App-Based Psychotherapy of Panic Disorder With Self-Guided Exposure in Virtual Reality

A Randomized Controlled Trial

Background: Patients with panic disorder often suffer from temporary unavailability of care. The smartphone app Invirto (IVT) provides digital treatment for panic disorder comprising self-guided exposure in virtual reality. The aim of this trial was to assess the efficacy of Invirto.

Methods: In a randomized, controlled, non-blinded trial, IVT was compared with care as usual (CAU) in patients with panic disorder (preregistration: DRKS00027585). The endpoints were assessed online before treatment (t0) and at 3 months (t1). The primary endpoint was the change in symptoms of anxiety, as measured with the Beck Anxiety Inventory (BAI), between the groups. The secondary endpoints were the patients’ scores on the following assessment instruments, all in their German versions: the Panic and Agoraphobia Scale (PAS), the Beck Depression Inventory (BDI-II), a questionnaire on patient satisfaction (Client Satisfaction Questionnaire, CSQ-8), the Acceptance and Action Questionnaire (AAQ-II), and quality of life as a global item in the World Health Organization Quality of Life Questionnaire (WHOQOL-BREF).

Results: One hundred twenty-four participants were included. The intention-to-treat analysis revealed greater improvement with IVT than with CAU with respect to both the primary endpoint (BAI, d = –0.46; 95% confidence interval [–0.87; –0.04]) and the secondary endpoints (PAS, d = –0.63 [–1.05; –0.22]; BDI-II, d = –0.44 [–0.86; –0.02]; AAQ-II, d = –0.42 [–0.84; –0.01]), except for WHOQOL-BREF (p = 0.216).

Conclusion: A digital treatment with virtual exposure can lessen anxiety, panic, and depressive symptoms and improve mental flexibility. In further studies, IVT should be compared with an active control group.

Cite this as: Schultz J, Baumeister A, Schmotz S, Schuurmans L, Jelinek L: App-based psychotherapy of panic disorder with self-guided exposure in virtual reality—a randomized controlled trial. Dtsch Arztebl Int 2025; 122: 1–6. DOI: 10.3238/arztebl.m2024.0246

Panic disorder is characterized by recurrent and unpredictable panic attacks and constant worrying about further attacks. The 12-month prevalence in the general population is 1.7–2.4% (1, 2). Panic attacks are frequently accompanied by physical symptoms such as feelings of suffocation, tachycardia, or chest pain. Persons with panic disorder often adopt dysfunctional forms of behavior, e.g., avoidance behavior, to prevent future attacks. This may lead to substantial restrictions of their daily activities and reduced quality of life (3, 4).

The treatment guidelines recommend cognitive behavioral therapy (CBT) with exposure therapy (5). With or without therapist guidance, patients confront themselves with anxiety-inducing situations, thus gaining insight into their physical symptoms, safety strategies, and avoidance behavior (6). However, roughly one-third of individuals with panic disorder do not receive psychological treatment (7). The barriers to treatment include a shortage of trained therapists, high treatment costs, and shame and stigmatization around seeking psychological help (8).

Internet-based cognitive behavioral therapy (iCBT) is a promising option for the treatment of persons with panic disorder. iCBT comprises structured web- or app-based programs and specifically addresses the barriers to obtaining a place for face-to-face psychotherapy (9). iCBT programs have been shown to be effective in reducing anxiety, with moderate to large effect sizes when compared with inactive control conditions and small effect sizes when compared with active control groups with conventional CBT (10). Carlbring et al. (11) reported comparable efficacy in the treatment of panic symptoms (g = 0.05), with iCBT proving less costly (12).

The exposure for persons with panic disorder focuses mainly on interoceptive exposure, although external cues can also trigger panic attacks. The resulting intensification of agoraphobic behavior, often unrecognized and untreated, may be associated with panic disorder (13, 14, 15). Exposure therapy is considered one of the most effective elements of classical CBT (16, 17) and has been replicated for the iCBT setting. Virtual reality (VR) can be integrated into exposure therapy to simulate real scenarios. This permits better control over the stimuli presented and thus enables greater precision during the exercise.

