Social phobia moderates the outcome in the EVIDENT study: A randomized controlled trial on an Internet-based psychological intervention for mild to moderate depressive symptoms

Acknowledgement: Jan Philipp Klein received payment for presentations, workshops, and books on psychotherapy for chronic depression and psychiatric emergencies. Björn Meyer is employed as research director at GAIA AG, the company that developed, owns, and operates the web intervention investigated in this trial. All other authors and members of the EVIDENT study team report no financial or other relationship relevant to this article. Trial registration: ClinicalTrials.gov (identifier: NCT01636752).
Funding was provided by German Federal Ministry of Health Grant II A 5-2512 FSB 052. The funding body played no role in study design, data collection, analysis, or interpretation of the data. Additional funding was provided by GAIA AG (Hamburg, Germany), which provided all participants in the trial with licenses for the web intervention (Deprexis) as well as technical support. GAIA AG played no role in data collection, data analysis, or the decision to publish the results.

Deprexis is an Internet-based psychological intervention for depression (Twomey, O’Reilly, & Meyer, 2017). A meta-analysis including eight controlled trials on Deprexis found an effect size of g = .54 with no difference between trials that did or did not provide clinician support and no evidence of publication or developer-involvement bias (Twomey et al., 2017).

For personalized treatment selection (Cohen & DeRubeis, 2018), it is important to know for which specific person with elevated depressive symptoms interventions such as Deprexis work better than other treatments or no treatment at all (Beevers et al., 2017). Moderation analysis allows studying interactions between treatment and person characteristics, but this approach requires a relatively large sample size.

The EVIDENT study (Klein et al., 2013, 2016; Klein, Späth, et al., 2017), which was reanalyzed here, included a sample size that is sufficiently large to perform moderation analyses. This was a randomized controlled trial comparing an intervention group with access to Deprexis and care-as-usual with a control group with access to care-as-usual only in N = 1,013 participants with mild to moderate depressive symptoms. Previous moderation analyses showed that Deprexis was most effective compared to the control group (CG) in participants without antidepressant medication and in those without concomitant psychosocial care (Klein et al., 2016), as well as in those with more positive attitudes toward Internet interventions (Schröder et al., 2018).

The present study evaluated whether specific anxiety-related comorbidities would moderate the intervention effect on depression outcome. Evaluating anxiety-related disorders as moderators of outcomes in interventions for depression is important, not only because these disorders are highly comorbid but also because anxiety-related comorbidities put individuals with depression at risk of a negative outcome (e.g., Coryell et al., 2012; Fava et al., 2008; Klein, Späth, et al., 2017). Therefore, there is a clinical need for effective treatments for individuals with depression and anxiety-related comorbidities. In a more recent study, Dold et al. (2017) reported that specific anxiety-related comorbidities can have no, detrimental (comorbid generalized anxiety disorder), or beneficial (comorbid panic disorder) effects on depression outcome. The effects of specific anxiety-related comorbidities on depression outcome might be neutralized when exploring anxiety-related comorbidity in general. In line with this argumentation, a recent meta-analysis of self-guided Internet-based interventions for depression (Karyotaki et al., 2017) showed that patients’ anxiety-related comorbidity in general did not moderate intervention effects on outcome. Because specific anxiety-related comorbid disorders were not tested as moderators in this meta-analysis, the current study explored whether specific anxiety-related comorbidities moderate depression outcome. Data from the EVIDENT study were therefore reanalyzed to address the following research questions (RQs).
RQ 1: Do specific anxiety-related comorbidities moderate the intervention effect on depression outcome?

The following eight specific anxiety-related comorbidities were evaluated as moderators within one statistical model: generalized anxiety disorder, social phobia, panic disorder, agoraphobia, panic disorder with agoraphobia, specific phobia, posttraumatic stress disorder, and obsessive–compulsive disorder. The statistical model included 12 moderators in total. Besides the eight specific anxiety-related comorbidities, the three previously identified significant moderators in the EVIDENT trial (antidepressant medication, concomitant psychosocial treatment, attitudes toward Internet interventions) were added to control for the known moderators, and initial depression severity was entered to explore whether moderating effects are specific to anxiety or more general to the severity of depression. Continuous scale scores (RQ 1a) as well as clinically important changes (RQ 1b) were used as depression outcomes.
RQ 2: If one or more significant moderator(s) emerged when including all 12 moderators, would this result depend on the presence of the other moderators in the statistical model?
RQ 3: Can moderating effects be replicated in randomly selected split halves of the sample?

