Science

Our vision: To challenge paradigms by developing effective innovations that treat disease and optimize health, and that prove their value in methodologically sound scientific research.

Research & Development projects

Selected publications on GAIA R&D

Research & Development Projects

Our R&D projects cover a range of medical, psychological and technological topics. What they have in common is close collaboration between world-leading scientists and GAIA in-house experts.

Nevermind

Topic/Focus

Sensor technology

Selected collaborating parties

Universities and research centres in Pisa, Turin (Italy), Madrid (Spain), Lisbon (Portugal), Stockholm (Karolinska Institute, Sweden), and Essex (United Kingdom)

This project is supported by the European Commission under the Horizon2020 scheme and aims to utilize sensor-technology in order to improve the detection and treatment of depression among patients with certain medical conditions (e.g., cardiovascular disease, kidney failure). Using artificial intelligence algorithms, sensor technology is used to estimate patients’ depression risk, based on routinely collected physiological data, and to initiate appropriate interventions accordingly. This project is consistent with GAIA’s vision to harness sophisticated software and technology in order to transform diagnostic and treatment procedures and thereby improve patient outcomes as well as quality of life.

Evident

Topic/Focus

Depression treatment

Selected collaborating parties

Universities and medical centres in Hamburg, Lübeck, Berlin (Charité), Trier, Bielefeld, Tübingen, Bern (Switzerland), and Linköping (Sweden)

This multicenter randomized controlled trial was sponsored by the German Ministry of Health and investigated how deprexis, our evidence-based depression intervention, can help improve the standard of treatment for people with mild to moderate depressive symptoms. More than 1,000 adults with depressive symptoms were randomized to either deprexis or a control group, and the results showed significant and clinically meaningful effects in favour of deprexis. This was the largest trial of its kind, and apart from the main results, the EVIDENT trial continues to yield many scientific publications, providing detailed insights into how effective software can help reduce the global burden of depression. Many follow-up studies are now being conducted to further investigate how deprexis can best be implemented to help patients around the globe.

Overcoming anxiety

Topic/Focus

Major anxiety disorders

Selected collaborating parties

University of Texas (Austin, US) and VA Palo Alto (US), Sheffield Hallam University and City, University of London (UK)

Anxiety disorders are among the most common mental disorders across the globe, are associated with immense suffering, psychosocial impairment, and economic costs, but only a small proportion of those affected receive adequate treatment. We have developed an effective software intervention for the three major anxiety disorders: Panic disorder, generalized anxiety disorder, and social phobia. This intervention—velibra—has demonstrated efficacy in a recently published RCT (Berger et al., 2017, Psychological Medicine). Along with our international collaborating partners, we are now finalizing an English version of velibra and will soon be launching research in the US, UK and potentially other English-speaking regions. Our vision is to make a meaningful contribution to alleviating the global burden of anxiety and thereby improve the lives of millions who are struggling to overcome anxiety.

MS Interventions

Topic/Focus

Multiple sclerosis

Selected collaborating parties

University medical centres in Hamburg and Berlin (Charité), King’s College/Guy’s Hospital (London, UK) and universities and medical centres in the USA (Los Angeles, Pennsylvania, Missouri)

Following encouraging results from a first study (Fischer et al., 2015, Lancet Psychiatry), which showed that our software (deprexis) can be used to treat depression in multiple sclerosis (MS), we are continuing to pursue this important clinical challenge. Symptoms such as fatigue and depression are exceedingly common in MS but few evidence-based treatments are available to most patients. We have developed a software-based intervention (ELEVIDA) specifically for MS-fatigue, and our novel depression intervention (MS-deprexis) is currently examined in a large, international, multicenter RCT, sponsored by the National MS Society (USA; Principal Investigator: Professor S. Gold, Berlin). Our vision is to bring effective software-based treatments to people living with MS, anywhere on the globe, easily accessible whenever they need it.

Selected Publications on GAIA R&D

Research on or about GAIA’s innovations is published regularly in peer-reviewed scientific journals. Here is a selection of recent articles.

Holtdirk, F., et al. (2021).

