Digital cognitive behavior therapy intervention for depression and anxiety: retrospective study
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Abstract
BACKGROUND: Digital mental health interventions offer a scalable solution that reduces barriers to seeking care for clinical depression and anxiety. OBJECTIVE: We aimed to examine the effectiveness of a 12-week therapist supported, app-based cognitive behavioral therapy program in improving symptoms of depression and anxiety within 9 months. METHODS: A total of 323 participants with mild to moderately severe depression or anxiety were enrolled in a 12-week digital cognitive behavior therapy program. The analysis was restricted to participants who provided at least one follow-up assessment after baseline. As a result, 146 participants (45.2%) were included in the analysis-74 (50.7%) participants completed assessments at 3 months, 31 participants (21.2%) completed assessments at 6 months, and 21 participants (14.4%) completed assessments at 9 months. The program included structured lessons and tools (ie, exercises and practices) as well as one-on-one weekly video counseling sessions with a licensed therapist for 12 weeks and monthly check-in sessions for 1 year. The clinically validated Patient Health Questionnaire (PHQ-8) and Generalized Anxiety Disorder Scale (GAD-7) were used to assess depression and anxiety, respectively. Linear mixed-effects modeling was employed to examine changes in depression and anxiety over time. RESULTS: We observed a significant positive effect of program time on improvement in depression (β=-0.12, P<.001) and anxiety scores (β=-0.10, P<.001). At the end of the 12-week intervention, we observed an average reduction of 3.76 points (95% CI -4.76 to -2.76) in PHQ-8 scores. Further reductions in depression were seen at program month 6 (4.75-point reduction, 95% CI -6.61 to -2.88) and program month 9 (6.42-point reduction, 95% CI -8.66 to -6.55, P<.001). A similar pattern of improvement emerged for anxiety, with a 3.17-point reduction at the end of the 12-week intervention (95% CI -4.21 to -2.13). These improvements were maintained at program month 6 (4.87-point reduction, 95% CI -6.85 to -2.87) and program month 9 (5.19-point, 95% -6.85 to 4.81). In addition, greater program engagement during the first 12 weeks predicted a greater reduction in depression (β=-0.29, P<.001). CONCLUSIONS: The results suggest that digital interventions can support sustained and clinically meaningful improvements in depression and anxiety. Furthermore, it appears that strong initial digital mental health intervention engagement may facilitate this effect. However, the study was limited by postintervention participant attrition as well as the retrospective observational study design.
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CBT-DHI programmes often require consistent use, and high attrition rates have limited their efficacy in research.
“CBT-DHI programmes often require consistent use, and high attrition rates have limited their efficacy in research.47”
From Mixed-methods feasibility outcomes for a novel ACT-based video game ‘ACTing Minds’ to support mental health (2024) · cites this paper as [47]
The Results (Engagement) associate greater program engagement with greater improvement, and the Introduction and Discussion (Limitations) describe attrition as a continuing challenge. However, the paper says attrition limits the study and leaves overall effectiveness uncertain; it does not establish that high attrition has reduced the programmes’ efficacy. (LLM, conf=0.84)
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SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2020) · Nature Methods · doi:10.1038/s41592-019-0686-2 · Cited by 38,430 · see citing works
Kessler, R. C., Chiu, W. T., Demler, O., & Walters, E. E. (2005) · Archives of General Psychiatry · doi:10.1001/archpsyc.62.6.617 · Cited by 12,052 · see citing works
SciPy 1.0: fundamental algorithms for scientific computing in Python
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al. (2019) · Apollo - University of Cambridge Repository · doi:10.17863/cam.64134 · Cited by 10,460 · see citing works
Statsmodels: Econometric and Statistical Modeling with Python
Seabold, S., & Perktold, J. (2010) · Proceedings of the Python in Science Conferences · doi:10.25080/majora-92bf1922-011 · Cited by 6,673 · see citing works
Whiteford, H. A., Degenhardt, L., Rehm, J., Baxter, A. J., Ferrari, A. J., Erskine, H. E., Charlson, F. J., Norman, R. E., Flaxman, A. D., Johns, N., et al. (2013) · The Lancet · doi:10.1016/s0140-6736(13)61611-6 · Cited by 6,006 · see citing works
The PHQ-8 as a measure of current depression in the general population
Kroenke, K., Strine, T. W., Spitzer, R. L., Williams, J. B. W., Berry, J. T., & Mokdad, A. H. (2009) · Journal of Affective Disorders · doi:10.1016/j.jad.2008.06.026 · Cited by 5,121 · see citing works
The Prevalence of Comorbid Depression in Adults With Diabetes
Anderson, R. J., Freedland, K. E., Clouse, R. E., & Lustman, P. J. (2001) · Diabetes Care · doi:10.2337/diacare.24.6.1069 · Cited by 3,926 · see citing works
Clement, S., Schauman, O., Graham, T., Maggioni, F., Evans-Lacko, S., Bezborodovs, N., Morgan, C., Rüsch, N., Brown, J. S. L., & Thornicroft, G. (2015) · Psychological Medicine · doi:10.1017/s0033291714000129 · Cited by 3,152 · see citing works
Internet-based cognitive behaviour therapy for symptoms of depression and anxiety: A meta-analysis
SPEK, V., CUIJPERS, P., NYKLÍČEK, I., RIPER, H., KEYZER, J., & POP, V. (2007) · Psychological Medicine · doi:10.1017/s0033291706008944 · Cited by 1,586 · see citing works
Computer-based psychological treatments for depression: A systematic review and meta-analysis
Richards, D., & Richardson, T. (2012) · Clinical Psychology Review · doi:10.1016/j.cpr.2012.02.004 · Cited by 1,442 · see citing works
Andrews, G., Cuijpers, P., Craske, M. G., McEvoy, P., & Titov, N. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013196 · Cited by 1,311 · see citing works
Carlbring, P., Andersson, G., Cuijpers, P., Riper, H., & Hedman-Lagerlöf, E. (2018) · Cognitive Behaviour Therapy · doi:10.1080/16506073.2017.1401115 · Cited by 1,232 · see citing works
Firth, J., Torous, J., Nicholas, J., Carney, R., Pratap, A., Rosenbaum, S., & Sarris, J. (2017) · World Psychiatry · doi:10.1002/wps.20472 · Cited by 1,097 · see citing works
Psychotherapy for depression in adults: A meta-analysis of comparative outcome studies.