For anxiety-related disorders, exposure therapy in VR (VRET) shows an overall large effect size compared with wait-list conditions (g = 0.90) and a medium to large effect size compared with active control conditions (g = 0.78) (18). While VRET might be useful in enhancing the efficacy of iCBT for persons with panic disorder, to our knowledge no study has yet investigated the efficacy of self-guided VRET. German health insurance funds currently cover the costs of only one app-based program that integrates self-guided VRET for panic disorder: Invirto. Initial data on the smartphone app Invirto (IVT) have been published on the website of the Federal Institute for Drugs and Medical Devices (available in German from https://diga.bfarm.de/de/verzeichnis/00300). However, patients with panic disorder were slightly underrepresented, so more data are needed.

Objective

The aim of the study was to investigate the efficacy of IVT in comparison with a control group with access to care as usual (CAU). Based on meta-analytic data (19), the following assumptions were made:

• Greater improvement in both the primary endpoint and the secondary endpoints in the IVT group than in the CAU group over the 3-month intervention period (t0–t1)
• After delayed receipt of the intervention in the CAU group, a decrease in both the primary and secondary endpoints between t1 and t2
• High satisfaction with IVT (as measured using the Client Satisfaction Questionnaire, CSQ-8).

The primary endpoint was the difference between the baseline and postassessment scores on the Beck Anxiety Inventory (BAI).

The secondary endpoints were changes in the following:

• Panic-specific symptoms (measured on the Panic and Agoraphobia Scale, PAS)
• Psychological flexibility (Acceptance and Action Questionnaire, AAQ-II)
• Symptoms of depression (Beck Depression Inventory, BDI-II)
• Quality of life (global item of the World Health Organization Quality of Life Questionnaire, WHOQOL-BREF)

Methods

Study design

The study was a two-armed randomized controlled trial (RCT) comparing IVT with CAU. The IVT group received access to the intervention immediately after the beginning of the study (t0) and its members were instructed to follow the IVT treatment pathway (Table 1). The CAU group received no instructions and were informed that they could make use of their CAU as needed. After 3 months (t1), cross-over of the treatments was performed and the CAU group also received access to IVT. A pre–post comparison was carried out to analyze within-group effects (the results of the follow-up survey and the satisfaction rates can be found in the eResults, eFigure 1, eTable 1, and eTable 2). The study was approved by the local ethics committee (LPEK-0415) and preregistered with the German clinical trials registry (#DRKS00027585). Further details can be found in the eMethods and in the published study protocol (20).

Table 1

Modules and Content of IT

eFigure 1

Client Satisfaction Questionnaire (CSQ)

eTable 1

Anxiety, panic, depression, psychological flexibility, quality of life at t2, after treatment cross-over

eTable 2

Results of analyses of variance (ANCOVA) for the completed cases (CC) across time for primary and secondary endpoints (means and standard deviations refer to CC analyses)

Participants and procedure

Potential study participants underwent a clinical diagnostic interview for DSM-5 (SCID-5) (DSM, Diagnostic and Statistical Manual of Mental Disorders) (21) with a certified psychologist to confirm the diagnosis of panic disorder. After clarification of inclusion and exclusion criteria (Box), a survey via the online platform Qualtrics were carried out at baseline (t0) to document self-reported sociodemographic and psychopathological data (Tables 2 and 3). The health-related primary and secondary endpoints were assessed again 3 months after baseline (t1) and in the follow-up survey 6 months after baseline (t2) (Figure).

Box

Inclusion criteria, Exclusion criteria

Figure

Flow chart: overview of the study

Intervention

 IVT is an app-based iCBT program with self-guided VRET for the treatment of panic disorder (eight modules, approx. 15 hours; Table 1), to be completed over a period of 12 weeks. The contents of IVT are in line with the national guidelines for the treatment of anxiety disorders (5) and are based on established German treatment manuals (22, 23, 24). IVT comprises audio and video lessons recorded with experienced psychotherapists together with practical exercises in virtual and interoceptive exposure as well as cognitive restructuring. The app can be implemented as often as the user wishes. For use of the app (e.g., at home), each patient receives VR glasses and headphones. To support their self-guided VRET, patients have the option of taking part in two videoconference sessions (each lasting 50 minutes) with a clinical psychologist from the provider, Sympatient.