Results of the optimune trial: A randomized controlled trial evaluating a novel Internet intervention for breast cancer survivors

PLOS ONE

Introduction After the acute treatment phase, breast cancer patients often experience low quality of life and impaired mental health, which could potentially be improved by offering cognitive behavioural therapy (CBT) and addressing exercise and dietary habits. However, CBT and other behavioural interventions are rarely available beyond the acute treatment phase. Internet-based interventions could bridge such treatment gaps, given their flexibility and scalability. In this randomized controlled trial (RCT), we investigated the effects of such an intervention (“Optimune”) over three months.

Methods This RCT included 363 female breast cancer survivors (age range = 30–70), recruited from the community, who had completed the active treatment phase. Inclusion criteria were: breast cancer diagnosis less than 5 years ago and acute treatment completion at least 1 month ago. Participants were randomly assigned to (1) an intervention group (n = 181), in which they received care as usual (CAU) plus 12-month access to Optimune immediately after randomization, or (2) a control group (n = 182), in which they received CAU and Optimune after a delay of 3 months. Primary endpoints were quality of life (QoL), physical activity, and dietary habits at three months. We hypothesized that intervention group participants would report better QoL, more physical activity, and improved dietary habits after 3 months.

Result Intention-to-treat (ITT) analyses revealed significant effects on QoL (d = 0.27, 95% CI: 0.07–0.48) and dietary habits (d = 0.36, 95% CI: 0.15–0.56), but the effect on physical exercise was not significant (d = 0.30; 95% CI: 0.10–0.51).

Conclusion Results indicate that the adjunctive use of the investigated intervention can produce additional and lasting effects in routine outpatient psychotherapy for mild to moderate levels of depression. The study adds to the ongoing evidence on augmented effects of blended treatment. Future studies should investigate different types of blends in diverse populations by means of change-sensitive assessment strategies.


Schuster, R., et al. (2020).

Immediate and long-term effectiveness of adding an Internet intervention for depression to routine outpatient psychotherapy: Subgroup Analysis of the Evident Trial

Journal of Affective Disorders

Objective To examine immediate and long-term effectiveness of an adjunctive Internet intervention for depression in a large sample of patients undergoing routine psychotherapy.

Method The current study evaluated a subgroup of patients from the Evident trial, a randomized investigation of a 12-week minimally guided Internet intervention (Deprexis) for the treatment of mild to moderate depression. 340 adults (mean age = 43.3 years; 71.7 % female) of the original sample received routine outpatient psychotherapy during the trial period, resulting in a standard psychotherapy group (n = 174) and an augmented therapy group (n = 166). Outcomes were assessed at baseline, post-treatment and 6-month follow-up.

Result Intention-to-treat analyses indicated that combined treatment led to a greater reduction in symptoms of depression (effect size d = 0.32; p = .002), improved therapeutic progress (d = 0.36; p = .003), and higher mental health-related quality of life (d = 0.34; p = .004). There was no intervention effect on physical health-related quality of life. The same pattern was found at 6-month follow-up, and adjunctive treatment also resulted in increased rates of clinical improvement. Treatment success was independent from therapeutic orientation of combined face-to-face therapy.

Conclusion Results indicate that the adjunctive use of the investigated intervention can produce additional and lasting effects in routine outpatient psychotherapy for mild to moderate levels of depression. The study adds to the ongoing evidence on augmented effects of blended treatment. Future studies should investigate different types of blends in diverse populations by means of change-sensitive assessment strategies.


Twomey, C., et al. (2020).

Effectiveness of a tailored, integrative Internet intervention (deprexis) for depression: Updated meta-analysis

PloS one 15 (1), e0228100

Digitally delivered interventions for depression vary in many aspects, including their therapeutic orientation, depth of content, interactivity, individual tailoring, inclusion of multimedia, cost, and effectiveness. However, their effectiveness is rarely examined in intervention-specific meta-analyses. An earlier meta-analysis of eight randomized controlled trials (RCT) demonstrated the effectiveness of a tailored, integrative digital intervention (deprexis), which is delivered via the Internet. This updated meta-analysis of twelve deprexis-specific RCT with a total of N = 2901 participants confirmed the effectiveness of deprexis for depression reduction at post-intervention (g = 0.51, 95% CI: 0.40–0.62, I2 = 26%). Results were analogous when study quality, screening and randomization procedure were taken into account. Clinician guidance, developer-involvement, setting (community vs. clinical), and initial symptom severity did not have statistically significant effects on the effect size, and there was no evidence of publication bias. Thus, these findings demonstrate that deprexis can facilitate clinically relevant reduction of depressive symptoms over 8–12 weeks across a broad range of initial symptom severity, and that the intervention can be combined with other forms of depression treatment. There is now a need to study the intervention’s implementation in routine care settings as well as its long-term effectiveness and cost-effectiveness in diverse cultural and linguistic settings.


