User Acceptance of Computerized Cognitive Behavioral Therapy for Depression: Systematic Review
Open accessAbstract
BACKGROUND: Computerized cognitive behavioral therapy (cCBT) has been proven to be effective in depression care. Moreover, cCBT packages are becoming increasingly popular. A central aspect concerning the take-up and success of any treatment is its user acceptance. OBJECTIVE: The aim of this study was to update and expand on earlier work on user acceptance of cCBT for depression. METHODS: This paper systematically reviewed quantitative and qualitative studies regarding the user acceptance of cCBT for depression. The initial search was conducted in January 2016 and involved the following databases: Web of Science, PubMed, the Cochrane Library, and PsycINFO. Studies were retained if they described the explicit examination of the user acceptance, experiences, or satisfaction related to a cCBT intervention, if they reported depression as a primary outcome, and if they were published in German or English from July 2007 onward. RESULTS: A total of 1736 studies were identified, of which 29 studies were eligible for review. User acceptance was operationalized and analyzed very heterogeneously. Eight studies reported a very high level of acceptance, 17 indicated a high level of acceptance, and one study showed a moderate level of acceptance. Two qualitative studies considered the positive and negative aspects concerning the user acceptance of cCBT. However, a substantial proportion of reviewed studies revealed several methodical shortcomings. CONCLUSIONS: In general, people experience cCBT for depression as predominantly positive, which supports the potential role of these innovative treatments. However, methodological challenges do exist in terms of defining user acceptance, clear operationalization of concepts, and measurement.
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Web-based mental health interventions are increasingly being used in the work environment.
“Web-based mental health interventions are increasingly being used in the work environment as they have the advantage of being cost-effective, efficient, anonymous, location-independent, flexible, and empowering. They are regularly used for both prevention and intervention [5-10].”
From Acceptability of Web-Based Mental Health Interventions in the Workplace: Systematic Review (2022) · cites this paper as [10]
The Introduction describes computerized treatment for depression as an approach to improving access, and the References list a worker-directed web-based intervention for employees with depressive symptoms (ref. 38). These passages support the existence of an intervention aimed at workers, but they do not establish that use in work environments is increasing. (LLM, conf=0.76)
Experimental — accuracy not yet measuredThe level of acceptability was categorized into quartiles: low, moderate, high, and very high.
“Similar to corresponding systematic reviews on the acceptability of web-based interventions [10], the level of acceptability was categorized into the following quartiles: low (− −), moderate (−), high (+), and very high (+ +).”
From Acceptability of Web-Based Mental Health Interventions in the Workplace: Systematic Review (2022) · cites this paper as [10]
Technology-based mental health services are considered acceptable by healthcare professionals, lay people, and users.
“These services are also considered as acceptable by healthcare professionals,19 by lay people19 and by users (eg, affected individuals using TBIs).20 21”
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Flagged first, then by citations
Cited by
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Functionality of Top-Rated Mobile Apps for Depression: Systematic Search and Evaluation
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Early detection of depression using a conversational AI bot: A non-clinical trial
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“In recent years, the UTAUT and TAM have been implemented in various medical settings [35-41].”
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“For example, cognitive-behavioral therapy (CBT), a wellestablished treatment option, can be enhanced using computer-delivered CBT (cCBT) [7, 29, 30].”
BackgroundDeterminant Factors of Public Acceptance of Stress Management Apps: Survey Study
Apolinário-Hagen, J., Hennemann, S., Fritsche, L., Drüge, M., & Breil, B. (2019) · JMIR Mental Health · doi:10.2196/15373 · Cited by 63 · see citing works
“…of stress coping apps and health promotion, and the necessary slight adaptations of some scales to the mHealth context, impede the comparability with most studies in this field that targeted e-mental health treatments [33,82,83] or specific mental disorders, such as depression [43,123,124].”
Individualized Web-Based Exercise for the Treatment of Depression: Randomized Controlled Trial
Haller, N., Lorenz, S., Pfirrmann, D., Koch, C., Lieb, K., Dettweiler, U., Simon, P. D., & Jung, P. (2018) · JMIR Mental Health · doi:10.2196/10698 · Cited by 58 · see citing works
“Computerized CBT (cCBT) is highly accepted [57] and has garnered increasing attention due to its capability to deliver a potentially effective and efficient therapeutic method to large numbers of people with depression.”
