Greiner, Viola Gräfe), Charité Berlin (Matthias Rose, Sandra Nolte and coworkers), Hamburg University (Steffen Moritz, Johanna Schröder), Lübeck University (Philipp Klein, Christina Späth). Coordinator Diagnostic: Johanna Schröder, Hamburg Christina Späth, Lübeck. Diagnostic Team: Charité Berlin (Matthias Rose, Sandra Nolte and coworkers), Hamburg University (Steffen Moritz, Johanna Schröder and coworkers), Lübeck University (Philipp Klein, Christina Späth and coworkers), Trier University (Wolfgang Lutz, David Rosenbaum and coworkers), Tübingen University (Martin Hautzinger, Kristina Fuhr and coworkers). Coordinator E-Mail-Support: Thomas Berger, Bern. E-Mail-Support Team: Bern University (Thomas Berger), Trier University (Winfried Lutz, David Rosenbaum), Tübingen University (Martin Hautzinger, Kristina Fuhr). E-Mail-Hotline: Bielefeld University (Wolfgang Greiner, Viola Gräfe).
Competing interests
BM is employed as research director at GAIA AG, the company that developed and owns the internet-based psychological intervention investigated in this trial.
Authors’ contributions
JPK participated in the conception and design of the study, the acquisition of data and drafted the first manuscript. TB participated in the conception and design of the study and in drafting the manuscript and data acquisition. JS participated in the design of the study and in drafting the manuscript and data acquisition. CS participated in drafting the manuscript and data acquisition. BM participated in the conception and design of the study and in drafting the manuscript. FC participated in the design of the study. WL participated in the design of the study and in drafting the manuscript and data acquisition. WG participated in the design of the study and in drafting the manuscript and data acquisition. MH participated in the design of the study and in drafting the manuscript and data acquisition. MR participated in the design of the study and in data acquisition. VG participated in drafting the manuscript and data acquisition. FH participated in the conception and design of the study and in data acquisition. GA participated in design of the study and in drafting of the manuscript. EV participated in design of the study and in drafting of the manuscript. SM participated in the conception and design of the study, the acquisition of data and in drafting the manuscript. All authors read and approved the final manuscript.