The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.
Predictors and moderators of response to internet-delivered Interpersonal Psychotherapy and Cognitive Behavior Therapy for depression
Open accessAbstract
Background By identifying which predictors and moderators lead to beneficial outcomes, accurate selection of the best initial treatment will have significant benefits for depressed individuals.Method An automated, fully self-guided randomized controlled internet-delivered noninferiority trial was conducted comparing two new interventions (Interpersonal Psychotherapy [IPT; n=620] and Cognitive Behavioral Therapy [CBT; n=610]) to an active control intervention (MoodGYM; n=613) over a period of 4 weeks to spontaneous visitors of an internet-delivered therapy website (e-couch). A range of putative predictors and moderators (socio-demographic characteristics [age, gender, marital status, education level], clinical characteristics [depression/anxiety symptoms, disability, quality of life, medication use], skills [mastery and dysfunctional attitudes] and treatment preference) were assessed using internet-delivered self-report measures at baseline and immediately following treatment and at six months follow-up. Analyses were conducted using Mixed Model Repeated Measures (MMRM).Results Female gender, lower mastery and lower dysfunctional attitudes predicted better outcome at post-test and/or follow-up regardless of intervention. No overall differential effects for condition on depression as a function of outcome were found. However, based on time-specific estimates, a significant interaction effect of age was found. For younger people, internet-delivered IPT may be the preferred treatment choice, whereas older participants derive more benefits from internet-delivered CBT programs.Limitations Although the sample of participants was large, power to detect moderator effects was still lacking.Conclusions Different e-mental health programs may be more beneficial for specific age groups. The findings raise important possibilities for increasing depression treatment effectiveness and improving clinical practice guidelines for depression treatment of different age groups.
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“Although EMIs represent an important advance compared to episodic face-to-face interventions and even self-applied psychotherapy because of their traditional rigidity, it is known that not all people respond in the same way to psychological treatments [64], including the ones supported by technology [65].”
From Using Artificial Intelligence to Enhance Ongoing Psychological Interventions for Emotional Problems in Real- or Close to Real-Time: A Systematic Review (2022) · cites this paper as [65]
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“Despite the relatively minimal guidance provided among the prevention studies, program adherence was moderate across the studies and not dissimilar to that of clinical studies [62, 63].”
From eHealth interventions for the prevention of depression and anxiety in the general population: a systematic review and meta-analysis (2017) · cites this paper as [62]
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Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,603
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
The CES-D Scale: A Self-Report Depression Scale for Research in the General Population
Radloff, L. S. (1977) · Applied Psychological Measurement · doi:10.1177/014662167700100306 · Cited by 53,267
A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7
Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006) · Archives of Internal Medicine · doi:10.1001/archinte.166.10.1092 · Cited by 31,765
Cognitive Therapy for Depression
(2012) · PsycEXTRA Dataset · doi:10.1037/e675542012-001 · Cited by 9,678
Pearlin, L. I., & Schooler, C. (1978) · Journal of Health and Social Behavior · doi:10.2307/2136319 · Cited by 7,791 · cited 2×
“Mastery: The baseline 7-item Mastery Scale (Pearlin and Schooler, 1978) was used to assess perceived control.”
MethodCognitive Therapy of Depression
HOLLON, S. D., & BECK, A. T. (1979) · Cognitive-Behavioral Interventions · doi:10.1016/b978-0-12-404480-7.50012-5 · Cited by 4,685
Mediators and Moderators of Treatment Effects in Randomized Clinical Trials
Kraemer, H. C., Wilson, G. T., Fairburn, C. G., & Agras, W. S. (2002) · Archives of General Psychiatry · doi:10.1001/archpsyc.59.10.877 · Cited by 2,562 · cited 3×
“Predictors (pre-treatment variables which predict depressive outcome in all treatment groups; Kraemer et al., 2002) and moderators (pre-treatment variables identifying which individuals are more likely to benefit from a particular treatment; Kazdin, 2007) are important to identify for several reasons.”
BackgroundInfluentialEysenbach, G. (2005) · Journal of Medical Internet Research · doi:10.2196/jmir.7.1.e11 · Cited by 2,524
Mediators and Mechanisms of Change in Psychotherapy Research
Kazdin, A. E. (2007) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.3.022806.091432 · Cited by 2,504 · cited 2×
“…(pre-treatment variables which predict depressive outcome in all treatment groups; Kraemer et al., 2002) and moderators (pre-treatment variables identifying which individuals are more likely to benefit from a particular treatment; Kazdin, 2007) are important to identify for several reasons.”