Measures

All instruments are described in full in the eMethods. The methodology and the endpoints were selected for comparability with the prior study on IVT. The primary endpoint was the difference between the two groups in changes in anxiety symptoms from t0 to t1, as measured by the BAI (25, 26).

The secondary endpoints were changes in the following:

• Anxiety symptoms (PAS)
• Depression (BDI-II)
• Quality of life (WHOQOL-BREF)
• Psychological flexibility (AAQ-II)
• Satisfaction with the program (CSQ-8)

Negative effects were assessed with the aid of the Reliable Change Index (RCI), which determines clinically significant changes (deterioration) in a person’s scores, accounting for test reliability and measurement error (27). In this study, the RCI was used to measure significant symptom deterioration in BAI scores between t0 and t1. On the assumption that negative experiences with IVT would lead to lower adherence, patients who reported using IVT less than once a week were asked about barriers to its use (eMethods).

Data analysis

Intention-to-treat (ITT) analyses with multiple imputation were conducted as primary analyses. Group allocation, sociodemographic variables (Table 2), and psychopathological variables at baseline (Table 3) were entered into the model as predictors for imputation; 100 imputations were run. To test the hypotheses, analyses of covariance (ANCOVA) were calculated using the respective baseline scores as covariate. The dependent variable was the change in BAI values from t0 to t1. Combined p-values and effect sizes are reported using Cohen’s d; values from 0.2 to < 0.5 indicate a small, 0.5 to < 0.8 a moderate, and > 0.8 a large effect size (28).

Table 2

Descriptive characteristics and group comparisons of the participants at baseline (t0)

Table 3

Participants’ clinical characteristics at baseline (t0)

Results

Demographic characteristics

The demographic data are displayed in Table 2 and described in more detail in the eResults.

Efficacy

ITT analyses

For the primary endpoint anxiety (BAI), analyses showed a greater improvement in the IVT group than in the CAU group, with a small effect (p < 0.029; d = –0.46; 95% confidence interval [−0.87; −0.04]; Table 4, eFigure 2). Improvement of secondary endpoints was also greater in the IVT group, with a moderate effect for panic symptoms (PAS; p < 0.003; d = –0.63, [−1.05; −0.22]) and small effects for depressive symptoms (BDI-II; p = 0.040; d = –0.44, [−0.86; −0.02]) and for experiential avoidance and psychological flexibility (AAQ-II; p = 0.045; d = –0.42, [−0.84; −0.01]). Change in quality of life did not differ between the groups (WHOQOL-BREF; p = 0.216; d = 0.24, [−0.15; 0.63]).

Table 4

Primary endpoint anxiety and secondary endpoints panic, depression, psychological flexibility, quality of life—results of covariance analysis (ANCOVA) for the ITT analysis at t0 and t1

eFigure 2

Changes in the primary endpoint, anxiety (BAI), in the two groups

Negative effects: symptom deterioration (RCI)

The ITT analyses showed that one person in the IVT group and two persons in the CAU group experienced clinically meaningful symptom deterioration from t0 to t1, as measured by the RCI.

Discussion

App-based iCBT represents a promising tool for addressing panic symptoms and broadening the application of evidence-based treatment, by virtue of its low-threshold accessibility, flexibility, and independence from time and place. Patients might find smartphone apps such as IVT easier to use, as other digital interventions are available only in web-based form. The study reported here revealed greater improvement for IVT than for CAU across all primary (BAI) and secondary (PAS, BDI-II, AAQ-II) endpoints, except for quality of life (WHOQOL-BREF), over a 3-month period.