Gräfe, V., et al. (2019).

Health economic evaluation of a web-based intervention for depression: the EVIDENT-trial, a randomized controlled study

Health economics review 9 (1), 16

Background Depression often remains undiagnosed or treated inadequately. Web-based interventions for depression may improve accessibility of treatment and reduce disease-related costs. This study aimed to examine the potential of the web-based cognitive behavioral intervention “deprexis” in reducing disease-related costs.

Methods Participants with mild to moderate depressive symptoms were recruited and randomized to either a 12-week web-based intervention (deprexis) in addition to care as usual (intervention group) or care as usual (control group). Outcome measures were health-related resource use, use of medication and incapacity to work as well as relating direct health care costs. Outcomes were assessed on patients’ self-report at baseline, three months and six months.

Result A total of 1013 participants were randomized. In both groups total direct health care costs decreased during the study period, but changes from baseline did not significantly differ between study groups. Numeric differences between study groups existed in outpatient treatment costs. They could be attributed to differences in changes of costs for psychotherapeutic treatment from baseline. Whereas costs for psychotherapeutic treatment decreased in the intervention group, costs increased in the control group (− 16.8% (€80) vs. + 14.7% (€60)) (tdf = 685 = 2.57; p = 0.008).

Conclusion The study indicates the health economic potential of innovative e-mental-health programs. There is evidence to suggest that the use of deprexis over a period of 12 weeks leads to a decrease in outpatient treatment cost, especially in those related to different types of psychotherapeutic treatment.


Pearson, R., et al. (2019).

A machine learning ensemble to predict treatment outcomes following an Internet intervention for depression

Psychological medicine 49 (14), 2330-2341

Background Some Internet interventions are regarded as effective treatments for adult depression, but less is known about who responds to this form of treatment.

Method An elastic net and random forest were trained to predict depression symptoms and related disability after an 8-week course of an Internet intervention, Deprexis, involving adults (N = 283) from across the USA. Candidate predictors included psychopathology, demographics, treatment expectancies, treatment usage, and environmental context obtained from population databases. Model performance was evaluated using predictive R2 the expected variance explained in a new sample, estimated by 10 repetitions of 10-fold cross-validation.

Result An ensemble model was created by averaging the predictions of the elastic net and random forest. Model performance was compared with a benchmark linear autoregressive model that predicted each outcome using only its baseline. The ensemble predicted more variance in post-treatment depression (8.0% gain, 95% CI 0.8–15; total = 0.25), disability (5.0% gain, 95% CI −0.3 to 10; total = 0.25), and well-being (11.6% gain, 95% CI 4.9–19; total = 0.29) than the benchmark model. Important predictors included comorbid psychopathology, particularly total psychopathology and dysthymia, low symptom-related disability, treatment credibility, lower access to therapists, and time spent using certain Deprexis modules.

Conclusion A number of variables predict symptom improvement following an Internet intervention, but each of these variables makes relatively small contributions. Machine learning ensembles may be a promising statistical approach for identifying the cumulative contribution of many weak predictors to psychosocial depression treatment response.


Meyer, B., et al. (2019).

Effects of an epilepsy‐specific Internet intervention (Emyna) on depression: Results of the ENCODE randomized controlled trial

Epilepsia 60 (4), 656-668

Objective Depression and anxiety are highly prevalent among people with epilepsy (PwE) but often remain unrecognized and treated inadequately. Effective psychosocial treatments such as cognitive behavioral therapy (CBT ) are rarely available to most PwE, which is one reason electronically delivered CBT (eCBT ) is regarded as promising. This study examined an eCBT intervention, termed Emyna , that was tailored to suit the needs of PwE. It includes CBT ‐related content on depression, stress and anxiety, seizure triggers and auras, and lifestyle habits. The trial examined the efficacy of Emyna in reducing symptoms of depression (primary outcome) and anxiety as well as improving quality of life.