BackgroundA Multi-Industry Analysis of the Future Use of AI Chatbots
Kelly, S., Kaye, S.-A., & Oviedo-Trespalacios, Ó. (2022) · Human Behavior and Emerging Technologies · doi:10.1155/2022/2552099 · Cited by 66 · see citing works
“Further, while previous work has focused on user acceptance of chatbots [24, 32, 38], more research is required to apply theoretical models to measure user acceptance of AI chatbots across various industries.”
BackgroundJardine, J., Nadal, C., Robinson, S., Enrique, Á., Hanratty, M., & Doherty, G. J. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3635472 · Cited by 55 · see citing works
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“To increase access to therapy, a number of internet-based CBT (iCBT) programs [25-27] offer an acceptable and effective alternative [28-30].”
BackgroundJoerin, A., Rauws, M., & Ackerman, M. L. (2019) · Cureus · doi:10.7759/cureus.3972 · Cited by 47 · see citing works
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“Individuals who do not believe that their treatment will be effective often perceive it as inconvenient and quit trying another therapy technique or spending their time elsewhere [35].”
BackgroundWeitzel, E. C., Schwenke, M., Schomerus, G., Schönknecht, P., Bleckwenn, M., Mehnert, A., Riedel-Heller, S. G., & Löbner, M. (2023) · Archives of Public Health · doi:10.1186/s13690-023-01150-y · Cited by 41 · see citing works
Self-citationAcceptability of Web-Based Mental Health Interventions in the Workplace: Systematic Review
Scheutzow, J., Attoe, C., & Harwood, J. (2022) · JMIR Mental Health · doi:10.2196/34655 · Cited by 30 · see citing works
“They are regularly used for both prevention and intervention [5-10].”
BackgroundAcceptability of Computerized Cognitive Behavioral Therapy for Adults: Umbrella Review
Treanor, C., Kouvonen, A. M., Lallukka, T. M., & Donnelly, M. (2021) · JMIR Mental Health · doi:10.2196/23091 · Cited by 35 · see citing works
“A very wide range of uptake proportions (1%-97%) was reported across reviews [26-29,34].”
BackgroundInfluentialKarni, L., Dalal, K., Memedi, M., Kalra, D., & Klein, G. O. (2020) · Journal of Medical Internet Research · doi:10.2196/17459 · Cited by 31 · see citing works
“ICT-based strategies have also grown in popularity and proved to be efficient in the self-administered management of various conditions such as online cognitive behavioral therapies for depression and anxiety [4,6,7].”
E-Mental-Health und digitale Gesundheitsanwendungen in Deutschland
Weitzel, E. C., Quittschalle, J., Welzel, F. D., Löbner, M., Hauth, I., & Riedel-Heller, S. G. (2021) · Der Nervenarzt · doi:10.1007/s00115-021-01196-9 · Cited by 30 · see citing works
Self-citationKlein, N. S., Bockting, C., Wijnen, B. F. M., Kok, G. D., van Valen, E., Riper, H. M., Cuijpers, P. J., Dekker, J., van der Heiden, C., Burger, H., et al. (2018) · Journal of Medical Internet Research · doi:10.2196/10437 · Cited by 29 · see citing works
“In addition, besides examining the (cost) effectiveness of specific internet-based interventions, future studies should focus more on the implementation in clinical practice, taking into account specific barriers (eg, preferences of individuals and professionals) [54,55].”
Kim, J. C., Saguna, S., & Åhlund, C. (2023) · JMIR Human Factors · doi:10.2196/42145 · Cited by 32 · see citing works
“Regarding user acceptance, the definition varies based on the purpose of use [16].”
A systematic review and meta analysis on digital mental health interventions in inpatient settings
Diel, A., Schröter, I. C., Frewer, A.-L., Jansen, C., Robitzsch, A., Gradl-Dietsch, G., Teufel, M., & Bäuerle, A. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01252-z · Cited by 31 · see citing works
Woodford, J., Farrand, P. A., Hagström, J., Hedenmalm, L., & von Essén, L. (2021) · JMIR Formative Research · doi:10.2196/22709 · Cited by 28 · see citing works
“In addition to placing fewer demands on parents of children treated for cancer, guided internet-administered LICBT may represent a solution to address individual-and provider-level barriers to access [42-44].”