For the primary endpoint, the findings show that IVT was superior to CAU in reducing anxiety symptoms (BAI), although the effect size was small (d = −0.46) and thus lower than the moderate to large effect sizes reported in previous studies (29, 30). This could be due to various factors:

• First, unexpected external factors, e.g., the pandemic occurring during the study period, may have amplified patients’ anxiety.
• Second, although IVT is based on an empirically validated treatment, some participants experienced technical problems that may have have reduced its efficacy.
• Third, methodological factors may have played a role as panic symptoms (measured using the PAS) in particular showed improvement with a moderate effect size (d = −0.63), which is in line with the results of previous research (10) and may better reflect the objectives of IVT, as this scale is explicitly aimed at panic symptoms.

Although the BDI-II t0 scores may seem high in the present sample, the data are in line with other research showing a high comorbidity rate of 38.5% between panic disorder and major depressive disorder (31). Depressive symptoms at t0 may have been more severe than usual as the survey took place during the COVID-19 pandemic (32, 33). In line with research showing that patients who receive panic-focused psychotherapy often experience clear remission of their diagnosed depression (34), the use of IVT resulted in a decrease in depressive symptoms with a small effect size (d = −0.44). However, lower adherence was associated with more pronounced depressive symptoms, which could have also influenced drop-out rates in the present sample. Additional optimization may be needed to keep patients with comorbid depression in treatment (34).

Panic disorders can impact quality of life (3, 4), particularly when left untreated (35, 36). In the present study, no group differences in quality of life were found (p = 0.2). Even within the groups, there was only a slight difference between t0 and t1. However, there was a slightly greater absolute difference in the IVT group from t0 to t1, which could be increased through further improvements such as additional modules geared to the needs of individual patients.

The level of experiential avoidance (AAQ-II) showed improvement with a small effect size (d = −0.42). In the context of exposure, this might be critical in regard to willingness to continue with aversive experiences and to take action instead of engaging in avoidance (37, 38).

Limitations

Besides the present study’s strengths (e.g., compliance with preregistration), some general limitations must be acknowledged.

Although study inclusion was based on diagnosis verification via structured clinical interviews by trained clinicians, all results are based on self-reports. The data may thus differ from clinical assessment. Not requiring face-to-face interviews can avoid alienating those who feel intense shame or fear of stigma; such persons tend to benefit greatly from internet-based treatments. Expert assessments based on telephone interviews, allowing for anonymity, should therefore be considered for future research.

In addition, we did not use face-to-face therapy as an active control condition, which should be considered in a follow-up study. Although all participants had the option of taking part in conventional treatment, only 8.1% of them chose to do so.

The present study did not acquire objective user data (e.g., number of conducted exposures in VR). This would therefore be an important consideration for follow-up studies (e.g., number of modules completed or order of completion), as usage outside the study setting might differ from engagement in research (39, 40).

Despite the two groups’ baseline differences in the primary endpoint (BAI score), randomization was considered successful as it was automatically carried out via Qualtrics with a ratio adjustment. We therefore consider that the psychopathological differences in BAI baseline score were coincidental.

Furthermore, as in many online studies and in line with epidemiological data (e1), women were over-represented in the present study, limiting generalizability.

Conclusion

To the best of our knowledge, this is the first study to investigate the efficacy of an unguided app-based iCBT program for panic disorder with self-guided exposure therapy. IVT was found superior to CAU in reducing anxiety, comorbid depressive symptoms, and experiential avoidance, but not in improving quality of life. This study offers additional evidence for the efficacy of app-based iCBT and its incorporation into treatment guidelines for panic disorder as an evidence-based intervention.

Acknowledgments
We would like to thank the patients and the psychologists for their participation.

Funding
The product Invirto was provided, and thus the study partly financed, by the manufacturer Sympatient GmbH. The study was designed in collaboration with Sympatient GmbH. Psychologists employed by Sympatient conducted the diagnostic interviews for study inclusion or exclusion. The supportive interviews during Invirto treatment were also carried out by psychologists employed by Sympatient.

Data sharing
The data are available upon request.

Ethics approval and consent to study participation
The study was approved by the local ethics committee of the University Medical Center Hamburg-Eppendorf (LPEK-0415). Electronic informed consent to participate in the study was obtained from all participants.