Methods Participants (N = 200) with epilepsy, a diagnosis of a depressive disorder, and at least moderate depressive symptoms were randomized to Emyna or care as usual. At baseline and after 3, 6, and 9 months, participants were invited to complete online questionnaires. The primary outcome was improvement of depressive symptoms at 3 months.

Result Relative to the control group, intervention group participants experienced significantly greater improvements in depression, anxiety, stress, social‐occupational impairment, and epilepsy‐related quality of life, in both intention‐to‐treat (ITT ) and per‐protocol analyses. In ITT analyses, effects of medium magnitude were observed, as measured by the Patient Health Questionnaire–9 items (Cohen d = 0.54, 95% confidence interval [CI ] = 0.25‐0.82, P < 0.001) and the Neurological Disorders Depression Inventory for Epilepsy (d = 0.51, 95% CI = 0.23‐0.79, P < 0.01). At 3 months, intervention group participants also reported fewer illness‐related days off work and fewer days hospitalized over the preceding months, compared to control group participants (P ≤ 0.05), whereas no such differences were present at baseline (P > 0.30).

Significance These findings showed that Emyna, used adjunctively to usual care, could help improve mental health, social‐occupational functioning, and quality of life among PwE. The program provides an additional treatment option that could produce clinically relevant symptom reductions and reduce key cost drivers (ie, hospitalization rates and illness‐related inability to work).

Key Points Randomized controlled trial of a novel Internet‐based cognitive‐behavioral therapy intervention to improve depression among people with epilepsy Over 3 months, use of the intervention adjunctively to usual care improved symptoms of depression, anxiety, and other aspects of mental health, with effect sizes that are above the threshold of clinical relevance (d > 0.5) Continued improvement of symptoms was observed at the 9‐month time point, although access to the intervention expired after month 6 for the intervention group Decreases in illness‐related days off work and hospitalization days were also observed


Zill, J. M., et al. (2019).

The Effectiveness of an Internet Intervention Aimed at Reducing Alcohol Consumption in Adults: Results of a Randomized Controlled Trial (Vorvida)

Deutsches Ärzteblatt International 116 (8), 127

Background In 2012, approximately 3.38 million people in Germany had an alcohol-related disorder. Internet interventions can help lower alcohol consumption, albeit with mostly small effect sizes. It is still unclear whether the effectiveness of programs aimed at lowering alcohol consumption can be improved by individually adjusting program content for each participant. We studied the effectiveness of Vorvida, a new cognitive-behavioral internet intervention with individual adjustment of content.

Methods A randomized controlled trial was conducted on 608 adults with problematic alcohol consumption. The primary outcome was self-reported alcohol consumption in the past 30 days (as determined by the Quantity-Frequency-Index, QFI) and in the past 7 days (using the Timeline Follow-Back method, TFB). The secondary outcomes were drinking behavior (binge drinking/drunkenness) and satisfaction with Vorvida. Data were collected at three time points: at baseline (t0) and three and six months later (t1, t2). Trial registration: DRKS00006104.

Result The intention-to-treat (ITT) analysis revealed significant differences between groups at time t1 with respect to alcohol consumption (QFI: d = 0.28; TFB: d = 0.42), binge drinking (d = 0.87), and drunkenness (d = 0.39). Satisfaction with the intervention was high (27.4 [standard deviation, SD: 5.3] out of 32 points). All effects persisted, or were stronger, at time t2. Alcohol consumption, as measured by the QFI, declined over the interval from t0 to t2 in both groups: from 63.69 g/day (SD: 61.4) to 32.67 g/day (SD: 39.78) in the intervention group, and from 61.64 g/day (SD: 58.84) to 43.75 g/day (SD: 43.68) in the control group.

Conclusion Vorvida was found to be effective in persons with risky, problematic alcohol consumption. Further studies should determine which elements of the program contribute most to effectiveness in routine clinical practice, and what long-term effects can be achieved.


Karyotaki, E., et al. (2018).

Is self-guided internet-based cognitive behavioural therapy (iCBT) harmful? An individual participant data meta-analysis

Psychological medicine 48 (15), 2456-2466

Background 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.

Methods 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.