The study was approved by the Ethics Committee of the German Psychological Association (SM 04_2012) and registered in ClinicalTrials.gov (NCT01636752). See the Appendix for data transparency: multiple uses of data collected from the same sample. The protocol was published by Klein et al. (2013), and the flowchart including the follow-up assessments was published by Klein, Späth, et al. (2017). All participants provided informed consent online.

Inclusion criteria were as follows: mild to moderate depressive symptoms, between 5 and 14 points on the Patient Health Questionnaire−9 (PHQ-9; Kroenke, Spitzer, & Williams, 2001), age between 18 and 65 years, Internet access, and sufficient knowledge in German language. Exclusion criteria included acute suicidality, lifetime diagnosis of bipolar disorder, and schizophrenia.

In total, N = 1,013 participants were randomized to the following two conditions: Deprexis group with access to care-as-usual (Deprexis; n = 509, M = 42.8 years old, 68.8% female) or control group with access to care-as-usual (CG; n = 504, M = 42.9 years old, 68.5% female). Randomization (1:1) to the two groups (Deprexis or CG) was stratified by PHQ-9 (PHQ-9 < 10 vs. PHQ-9 ≥ 10), because participants with PHQ-9 < 10 (mild depressive symptoms) received unguided Deprexis, and participants with PHQ-9 ≥ 10 (moderate depressive symptoms) received guided Deprexis. An independent investigator used a computerized random number generator for the allocation schedule.

Patient Health Questionnaire−9 (PHQ-9; Kroenke et al., 2001)

The PHQ-9 is a self-report including nine items on depressive symptoms. The continuous PHQ-9 score is the primary outcome in the EVIDENT trial. For the present study, the continuous PHQ-9 scores as well as minimal clinically important differences (Löwe, Unützer, Callahan, Perkins, & Kroenke, 2004) were used. Moreover, participants were categorized into those with mild or moderate depressive symptoms in the EVIDENT trial based on the PHQ-9 cutoff of 10. A recent meta-analysis by Levis, Benedetti, and Thombs (2019) reported maximized sensitivity and specificity for a cutoff score of 10 or higher (in studies with a semistructured interview: sensitivity = .88, specificity = .85).

Web Screening Questionnaire (WSQ; Donker, van Straten, Marks, & Cuijpers, 2009)

The WSQ is a brief online questionnaire consisting of 15 items that screen for common mental disorders. Cutoffs are provided to dichotomize the participants as having either a negative or a positive screening for the disorder (the cutoff scores can be seen in Web Screening Questionnaire, n.d.). Validation studies of these cutoff scores compared the WSQ screening results with the Composite International Diagnostic Interview in 502 individuals from the general population (Donker et al., 2009) and with the Mini-International Neuropsychiatric Interview—Plus in 1,292 adults, 1,117 from the general population and 175 psychiatric outpatients (Meuldijk et al., 2017). For the eight anxiety-related disorders investigated here, sensitivity ranged from .72 (social phobia) to 1.00 (agoraphobia) and specificity from .44 (panic disorder) to .77 (panic disorder and agoraphobia) in the study by Donker et al. (2009). In the study by Meuldijk et al. (2017), sensitivity ranged from .66 (generalized anxiety disorder) to 1.00 (panic disorder/specific phobia) and specificity from .52 (posttraumatic stress disorder) to .97 (panic disorder and agoraphobia).

Attitudes Toward Psychological Online Interventions Questionnaire (APOI; Schröder et al., 2015)

The APOI assesses attitudes toward Internet interventions on these four dimensions: skepticism and perception of risks, confidence in effectiveness, technologization threat, and anonymity benefits.

Quick Inventory of Depressive Symptomatology—Clinician Rating (QIDS; Rush et al., 2003)

The QIDS-C comprises 16 items and assesses the severity of depressive symptoms. The raters were blinded and trained (at least one audiotaped interview and observation of ratings by experienced raters; see Klein et al., 2013).

In both conditions (Deprexis and CG), participants had access to care-as-usual and were allowed to use antidepressant medication or psychotherapy or any other treatment, and this was not influenced by the investigators.