Declaration of use of AI in scientific writing
In the preparation of this manuscript, we utilized the generative AI tool ChatGPT to assist with summarizing information. The authors have thoroughly reviewed and revised all AI-generated content to ensure its accuracy, relevance, and adherence to ethical standards. The final responsibility for the content and integrity of this manuscript lies solely with the authors.

Submitted on 17 May 2024, revised version accepted on 18 November 2024

Corresponding author
Josephine Schultz
Klinik für Psychiatrie und Psychotherapie
Universitätsklinikum Hamburg-Eppendorf
Martinistr. 52
20246 Hamburg, Germany

References

1. Olaya B, Moneta MV, Miret M, Ayuso-Mateos JL, Haro JM: Epidemiology of panic attacks, panic disorder and the moderating role of age: results from a population-based study. J Affect Disord 2018; 241: 627–33.

2. De Jonge P, Roest AM, Lim CCW, et al.: Cross-national epidemiology of panic disorder and panic attacks in the world mental health surveys. Depress Anxiety 2016; 33: 1155–77.

3. McKnight PE, Monfort SS, Kashdan TB, Blalock D V, Calton JM: Anxiety symptoms and functional impairment: a systematic review of the correlation between the two measures. Clin Psychol Rev 2016; 45: 115–30.

4. Wilmer MT, Anderson K, Reynolds M: Correlates of quality of life in anxiety disorders: review of recent research. Curr Psychiatry Rep 2021; 23: 1–9.

5. Bandelow B, Werner AM, Kopp I, Rudolf S, Wiltink J, Beutel ME: The German guidelines for the treatment of anxiety disorders: first revision. Eur Arch Psychiatry Clin Neurosci 2022; 272: 571–82.

6. Abramowitz JS, Deacon BJ, Whiteside SPH: Exposure therapy for anxiety: principles and practice. Guilford Publications 2019.

7. Beesdo-Baum K, Höfler M, Jacobi F, Wittchen HU: Epidemiologische Beiträge zur Klinischen Psychologie BT—Klinische Psychologie & Psychotherapie. In: Hoyer J, Knappe S (eds.). Berlin, Heidelberg: Springer 2020.

8. Clement S, Schauman O, Graham T, et al.: What is the impact of mental health-related stigma on help-seeking? A systematic review of quantitative and qualitative studies. Psychol Med 2015; 45: 11–27.

9. Andersson G, Titov N: Advantages and limitations of Internet-based interventions for common mental disorders. World Psychiatry 2014; 13: 4–11.

10. Firth J, Torous J, Nicholas J, Carney R, Rosenbaum S, Sarris J: Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials. J Affect Disord 2017; 218: 15–22.

11. Carlbring P, Andersson G, Cuijpers P, Riper H, Hedman-Lagerlöf E: Internet-based vs. face-to-face cognitive behavior therapy for psychiatric and somatic disorders: an updated systematic review and meta-analysis. Cogn Behav Ther 2018; 47: 1–18.

12. Hedman E, Ljótsson B, Lindefors N: Cognitive behavior therapy via the internet: a systematic review of applications, clinical efficacy and cost-effectiveness. Expert Rev Pharmacoecon Outcomes Res 2012; 12: 745–64.

13. Perugi G, Frare F, Toni C: Diagnosis and treatment of agoraphobia with panic disorder. CNS Drugs 2007; 21: 741–64.

14. Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE: Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry 2005; 62: 593–602.

15. Beesdo K, Pine DS, Lieb R, Wittchen HU: Incidence and risk patterns of anxiety and depressive disorders and categorization of generalized anxiety disorder. Arch Gen Psychiatry 2010; 67: 47–57.

16. Pompoli A, Furukawa TA, Efthimiou O, Imai H, Tajika A, Salanti G: Dismantling cognitive-behaviour therapy for panic disorder: a systematic review and component network meta-analysis. Psychol Med 2018; 48: 1945–53.