Results 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.

Conclusion 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.


Pöttgen, J., et al. (2018).

Randomised controlled trial of a self-guided online fatigue intervention in multiple sclerosis

Journal of Neurology, Neurosurgery & Psychiatry 89 (9), 970-976

Objective Fatigue is a major disabling symptom in many chronic diseases including multiple sclerosis (MS), but treatment options are limited.Here, we tested the effectiveness of a self-guided , interactive, online fatigue management programme (ELEVIDA) based on principles of cognitive behavioural therapy (CBT) and related psychotherapeutic approaches (eg, mindfulness) for reducing fatigue in MS.

Methods Patients with MS and self-reported fatigue were recruited via the website of the German MS Society and assigned via an automated randomisation generator (1:1, no blocking or stratification) to a 12-week online intervention (ELEVIDA, n=139, 82% female, mean age 40.8, median patient determined disease steps (PDDS) 3.0) or a waitlist control group (n=136, 79% female, mean age 41.9, median PDDS 3.0). The primary outcome was the Chalder Fatigue Scale. Outcomes were assessed at baseline, at week 12 (postintervention) and at follow-up (week 24).

Results Compared with the control group, significantly greater reductions in Chalder Fatigue Scale scores were seen in the ELEVIDA group at week 12 (primary endpoint, intention-to-treat analysis: between-group mean difference 2.74 points; 95% CI 1.16 to 4.32; p=0.0007; effect size d=0.53), with effects sustained at week 24 (intention-to-treat analysis: between-group mean difference 2.19 points; 95% CI 0.57 to 3.82; p=0.0080).

Conclusion Our trial provides evidence for the effectiveness of a self-guided , internet-based intervention to reduce fatigue in MS. Interventions such as ELEVIDA may be a suitable low barrier, cost-effective treatment option for MS fatigue.


Berger, T., et al. (2018).

Evaluating an e-mental health program (“deprexis”) as adjunctive treatment tool in psychotherapy for depression: Results of a pragmatic randomized controlled trial

Journal of affective disorders 227, 455-462

Background Depressive disorders place a significant disease burden on individuals as well as on societies. Several web-based interventions for depression have shown to be effective in reducing depressive symptoms. However, it is not known whether web-based interventions, when used as adjunctive treatment tools to regular psychotherapy, have an additional effect compared to regular psychotherapy for depression.

Methods Adults (N = 98) with a unipolar affective disorder were recruited in routine outpatient psychotherapy practices in Germany from therapists over the course of their initial sessions and randomized within therapists to one of two active treatment conditions: regular psychotherapy or psychotherapy plus a web-based depression program („deprexis“). Primary outcome was depressive symptoms measured with the Beck Depression Inventory (BDI-II) at 12 weeks. Secondary outcomes were anxiety symptoms, somatic symptoms and quality of life at 12 weeks and six months follow-up. The study also included an assessment of the working alliance after six and 12 weeks.

Results The combination of psychotherapy with the web-based program was more effective than psychotherapy alone at 12 weeks, with medium between-group effect sizes on primary depressive symptoms (Cohen’s d = .51) and small to medium between-group effect sizes on secondary outcomes (Cohen’s d = .07–.55). Furthermore, we did not observe negative side effects in the blended format, e.g., a lower working alliance than in psychotherapy alone.

Limitations The study had a smaller than planned sample size and the dropout rate at follow-up was high.

Conclusion This study provides first evidence that the use of a web-based program as an adjunctive tool in regular psychotherapy could be a promising option to consider in future treatment for depression.


Klein, J. P., et al. (2017).

Time to remission from mild to moderate depressive symptoms: one year results from the EVIDENT-study, an RCT of an internet intervention for depression

Behaviour research and therapy 97, 154-162

Background Internet interventions are effective in treating depressive symptoms but few studies conducted a long-term follow-up. The aim of this study was to test the effectiveness of an internet intervention in increasing the remission rate over a twelve months period.

Methods A total of 1013 participants with mild to moderate depressive symptoms were randomized to either care as usual alone or a 12-week internet intervention (Deprexis) plus usual care. Self-rated depression severity (PHQ-9) was assessed regularly over twelve months.