Deprexis

In addition to access to care-as-usual, participants with mild depressive symptoms (PHQ-9 scores of 5–9) received unguided Deprexis for 3 months, whereas participants with moderate depressive symptoms (PHQ-9 scores of 10–14) received the same plus regular e-mail support by trained clinicians. The supportive messages aimed primarily at increasing adherence with the intervention. Deprexis includes the following modules: (1) psychoeducation, (2) behavioral activation, (3) cognitive modification, (4) mindfulness and acceptance, (5) interpersonal skills, (6) relaxation exercises, physical activity and lifestyle modification, (7) problem-solving, (8) expressive writing and schema-focused contents, (9) positive psychology and emotion-focused interventions, (10) dream work and emotion-focused interventions. According to Fuhr et al. (2018), adherence measures, that is, time using the program M = 429.70 min (SD = 294.10) and number of sessions (at least 10-min session) M = 8.32 (SD = 4.71), were correlated with depression outcome in the Deprexis condition.

CG

Access to Deprexis was offered after the 12-month follow-up. Until the 12-month follow-up, the CG had access to care-as-usual but not to Deprexis.

For RQ 1a, one linear multilevel model with the continuous PHQ-9 scores as dependent variable, the full maximum likelihood estimation, and a random intercept was performed in SPSS25. A random intercept model was selected because a model including the random intercept and the random slope did not converge. The multilevel model had two levels: assessments as Level 1 nested within study participants as Level 2. The four main assessment points of the EVIDENT trial were included (baseline, 3-month follow-up, 6-month follow-up, 12-month follow-up). As fixed effects, condition was entered as factor (Deprexis = 1 vs. CG = 0) and the following 12 moderators were included within one linear multilevel model. The eight WSQ anxiety-related disorders (screening positive = 1 vs. screening negative = 0), the three already known moderators (antidepressant medication, concomitant psychosocial treatment, attitudes toward Internet interventions), and initial depression severity. Time was included as a fixed effect. The baseline assessment was coded as 0, the exact time (in days) since baseline was used for the three follow-up assessments (3-month, 6-month, 12-month) given that the assessments did not occur at the exact intervals described. Besides main effects, two-way interactions (Condition × Moderators, Time × Moderators, Time × Condition) and three-way interactions (Time × Condition × Moderators) were examined.

To address RQ 1b, we performed one multilevel model for categorical outcomes, specifically, a binary logistic model within Generalized Estimating Equations (GEE) in SPSS25. Before running this model, participants were coded as having reached clinically important PHQ-9 change (coded as 1) or not having reached clinically important PHQ-9 change (coded as 0) at each assessment point (except baseline) using the suggested cutoff of at least 5 points of improvement (Löwe et al., 2004). This dichotomized PHQ-9 change score at the three follow-up assessments was the dependent variable in the model, for which the full maximum likelihood estimation was applied. Again, this multilevel model had two levels: assessments as Level 1 nested within study participants as Level 2. In GEE, participants were designated as subject variable, and time of the assessments (days since baseline) as within-subject variable (unstructured working correlation matrix). As fixed effects, condition was entered as a factor (Deprexis = 1 vs. CG = 0) and the 12 potential moderators (see earlier) were included within one model. Besides main effects, two-way interactions (Condition × Moderators) were examined.

For RQ 2, multilevel models like the ones described for RQ 1a and RQ 1b were performed, but only with the significant moderator(s) entered in these two models.

To address RQ 3, the analyses described earlier were performed in randomly selected split halves. The split halves of the total sample were randomly selected in SPSS using select cases, random sample of cases, approximately 50% of the cases.

For significant moderating effects in models with continuous PHQ-9 scores as dependent variable, R2 and f2 were calculated (full model vs. model excluding the significant three-way interaction). R2 refers to the proportion of variance in depression change explained by the moderator, and f2 is the related effect size measure (.02 small, .15 medium, .35 large).

Anxiety-related comorbidities did not differ between Deprexis and CG (see Table 1).

Of all 12 potential moderators, only social phobia was a significant moderator when investigating continuous PHQ-9 scores as outcome, t(2186.73) = −2.14, p = .032, R2 = .001, f2 = .001 (see Table 2). The moderating effect was in favor of Deprexis.

Of all 12 potential moderators, only social phobia moderated the depression outcome (again in favor of Deprexis) when evaluating clinically important PHQ-9 changes as outcome, Wald (1) = 4.40, p = .036, Exp(b) = 1.650 (see Table 3).