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Internet-based cognitive behavioural therapy
Høifødt, R. S. (2015)
Wie wirksam sind internetbasierte Programme?
Meyer, B., Jacob, G. A., & Weiss, M. (2014) · NeuroTransmitter · doi:10.1007/s15016-014-0587-7
Beulke, J. T. (2016) · ScholarWorks (Walden University)
Rachyla, I. (2019) · Tesis Doctorals en Xarxa (Consorci de Serveis Universitaris de Catalunya) · doi:10.6035/14109.2019.234380
Dubrow‐Marshall, L., & Smail, D. R. (2021) · Advances in psychology, mental health, and behavioral studies (APMHBS) book series · doi:10.4018/978-1-7998-7991-6.ch002
Secondary analysis: Bounce Back & Thrive! a Canadian resiliency building program
Wozniak, R. R. (2021) · ERA: Education and Research Archive (University of Alberta) · doi:10.7939/r3-1jpf-rt36
Imamura, K., Furukawa, T. A., Matsuyama, Y., Shimazu, A., Kuribayashi, K., Kasai, K., & Kawakami, N. (2018) · doi:10.2196/preprints.10231
Latent Trajectories of Depressive Symptoms During a Transdiagnostic Partial Hospitalization Program
Moscardini, E. H., Hudson, C. C., Kumar, D., Lewin, R. K., McDermott, T. J., Giangrande, E. J., Shea, L.-M., Tretyak, V., Beard, C., & Björgvinsson, Þ. (2024) · Behavior Therapy · doi:10.1016/j.beth.2024.05.008
Interpersonal Psychotherapy in the Netherlands
Peeters, F. P. M. L., Jonker, K., & Blom, M. B. J. (2024) · doi:10.1093/oso/9780197652084.003.0032
Peer-led online depression support groups: Potentially healthy and unhealthy associated behaviors
Kamicar, M., Abitante, G., Lovette, A. J., Wilson, R. A., Gao, J., & Cole, D. A. (2024) · Journal of Social and Clinical Psychology · doi:10.1521/jscp.2024.43.4.344
Rutherford, E. R., Vandelanotte, C., Chapman, J., & To, Q. G. (2022) · Figshare · doi:10.6084/m9.figshare.20652250
Chiauzzi, E. J., Williams, A. A. A., Mariano, T. Y., Pajarito, S., Robinson, A. H., Kirvin-Quamme, A., & Forman‐Hoffman, V. L. (2024) · Figshare · doi:10.6084/m9.figshare.26674502
Sunzeri, E., & Sunzeri, F. (2026) · Springer eBooks · doi:10.1007/978-3-032-14465-2_17
Sex and gender in digital mental health: why the data are not neutral
Cho, C. (2026) · Women s Health Nursing · doi:10.4069/whn.2026.08.03
Metadata
- Authors
- Donker, T., Batterham, P. J., Warmerdam, L., Bennett, K., Bennett, A., Cuijpers, P., Griffiths, K. M., & Christensen, H.
- Affiliations
- Black Dog Institute (AU)
- Australian National University (AU)
- Amsterdam Public Health (NL)
- Corresponding author
- Donker, T.
- ORCID
- Venue
- Journal of Affective Disorders
- Publisher
- Elsevier BV
- Published
- 2013-10
- Volume
- 151
- Issue
- 1
- Pages
- 343-351
- ISSN
- 0165-0327 (ISSN-L)
- OpenAlex
- W2091355781
- Cited by
- 115
- References
- 75
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 10 · 2023: 9 · 2022: 11 · 2021: 8 · 2020: 6 · 2019: 15 · 2018: 9 · 2017: 15 · 2016: 11 · 2015: 7 · 2014: 6
- FWCI
- 12.23
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Journal of Affective Disorders (publishedVersion)
- PubMed (publishedVersion)
- VU Research Portal (publishedVersion)
- ANU Open Research (Australian National University) (submittedVersion, other-oa)
- Multilingual Matters (Channel View Publications) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Health Sciences › Medicine › Psychiatry and Mental health › Mental Health Treatment and Access
- Keywords
- online therapy, interpersonal psychotherapy, cognitive behavioral therapy, depression, predictors of treatment response, treatment moderators, age differences, gender differences, mastery, dysfunctional attitudes, e-mental health, MoodGYM, treatment selection
- MeSH terms
- Adolescent, Adult, Age Factors, Attitude to Health, Depression, Female, Humans, Male, Middle Aged, Psychiatric Status Rating Scales, Psychotherapy, Sex Factors, Therapy, Computer-Assisted, Cognitive Behavioral Therapy, Treatment Outcome, Young Adult
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