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“Of the psychological treatments available, cognitive behavioural therapy (CBT) is the most commonly used, both in person and electronically via computer [11, 12].”
BackgroundJardine, J., Earley, C., Richards, D., Timulák, L., Palacios, J. E., Duffy, D. J., Tierney, K., & Doherty, G. J. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376254 · Cited by 22 · see citing works
“These include personal motivation (which is often linked to depression factors such as apathy, low self-esteem and difficulty concentrating), lack of computer/internet skills (or conversely technology fatigue from using a computer at work), a desire for human contact, negative attitudes towards technology/online self-…”
BackgroundCiharova, M., Cuijpers, P., Amanvermez, Y., Riper, H., Klein, A. M., Bolinski, F., de Wit, L. D., der Heijde, C. M. V., Bruffaerts, R., Struijs, S., et al. (2023) · Internet Interventions · doi:10.1016/j.invent.2023.100646 · Cited by 17 · see citing works
“Dropout is higher in participants perceiving an intervention as unhelpful, uncredible, inconvenient, or not meeting their preferences and needs (Beatty and Binnion, 2016; Kaltenthaler et al., 2008; Rost et al., 2017; Vallury et al., 2015).”
BackgroundSadowski, I., & Khoury, B. (2022) · Frontiers in Virtual Reality · doi:10.3389/frvir.2022.892905 · Cited by 20 · see citing works
“Common barriers to older adult mental health service provision cited in the literature include stigma, lack of information, perceived costs, mobility restraints, lack of specialized health professionals, limited mental health literacy, and beliefs that symptoms of mental health illnesses are a normal part of the aging…”
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“Such non-pharmacological interventions can be effectively adapted for digital delivery and have been demonstrated to be acceptable 25 and effective in other mood disorders such as Major Depressive Disorder 26 .”
BackgroundPosselt, J., Baumann, E., & Dierks, M. (2024) · Frontiers in Digital Health · doi:10.3389/fdgth.2024.1275569 · Cited by 17 · see citing works
Kheirkhah, F., Faramarzi, M., Shafierizi, S., Chehrazi, M., & Basirat, Z. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e15760 · Cited by 16 · see citing works
“The advantages of ICBT include access to service, avoidance of stigma associated with seeing a therapist [23], more privacy and convenience [24], greater treatment fidelity, cost effectiveness [25], no geographic restrictions [26], and anonymity [27].”
BackgroundWoodford, J., Wikman, A., Einhorn, K., Cernvall, M., Grönqvist, H., Romppala, A., & von Essén, L. (2018) · JMIR Mental Health · doi:10.2196/10085 · Cited by 16 · see citing works
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“The patients’ access to psychotherapies has increased in the last two decades owing to the advancement of technology and the emergence of Internet-Based cognitive behavioral therapies (ICBTs) (Leterme et al., 2020; Rollman et al., 2018; Rost et al., 2017).”
BackgroundPatient experience of supported computerized CBT in an inner-city IAPT service: a qualitative study
Perera-Delcourt, R. P., & Sharkey, G. (2019) · The Cognitive Behaviour Therapist · doi:10.1017/s1754470x18000284 · Cited by 14 · see citing works
“Further research on the patient experience of cCBT has therefore been called for (Rost et al. , 2017).”
BackgroundMethodInfluentialHäfner, J., Schönfeld, S., Tokgöz, P., Choroschun, K., Schlubach, A., & Dockweiler, C. (2022) · Healthcare · doi:10.3390/healthcare10102019 · Cited by 13 · see citing works
“It is possible that people who have reservations regarding DHI do not participate in the first place [32].”