After removing the 11 moderators not reaching significance in RQ 1, social phobia moderated continuous PHQ-9 scores as outcome, t(2512.52) = −2.41, p = .016, R2 = .001, f2 = .001 (see Table 4) and clinically important PHQ-9 changes, Wald (1) = 6.09, p = .014, Exp(b) = 1.731 (see Table 5) in favor of Deprexis.

Continuous PHQ-9 scores and 12 potential moderators: The moderating effect of social phobia was replicated in the first split half, t(1076.73) = −2.31, p = .021, R2 = .002, f2 = .002, but not in the second, t(1108.70) = −.231, p = .817. Clinically important PHQ-9 changes and 12 potential moderators: Social phobia was no moderator in the first split half, Wald (1) = 3.61, p = .057, and in the second, Wald (1) = 1.05, p = .305. Continuous PHQ-9 scores and only social phobia as moderator: Social phobia was a moderator in the first split half, t(1217.13) = −3.01, p = .003, R2 = .005, f2 = .005, but not in the second, t(1296.86) = −.30, p = .761. Clinically important PHQ-9 changes and only social phobia as moderator: Social phobia was a moderator in the first split half, Wald (1) = 5.70, p = .017, Exp(b) = 2.143, but not in the second, Wald (1) = 1.86, p = .172. The moderating effects were in favor of Deprexis.

In total, 12 potential moderators were evaluated, and only the participants’ comorbid social phobia moderated the intervention effect on the outcome. Participants with comorbid social phobia had a more favorable depression outcome in response to Deprexis compared to CG. This was the case when continuous PHQ-9 scores as well as clinically important PHQ-9 changes were the outcome. The previously identified moderators (antidepressant medication, concomitant psychosocial treatment, attitudes toward Internet interventions) in the EVIDENT trial were not significant anymore in the statistical model including the anxiety-related comorbidities. Moreover, the moderating effect was specific to social phobia and was not related to general depression severity. Furthermore, social phobia was still a moderator after excluding the other 11 potential moderators. This means that the moderating effect of social phobia did not depend on the other moderators in the statistical model. Yet, the moderating effects did not even reach small effect sizes, accounted for less than 1% of the variance in change in depressive symptoms, and showed limited reproducibility.

To address the concerns about the replicability of findings of post hoc moderation analyses, future studies could prospectively select participants with depressive symptoms and comorbid social phobia as well as those without comorbid social phobia and allocate both samples randomly to either Deprexis or CG. These future studies should assess social phobia (and other anxiety-related comorbidities) with standardized clinical interviews and dimensional scales, because the major shortcoming of the present study is that the WSQ was the only measure to assess anxiety-related comorbidities. The WSQ is a self-report with relatively high false positive rates. Regarding the significant moderator social phobia, positive predictive values for social phobia were .40 (Donker et al., 2009) and .15 (Meuldijk et al., 2017).

If the results can be replicated, clinical implications would be to offer Deprexis particularly to adults with mild to moderate depressive symptoms and concurrent social phobia.

Arndt, A., Lutz, W., Rubel, J., Berger, T., Schröder, J., Späth, C., . . .Moritz, S. (2019). Identifying change-dropout patterns during an internet-based intervention for depression by applying the Muthen-Roy model. Cognitive Behaviour Therapy. Advance online publication.

Beevers, C. G., Pearson, R., Hoffman, J. S., Foulser, A. A., Shumake, J., & Meyer, B. (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, 367–380. 10.1037/ccp0000171

Boschloo, L., Cuijpers, P., Karyotakia, E., Berger, T., Moritz, S., Meyer, B., & Klein, J. P. (2019). Symptom-specific effectiveness of an internet-based intervention in the treatment of mild to moderate depressive symptomatology: The potential of network estimation techniques. Behaviour Research and Therapy. Advance online publication. 10.1016/j.brat.2019.103440

Cohen, Z. D., & DeRubeis, R. J. (2018). Treatment selection in depression. Annual Review of Clinical Psychology, 14, 209–236. 10.1146/annurev-clinpsy-050817-084746

Coryell, W., Fiedorowicz, J. G., Solomon, D., Leon, A. C., Rice, J. P., & Keller, M. B. (2012). Effects of anxiety on the long-term course of depressive disorders. British Journal of Psychiatry, 200, 210–215. 10.1192/bjp.bp.110.081992