Results Remission rates over time were significantly higher in the intervention group (Cox regression: hazard ratio [HR] 1.31; p = 0.009). The intervention was more effective in the subgroup not taking antidepressant medication (Cox regression: HR 1.88; p < 0.001). PHQ-change from baseline was greater in the intervention group (linear mixed model [LMM]: p < 0.001) with the between-group effect gradually decreasing from d = 0.36 at three months to d = 0.13 at twelve months (LMM: group by time interaction: p < 0.001).

Conclusion This internet intervention can contribute to achieving remission in people with mild to moderate depressive symptoms, especially if they are not on antidepressant medication (Trial Registration: NCT01636752).


Beevers, C. G., et al. (2017).

Effectiveness of an internet intervention (Deprexis) for depression in a United States adult sample: A parallel-group pragmatic randomized controlled trial.

Journal of Consulting and Clinical Psychology, 85(4), 367-380.

Objective: To examine the effectiveness of an Internet intervention for depression with a randomized, controlled trial in a large sample of adults recruited from the United States.

Method The current study examines the effectiveness of Deprexis, an Internet treatment for depression that was provided with relatively minimal support. There were 376 treatment-seeking adults (mean age = 32 years; 74% female; 77% Caucasian, 7% Asian, 7% multiple races, 4% African American, and 11% Hispanic/Latino) with elevated depression (Quick Inventory of Depressive Symptoms-Self-Report [QIDS-SR] > = 10) who were randomized to receive an 8-week course of treatment immediately (n = 285) or after an 8-week delay (n = 91; i.e., waitlist control).

Result Intention-to-treat analyses indicated that treatment was associated with greater reduction in self-reported symptoms of depression (effect size d = .80) and 12 times greater likelihood of experiencing at least 50% symptom improvement compared with waitlist control. Similar effects were observed for several secondary outcomes, such as interviewer-rated depression symptoms, well-being, and depression-related disability. Treatment effects for symptoms of social anxiety, panic, and traumatic intrusions were relatively small.

Conclusion Results suggest that Deprexis can produce symptomatic improvement among depressed adults recruited from the United States. Additional research is needed that examines whether improvements are maintained over time and who is particularly likely to respond to this form of treatment.


Karyotaki, E., et al. (2017).

Efficacy of Self-guided Internet-Based Cognitive Behavioral Therapy in the Treatment of Depressive Symptoms: A Meta-analysis of Individual Participant Data.

JAMA Psychiatry, 74(4), 351-359.

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.

Result 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 < .001). None of the examined participant and study-level variables moderated treatment outcomes.

Conclusions and relevance Self-guided iCBT is effective in treating depressive symptoms. The use of meta-analyses of individual participant data provides substantial evidence for clinical and policy decision making because self-guided iCBT can be considered as an evidence-based first-step approach in treating symptoms of depression. Several limitations of the iCBT should be addressed before it can be disseminated into routine care.


Klein, J.-P., et al. (2016).

Effects of a psychological internet intervention in the treatment of mild to moderate depressive symptoms: results of the EVIDENT study, a randomized controlled trial.

Psychotherapy and Psychosomatics, 85(4), 218-228.

Background Mild to moderate depressive symptoms are common but often remain unrecognized and treated inadequately. We hypothesized that an Internet intervention in addition to usual care is superior to care as usual alone (CAU) in the treatment of mild to moderate depressive symptoms in adults.

Methods This trial was controlled, randomized and assessor-blinded. Participants with mild to moderate depressive symptoms (Patient Health Questionnaire, PHQ-9, score 5-14) were recruited from clinical and non-clinical settings and randomized to either CAU or a 12-week Internet intervention (Deprexis) adjunctive to usual care. Outcomes were assessed at baseline, 3 months (post-assessment) and 6 months (follow-up). The primary outcome measure was self-rated depression severity (PHQ-9). The main analysis was based on the intention-to-treat principle and used linear mixed models.

Results A total of 1,013 participants were randomized. Changes in PHQ-9 from baseline differed signixFB01;cantly between groups (t825 = 6.12, p < 0.001 for the main effect of group). The post-assessment between-group effect size in favour of the intervention was d = 0.39 (95% CI: 0.13-0.64). It was stable at follow-up, with d = 0.32 (95% CI: 0.06-0.69). The rate of participants experiencing at least minimally clinically important PHQ-9 change at the post-assessment was higher in the intervention group (35.6 vs. 20.2%) with a number needed to treat of 7 (95% CI: 5-10).