17. Norton PJ, Price EC: A meta-analytic review of adult cognitive-behavioral treatment outcome across the anxiety disorders. J Nerv Ment Dis 2007; 195: 521–31.

18. Carl E, Stein AT, Levihn-Coon A, et al.: Virtual reality exposure therapy for anxiety and related disorders: a meta-analysis of randomized controlled trials. J Anxiety Disord 2019; 61: 27–36.

19. Polak M, Tanzer NK, Bauernhofer K, Andersson G: Disorder-specific internet-based cognitive-behavioral therapy in treating panic disorder, comorbid symptoms and improving quality of life: a meta-analytic evaluation of randomized controlled trials. Internet Interv 2021; 24: 100364.

20. Schultz J, Baumeister A, Schmotz S, Moritz S, Jelinek L: Efficacy of an internet-based intervention with self-applied exposure therapy in virtual reality for people with panic disorder: study protocol for a randomized controlled trial. Trials 2023; 24: 521.

21. First MB, Williams JBW, Karg RS, Spitzer RL: SCID-5-CV: structured clinical interview for DSM-5 disorders: clinician version. Arlington, VA: American Psychiatric Association 2016.

22. Helbig-Lang S, Hagestedt D, Lang T, Petermann F: Therapeutische Hausaufgaben in der klinischen Praxis: Einsatz, Erledigung und Beziehungen zum Therapieverlauf. Zeitschrift für Psychiatr Psychol und Psychother 2012; 60: 111–9. DOI: 10.1024/1661–4747/a000106.

23. Hagena S, Gebauer M: Angststörungen. Weinheim, Basel: Beltz-Verlag 2014.

24. Neudeck P, Lang T: Reizkonfrontationsmethoden. In: Klinische Psychologie & Psychotherapie. Springer 2020.

25. Beck AT, Epstein N, Brown G, Steer RA: An inventory for measuring clinical anxiety: psychometric properties. Journal of consulting and clinical psychology 1988; 56: 893.

26. Margraf J, Ehlers A: Das Beck-Angstinventar (BAI). Springer 2007.

27. Jacobson NS, Truax P: Clinical significance: a statistical approach to defining meaningful change in psychotherapy research. J Consult Clin Psychol 1991; 59: 12–9.

28. Cohen J: Statistical power analysis for the behavioral sciences. Routledge 2013.

29. Domhardt M, Letsch J, Kybelka J, Koenigbauer J, Doebler P, Baumeister H: Are internet- and mobile-based interventions effective in adults with diagnosed panic disorder and/or agoraphobia? A systematic review and meta-analysis. J Affect Disord 2020; 276: 169–82.

30. Haug T, Nordgreen T, Öst LG, Havik OE: Self-help treatment of anxiety disorders: a meta-analysis and meta-regression of effects and potential moderators. Clin Psychol Rev 2012; 32: 425–45.

31. Kessler RC, Chiu WT, Jin R, Ruscio AM, Shear K, Walters EE: The epidemiology of panic attacks, panic disorder, and agoraphobia in the National Comorbidity Survey Replication. Arch Gen Psychiatry 2006; 63: 415–24.

32. Bäuerle A, Teufel M, Musche V, et al.: Increased generalized anxiety, depression and distress during the COVID-19 pandemic: a cross-sectional study in Germany. J Public Health (Bangkok). 2020; 42: 672–8.

33. Chang JJ, Ji Y, Li YH, Pan HF, Su PY: Prevalence of anxiety symptom and depressive symptom among college students during COVID-19 pandemic: a meta-analysis. J Affect Disord 2021; 292: 242–54.

34. Keefe JR, Chambless DL, Barber JP, Milrod BL: Treatment of anxiety and mood comorbidities in cognitive-behavioral and psychodynamic therapies for panic disorder. J Psychiatr Res 2019; 114: 34–40.

35. Mendlowicz M V, Stein MB: Quality of life in individuals with anxiety disorders. Am J Psychiatry 2000; 157: 669–82.

36. Olatunji BO, Cisler JM, Tolin DF: Quality of life in the anxiety disorders: a meta-analytic review. Clin Psychol Rev 2007; 27: 572–81.