Dold, M., Bartova, L., Souery, D., Mendlewicz, J., Serretti, A., Porcelli, S., . . .Kasper, S. (2017). Clinical characteristics and treatment outcomes of patients with major depressive disorder and comorbid anxiety disorders—Results from a European multicenter study. Journal of Psychiatric Research, 91, 1–13. 10.1016/j.jpsychires.2017.02.020

Donker, T., van Straten, A., Marks, I., & Cuijpers, P. (2009). A brief web-based screening questionnaire for common mental disorders: Development and validation. Journal of Medical Internet Research, 11, e19. 10.2196/jmir.1134

Fava, M., Rush, A. J., Alpert, J. E., Balasubramani, G. K., Wisniewski, S. R., Carmin, C. N., . . .Trivedi, M. H. (2008). Difference in treatment outcome in outpatients with anxious versus nonanxious depression: A STAR*D report. American Journal of Psychiatry, 165, 342–351. 10.1176/appi.ajp.2007.06111868

Fuhr, K., Schröder, J., Berger, T., Moritz, S., Meyer, B., Lutz, W., . . .Klein, J. P. (2018). The association between adherence and outcome in an internet intervention for depression. Journal of Affective Disorders, 229, 443–449. 10.1016/j.jad.2017.12.028

Gräfe, V., Berger, T., Hautzinger, M., Hohagen, F., Lutz, W., Meyer, B., . . .Greiner, W. (2019). Health economic evaluation of a web-based intervention for depression: The EVIDENT-trial, a randomized controlled study. Health Economics Review, 9, 16. 10.1186/s13561-019-0233-y

Karyotaki, E., Riper, H., Twisk, J., Hoogendoorn, A., Kleiboer, A., Mira, A., . . .Cuijpers, P. (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, 351–359. 10.1001/jamapsychiatry.2017.0044

Klein, J. P., Berger, T., Schröder, J., Späth, C., Meyer, B., Caspar, F., . . .Hohagen, F. (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, 218–228. 10.1159/000445355

Klein, J. P., Berger, T., Schröder, J., Späth, C., Meyer, B., Caspar, F., . . .Moritz, S. (2013). The EVIDENT-trial: Protocol and rationale of a multicenter randomized controlled trial testing the effectiveness of an online-based psychological intervention. BMC Psychiatry, 13, 239. 10.1186/1471-244X-13-239

Klein, J. P., Gamon, C., Späth, C., Berger, T., Meyer, B., Hohagen, F., . . .Schröder, J. (2017). Does recruitment source moderate treatment effectiveness? A subgroup analysis from the EVIDENT study, a randomised controlled trial of an internet intervention for depressive symptoms. British Medical Journal, 7, e015391. 10.1136/bmjopen-2016-015391

Klein, J. P., Späth, C., Schröder, J., Meyer, B., Greiner, W., Hautzinger, M., . . .Berger, T. (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. 10.1016/j.brat.2017.07.013

Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16, 606–613. 10.1046/j.1525-1497.2001.016009606.x

Levis, B., Benedetti, A., & Thombs, B. D. (2019). Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: Individual participant data meta-analysis. British Medical Journal, 365, l1476. 10.1136/bmj.l1476

Löwe, B., Unützer, J., Callahan, C. M., Perkins, A. J., & Kroenke, K. (2004). Monitoring depression treatment outcomes with the Patient Health Questionnaire-9. Medical Care, 42, 1194–1201. 10.1097/00005650-200412000-00006

Lutz, W., Arndt, A., Rubel, J., Berger, T., Schröder, J., Späth, C., . . .Moritz, S. (2017). Defining and predicting patterns of early response in an internet-based intervention for depression. Journal of Medical Internet Research, 19, e206. 10.2196/jmir.7367

Maas, I. L., Nolte, S., Walter, O. B., Berger, T., Hautzinger, M., Hohagen, F., . . .Rose, M. (2017). The regression discontinuity design showed to be a valid alternative to a randomized controlled trial for estimating treatment effects. Journal of Clinical Epidemiology, 82, 94–102. 10.1016/j.jclinepi.2016.11.008

Meuldijk, D., Giltay, E. J., Carlier, I. V., van Vliet, I. M., van Hemert, A. M., & Zitman, F. G. (2017). A validation study of the Web Screening Questionnaire (WSQ) compared with the Mini-International Neuropsychiatric Interview-Plus (MINI-Plus). JMIR Mental Health, 4, e35. 10.2196/mental.5453