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Use of a self-guided computerized cognitive behavioral tool during COVID-19: evaluation study
Detweiler Guarino, I., Cowan, D. R., Fellows, A. M., & Buckey, J. C. (2021) · JMIR Formative Research · doi:10.2196/26989 · Cited by 10 · see citing works
Freund, J., Buntrock, C., Braun, L., Thielecke, J., Baumeister, H., Berking, M., Ebert, D. D., & Titzler, I. (2022) · Internet Interventions · doi:10.1016/j.invent.2022.100566 · Cited by 11 · see citing works
Dropout and completion in iCBT for university students: Insights from a thematic analysis
Koelen, J. A., de Koning, L., Nottage, M., Klein, A. M., der Heijde, C. M. V., Vonk, P., & Wiers, R. W. H. J. (2025) · Internet Interventions · doi:10.1016/j.invent.2025.100831 · Cited by 11 · see citing works
Lara, M. A., Patiño, P., Tiburcio, M., & Navarrete, L. (2021) · JMIR Formative Research · doi:10.2196/29566 · Cited by 10 · see citing works
“According to Rost et al [27], the severity of symptoms and possible comorbidities affect users’ perceptions of acceptability and satisfaction.”
BackgroundResultLeung, L. B., Dyer, K. E., Yano, E. M., Young, A. S., Rubenstein, L. V., & Hamilton, A. B. (2020) · Translational Behavioral Medicine · doi:10.1093/tbm/ibz122 · Cited by 10 · see citing works
“Although patients have generally found cCBT to be acceptable [17,18], we know little about U.S. mental health clinicians’ perceptions of cCBT-enhanced collaborative care.”
BackgroundLöbner, M., Stein, J., Rechenberg, T., Förster, F., Dorow, M., Keller, J., Weidauer, E., & Riedel-Heller, S. G. (2019) · Psychiatrische Praxis · doi:10.1055/a-0956-3775 · Cited by 9 · see citing works
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Schladitz, K., Förster, F., Löbner, M., Welzel, F. D., Stein, J., Luppa, M., & Riedel-Heller, S. G. (2020) · Zeitschrift für Evidenz Fortbildung und Qualität im Gesundheitswesen · doi:10.1016/j.zefq.2020.01.007 · Cited by 8 · see citing works
Self-citationStudents’ perceptions of an online mental health intervention: a qualitative interview study
Irish, M., Zeiler, M. D., Kuso, S., Musiat, P., Potterton, R., Wagner, G., Karwautz, A. F. K., Waldherr, K., & Schmidt, U. H. (2020) · Neuropsychiatrie · doi:10.1007/s40211-020-00383-5 · Cited by 8 · see citing works
Health Care Social Robots in the Age of Generative AI: Protocol for a Scoping Review
Lempe, P. N., Guinemer, C., Fürstenau, D., Dressler, C., Balzer, F., & Schaaf, T. (2024) · JMIR Research Protocols · doi:10.2196/63017 · Cited by 7 · see citing works
“Simply introducing these innovative robots is not sufficient if individuals are hesitant or unwilling to interact with them [13].”
A Framework for Open Source Intelligence Penetration Testing of Virtual Health Care Systems
DeCusatis, C. M., Peko, P., Irving, J., Teache, M., Laibach, C., & Hodge, J. (2022) · IEEE Annual Computing and Communication Workshop and Conference (CCWC) · doi:10.1109/ccwc54503.2022.9720785 · Cited by 7 · see citing works
“Specifically, one of the most important use cases for telemedicine involves providing mental health care and support for patients who cannot attend conventional in-person therapy sessions [4-6].”
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Usability of a mHealth Solution using Speech Recognition for Point-of-care Diagnostic Management
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Du, E., Quayle, E., & Macleod, H. (2021) · The Cognitive Behaviour Therapist · doi:10.1017/s1754470x21000210 · Cited by 5 · see citing works
“There is need for greater understanding of patient experience of CCBT (Rost et al., 2017), of related CCBT services, and of similarities and differences in the support offered (Gellatly et al.”
Egan, S. J., Shafran, R., Wade, T. D., Ure, S., Gill, C., Wilker, L., Anderson, R., Mazzucchelli, T. G., & McEvoy, P. M. (2022) · Clinical Psychologist · doi:10.1080/13284207.2022.2031946 · Cited by 5 · see citing works
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“training and support) support the use of the district app? The acceptance of an innovation can be considered as a multilevel process [11].”