Conclusion: The Internet intervention examined in this trial was superior to CAU alone in reducing mild to moderate depressive symptoms. The magnitude of the effect is clinically important and has public health implications.


Meyer, B., et al. (2015).

Effects of an Internet intervention (Deprexis) on severe depression symptoms: Randomized controlled trial.

Internet Interventions, 2(1), 48-59.

Background: Studies have shown that certain Internet interventions can help alleviate depression. However, many such interventions contain personal support elements, making it difficult to ascertain whether the program or the support drives the effects. Studies are needed to investigate whether Internet interventions contribute to symptom reduction even when they are delivered without personal support, and even among severely depressed individuals who often receive other forms of treatment.

Objective: This randomized controlled trial aimed to examine the effect of an Internet intervention that was deployed without personal support (“Deprexis”) among adults with initially severe depression symptoms.

Methods: Adults recruited from a range of sources who had exceeded the threshold for severe depression (PHQ-9 ≥ 15) in a pre-screening assessment and met inclusion criteria were randomized (N = 163) to the intervention (3 months program access; n = 78) or care-as-usual/waitlist control (n = 85). A diagnostic screening interview was administered by telephone at baseline to all participants. Online assessments were administered at baseline, 3 months (post-treatment), and 6 months (follow-up). The main outcome was the Patient Health Questionnaire (PHQ-9) between baseline and post-treatment.

Results: Eighty-two percent of randomized participants were reached for the post-treatment assessment. Results for the intention-to-treat (ITT) sample showed significant intervention effects on depression reduction between baseline and post-treatment (linear mixed model [MM], F1,155.6 = 9.00, p < .01, for the time by condition interaction), with a medium between-group effect size, Cohen’s d = 0.57 (95% CI: 0.22–0.92). Group differences in depression severity at follow-up were marginally significant in the ITT sample, t (119) = 1.83, p = 0.07, and smaller than at post-treatment (PHQ-9, d = 0.33, 95% CI: −0.03–0.69). The number needed to treat (NNT) at post-treatment was 5, with 38% of participants in the intervention group achieving response (at least 50% PHQ-9 symptom change, plus post-treatment score <10), compared to 17% in the control group, p < 0.01. Effects on secondary outcomes, including anxiety, health-related quality of life, and somatic symptoms, were not significant, with the exception of significant effects on anxiety reduction in PP analyses. Early ratings of program helpfulness/alliance (after 3 weeks) predicted pre–post depression reduction, controlling for baseline severity and early symptom change.

Conclusion: These results replicate and extend previous findings by showing that Deprexis can facilitate symptomatic improvement over 3 months and, perhaps to a lesser degree, up until 6 months among adults with initially severe depression.


Bower, P., et al. (2013).

Influence of initial severity of depression on effectiveness of low intensity interventions: meta-analysis of individual patient data.

BMJ, 346, f540.

Objective: To assess how initial severity of depression affects the benefit derived from low intensity interventions for depression.

Design: Meta-analysis of individual patient data from 16 datasets comparing low intensity interventions with usual care.

Setting: Primary care and community settings.

Participants: 2470 patients with depression.

Interventions: Low intensity interventions for depression (such as guided self help by means of written materials and limited professional support, and internet delivered interventions).

Main outcome measures: Depression outcomes (measured with the Beck Depression Inventory or Center for Epidemiologic Studies Depression Scale), and the effect of initial depression severity on the effects of low intensity interventions.

Results: Although patients were referred for low intensity interventions, many had moderate to severe depression at baseline. We found a significant interaction between baseline severity and treatment effect (coefficient −0.1 (95% CI −0.19 to −0.002)), suggesting that patients who are more severely depressed at baseline demonstrate larger treatment effects than those who are less severely depressed. However, the magnitude of the interaction (equivalent to an additional drop of around one point on the Beck Depression Inventory for a one standard deviation increase in initial severity) was small and may not be clinically significant.

Conclusion: The data suggest that patients with more severe depression at baseline show at least as much clinical benefit from low intensity interventions as less severely depressed patients and could usefully be offered these interventions as part of a stepped care model.


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