Moritz, S., Hörmann, C. C., Schröder, J., Berger, T., Jacob, G. A., Meyer, B., . . .Klein, J. P. (2013). Beyond words: Sensory properties of depressive thoughts. Cognition and Emotion, 28, 1047–1056. 10.1080/02699931.2013.868342

Rush, A. J., Trivedi, M. H., Ibrahim, H. M., Carmody, T. J., Arnow, B., Klein, D. N., . . .Keller, M. B. (2003). The 16-item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): A psychometric evaluation in patients with chronic major depression. Biological Psychiatry, 54, 573–583. 10.1016/S0006-3223(02)01866-8

Schneider, B. C., Schröder, J., Berger, T., Hohagen, F., Meyer, B., Späth, C., . . .Klein, J. P. (2018). Bridging the “digital divide”: A comparison of use and effectiveness of an online intervention for depression between baby boomers and millennials. Journal of Affective Disorders, 236, 243–251. 10.1016/j.jad.2018.04.101

Schröder, J., Berger, T., Meyer, B., Lutz, W., Hautzinger, M., Späth, C., . . .Moritz, S. (2017). Attitudes towards internet interventions among psychotherapists and individuals with mild to moderate depression symptoms. Cognitive Therapy and Research, 41, 745–756. 10.1007/s10608-017-9850-0

Schröder, J., Berger, T., Meyer, B., Lutz, W., Späth, C., Michel, P., . . .Moritz, S. (2018). Impact and change of attitudes toward Internet interventions within a randomized controlled trial on individuals with depression symptoms. Depression and Anxiety, 35, 421–430. 10.1002/da.22727

Schröder, J., Sautier, L., Kriston, L., Berger, T., Meyer, B., Späth, C., . . .Moritz, S. (2015). Development of a questionnaire measuring attitudes towards psychological online interventions—The APOI. Journal of Affective Disorders, 187, 136–141. 10.1016/j.jad.2015.08.044

Späth, C., Hapke, U., Maske, U., Schröder, J., Moritz, S., Berger, T., . . .Klein, J. P. (2017). Characteristics of participants in a randomized trial of an internet intervention for depression (EVIDENT) in comparison to a national sample (DEGS1). Internet Interventions, 9, 46–50. 10.1016/j.invent.2017.05.003

Twomey, C., O’Reilly, G., & Meyer, B. (2017). Effectiveness of an individually-tailored computerised CBT programme (Deprexis) for depression: A meta-analysis. Psychiatry Research, 256, 371–377. 10.1016/j.psychres.2017.06.081

Web Screening Questionnaire for common mental disorders (WSQ). (n.d.). Web Screening Questionnaire for common mental disorders (WSQ). Retrieved from http://webscreeningquestionnaire.org/files/WSQ.pdf

The data reported in this article have been previously published and/or were collected as part of a larger data collection (at one or more points in time). Findings from the data collection of the EVIDENT trial have been reported in separate articles. Moritz et al. (2013) focused on sensory properties of depressive thoughts; Schröder et al. (2015) focused on the development of a questionnaire measuring attitudes towards psychological online interventions; Klein et al. (2016) focused on the treatment outcome at posttreatment and follow-up as well as concomitant psychosocial care and antidepressant medication as moderators; Klein, Späth, et al. (2017) focused on time to remission and the following four moderator variables: antidepressant medication, outpatient psychiatric treatment, initial depression severity, and depression diagnosis; Klein, Gamon, et al. (2017) focused on recruitment source as moderator of the treatment outcome; Lutz et al. (2017) focused on patterns of early response; Maas et al. (2017) focused on regression discontinuity design; Schröder et al. (2017) focused on attitudes towards Internet interventions among psychotherapists and study participants; Späth et al. (2017) focused on a comparison between the study sample and a national sample; Fuhr et al. (2018) focused on the influence of adherence on the treatment outcome; Schröder et al. (2018) focused on the influence of attitudes toward Internet interventions on the treatment outcome; Schneider et al. (2018) focused on a comparison of the treatment outcome between Baby Boomers and Millennials; Arndt et al. (2019) focused on change-drop-out patterns; Boschloo et al. (2019) focused on symptom-specific effectiveness of the intervention using network estimation techniques; Gräfe et al. (2019) focused on health economic evaluation; the current article focused on anxiety-related comorbidities as moderators of the intervention effect on the treatment outcome, and this research question was not addressed in any of the other articles.

Submitted: March 18, 2019 Revised: July 26, 2019 Accepted: July 29, 2019