BackgroundStephenson, C., Jagayat, J., Kumar, A., Khamooshi, P., Eadie, J., Pannu, A., Meartsi, D., Danaee, E., Gutiérrez, G., Khan, F., et al. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1220607 · Cited by 4 · see citing works
“Drop-out rates for in-person psychotherapy vary from 20–47% depending on the study design (15–17), whereas a systematic review of 29 studies revealed the dropout rate for e-CBT for depression can range from 0–63%, with an average dropout rate of 32% (18).”
BackgroundResearch Trends and Hotspots on Asthma and Depression: A Bibliometric Analysis
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Barriers to Implementation of a Technology-Based Mental Health Intervention in a Rural Setting
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“Researchers have evaluated the acceptability [9,10], feasibility [11], and efficacy of DMH interventions delivered using differing modalities [11,12] and with a broad range of participant groups [12].”
Yisma, E., Walsh, S., Steen, M., Gray, R. J., Dennis, S., Gillam, M., Parange, N., & Jones, M. (2024) · Nursing Reports · doi:10.3390/nursrep14010007 · Cited by 3 · see citing works
“It has been reported previously that generally, attrition rates for computerized CBT tend to be high [27,28], so perhaps the high attrition rate in the included studies is not too surprising.”
BackgroundEffectiveness of mental therapy for poor medication adherence in depression: A review
Xu, S., Liu, B., & Zhang, Y. (2020) · Tropical Journal of Pharmaceutical Research · doi:10.4314/tjpr.v19i8.30 · Cited by 3 · see citing works
“Besides, the use of internet and computer-assisted programs to deliver CBT may be effective intermediations for MDD, as it would make CBT much more manageable to patients [17].”
MethodYank, V. A., Gale, R. C., Nevedal, A., Okwara, L., Koenig, C. J., TRIVEDI, R. B., Dupke, N. J., Kabat, M., & Asch, S. M. (2021) · Journal of Medical Internet Research · doi:10.2196/16495 · Cited by 3 · see citing works
“Evidence-based online psychoeducational programs may offer an efficient, accessible, and scalable option for improving participants’health and well-being [1-9] but only if they succeed in reaching the participants for whom they are designed [10,11].”
BackgroundWeb-Based Psychotherapy and Exercise Interventions for Depressive and Anxiety Disorders
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Mental Health and Psychological Assessment During the COVID-19 Pandemic: Systematic Review
Scortegagna, S. A., de Lima, E. D. S., Marchi, A. C. B. D., & Portella, M. R. (2022) · Psicologia Teoria e Pesquisa · doi:10.1590/0102.3772e38425.en · Cited by 3 · see citing works
Cognitive therapy for brain diseases using deep learning models
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The Use of Mobile Phones for Frontline Health-Care Workers to Manage Depression
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Saúde Mental e Avaliação Psicológica Durante a Pandemia de Covid-19: Revisão Sistemática
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The Use of Mobile Phones for Frontline Health-Care Workers to Manage Depression
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Depression Tendency Estimation Method Using AI Chatbot
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Recent Progress in Internet-Based Cognitive Behavioral Therapy for Depression
孙, 玉. (2025) · Advances in Psychology · doi:10.12677/ap.2025.1512662
- Authors
- Rost, T., Stein, J., Löbner, M., Kersting, A., Luck-Sikorski, C., & Riedel-Heller, S. G.
- Affiliations
- Leipzig University (DE)
- Corresponding author
- Riedel-Heller, Steffi G
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2017-09-13
- Volume
- 19
- Issue
- 9
- Pages
- e309
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC5617907
- OpenAlex
- W2754765682
- Cited by
- 91
- References
- 54
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 16 · 2023: 12 · 2022: 11 · 2021: 16 · 2020: 11 · 2019: 9 · 2018: 10
- FWCI
- 0.95
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Deutsche Forschungsgemeinschaft
- Bundesministerium für Bildung und Forschung (01GY1613)
- 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 › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Keywords
- computerized cognitive behavioral therapy, depression, user acceptance, user satisfaction, digital mental health interventions, methodological issues
- MeSH terms
- Depression, Humans, Therapy, Computer-Assisted, Cognitive Behavioral Therapy, Treatment Outcome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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