37. Hayes SC, Strosahl K, Wilson KG, et al.: Measuring experiential avoidance: a preliminary test of a working model. Psychol Rec 2004; 54: 553–78.

38. Hoyer J, Gloster AT: Psychologische Flexibilität messen = measuring psychological flexibility: Der Fragebogen zu Akzeptanz und Handeln–II (FAH-II): the acceptance and action questionnaire–II (AAQ-II). Verhaltenstherapie 2013; 23: 42–4.

39. Fleming T, Bavin L, Lucassen M, Stasiak K, Hopkins S, Merry S: Beyond the trial: systematic review of real-world uptake and engagement with digital self-help interventions for depression, low mood, or anxiety. J Med Internet Res 2018; 20: e199.

40. Guiney H, Mahoney A, Elders A, David C, Poulton R: Internet-based cognitive behavioural therapy in the real world: naturalistic use and effectiveness of an evidence-based platform in New Zealand. Aust New Zeal J Psychiatry 2024; 58: 238–49.

e1. Bekker MH, van Mens-Verhulst J: Anxiety disorders: sex differences in prevalence, degree, and background, but gender-neutral treatment. Gend Med 2007; 4: 178–93.

e2. Faul F, Erdfelder E, Lang AG, Buchner A: G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 2007; 39: 175–91.

e3. Geissner E, Huetteroth A: Beck Anxiety Inventory deutsch – Ein reliables, valides und praxisgeeignetes Instrument zur Messung klinischer Angst. Psychother Psychosom Med Psychol 2018; 68: 118–25.

e4. Bandelow B: Panik-und Agoraphobie-Skala (PAS). Göttingen: Hogrefe, Verlag für Psychologie 1997.

e5. Beck AT, Steer RA, Brown G: Manual for the Beck Depression Inventory-II. San Antonio, TX: Psychological Corporation 1996.

e6. García-Batista ZE, Guerra-Peña K, Cano-Vindel A, Herrera-Martínez SX, Medrano LA: Validity and reliability of the Beck Depression Inventory (BDI-II) in general and hospital population of Dominican Republic. PLoS One 2018; 13: e0199750.

e7. Development of the World Health Organization WHOQOL-BREF quality of life assessment. The WHOQOL Group. Psychol Med 1998; 28: 551–8.

e8. Skevington SM, Lotfy M, O’Connell KA: The World Health Organization’s WHOQOL-BREF quality of life assessment: psychometric properties and results of the international field trial. A report from the WHOQOL Group. Qual Life Res 2004; 13: 299–310.

e9. Schmidt J, Wittmann WW: Fragebogen zur Messung der Patientenzufriedenheit. In: Diagnostische Verfahren in der Psychotherapie. Göttingen: Hogrefe 2002; 392–6.

e10. Kinnear PR, Gray CD: IBM SPSS Statistics 18 made simple. Psychology Press 2011.

e11. Karyotaki E, Efthimiou O, Miguel C, et al.: Internet-based cognitive behavioral therapy for depression: a systematic review and individual patient data network meta-analysis. JAMA psychiatry 2021; 78: 361–71.

e12. van Ballegooijen W, Cuijpers P, van Straten A, et al.: Adherence to internet-based and face-to-face cognitive behavioural therapy for depression: a meta-analysis. PLoS One 2014; 9: e100674.

e13. Lüdtke T, Pult LK, Schröder J, Moritz S, Bücker L: A randomized controlled trial on a smartphone self-help application (Be Good to Yourself) to reduce depressive symptoms. Psychiatry Res 2018; 269: 753–62.

e14. Titov N, Dear BF, Johnston L, et al.: Improving adherence and clinical outcomes in self-guided internet treatment for anxiety and depression: randomised controlled trial. PLoS One 2013; 8: e62873.

e15. Deterding S, Dixon D, Khaled R, Nacke L: From game design elements to gamefulness: defining “gamification“. In: Proceedings of the 15th international academic MindTrek conference: envisioning future media environments. 2011; 9–15.