Cuijpers, P., van Straten, A., Andersson, G., & van Oppen, P. (2008) · Journal of Consulting and Clinical Psychology · doi:10.1037/a0013075 · Cited by 1,050 · cited 1× · see citing works
“Available in all 50 states, the therapy program that is the focus of this study is based on cognitive behavior therapy, a therapeutic approach that has shown the strongest evidence for treating depression and anxiety [15,16].”
BackgroundLattie, E. G., Adkins, E. C., Winquist, N., Stiles-Shields, C., Wafford, Q. E., & Graham, A. K. (2019) · Journal of Medical Internet Research · doi:10.2196/12869 · Cited by 843 · see citing works
Firth, J., Torous, J., Nicholas, J., Carney, R., Rosenbaum, S., & Sarris, J. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.04.046 · Cited by 675 · see citing works
Fleming, T., Bavin, L., Lucassen, M., Stasiak, K., Hopkins, S., & Merry, S. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9275 · Cited by 670 · see citing works
Is cognitive–behavioral therapy more effective than other therapies?
Tolin, D. F. (2010) · Clinical Psychology Review · doi:10.1016/j.cpr.2010.05.003 · Cited by 645 · see citing works
Ebert, D. D., Zarski, A.-C., Christensen, H., Stikkelbroek, Y., Cuijpers, P., Berking, M., & Riper, H. (2015) · PLOS ONE · doi:10.1371/journal.pone.0119895 · Cited by 533 · see citing works
Computer‐Aided Psychotherapy for Anxiety Disorders: A Meta‐Analytic Review
Cuijpers, P., Marks, I. M., van Straten, A., Cavanagh, K., Gega, L., & Andersson, G. (2009) · Cognitive Behaviour Therapy · doi:10.1080/16506070802694776 · Cited by 429 · see citing works
Rutter, L. A., & Brown, T. A. (2017) · Journal of Psychopathology and Behavioral Assessment · doi:10.1007/s10862-016-9571-9 · Cited by 402 · see citing works
Carolan, S., Harris, P. R., & Cavanagh, K. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7583 · Cited by 385 · cited 1× · see citing works
“Carolan et al [28] observed that a cognitive behavior therapy–based occupational program was no more effective than interventions that utilized other therapeutic approaches; they hypothesized that cognitive behavior therapy–based digital programs are not designed for delivery in occupational settings.”
BackgroundTechnological innovations in mental healthcare: harnessing the digital revolution
Hollis, C., Morriss, R., Martin, J., Amani, S., Cotton, R., Denis, M., & Lewis, S. (2015) · British Journal of Psychiatry · doi:10.1192/bjp.bp.113.142612 · Cited by 375 · see citing works
The key principles of cognitive behavioural therapy
Fenn, K., & Byrne, M. (2013) · InnovAiT: Education and inspiration for general practice · doi:10.1177/1755738012471029 · Cited by 363 · see citing works
Copeland, M. E. (2002) · Occupational Therapy in Mental Health · doi:10.1300/j004v17n03_09 · Cited by 341 · see citing works
Reger, M. A., & Gahm, G. A. (2009) · Journal of Clinical Psychology · doi:10.1002/jclp.20536 · Cited by 234 · see citing works
Game-based digital interventions for depression therapy: a systematic review and meta-analysis
Li, J., Theng, Y.-L., & Foo, S. (2014) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2013.0481 · Cited by 219 · cited 2× · see citing works
“Li et al [10] observed a similar pattern: a larger effect size for game-based interventions for the treatment of depression that did not include therapist support than for therapist-supported interventions.”
BackgroundTuerk, P. W., Yoder, M. S., Ruggiero, K. J., Grös, D. F., & Acierno, R. E. (2010) · Journal of Traumatic Stress · doi:10.1002/jts.20494 · Cited by 209 · see citing works
Diminished effort on a progressive ratio task in both unipolar and bipolar depression
Hershenberg, R., Satterthwaite, T. D., Daldal, A., Katchmar, N., Moore, T. M., Kable, J. W., & Wolf, D. H. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.02.003 · Cited by 157 · see citing works
Richards, D., Richardson, T., Timulak, L., & McElvaney, J. (2015) · Internet Interventions · doi:10.1016/j.invent.2015.07.003 · Cited by 111 · cited 1× · see citing works
“In their meta-analytic review, Richards et al [7] observed a significant and clinically meaningful effect of internet-based interventions for the treatment of generalized anxiety disorder when compared to waitlist controls, including those with comorbid depression.”
BackgroundNaik, A. D., Hundt, N. E., Vaughan, E. M., Petersen, N. J., Zeno, D., Kunik, M. E., & Cully, J. A. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.8634 · Cited by 57 · see citing works
(2004) · PsycEXTRA Dataset · doi:10.1037/e334172004-001 · Cited by 2 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [21]Beck J.S Beck A.T Cognitive therapy: Basics and beyond. No Sirsi) i9780898628470 1995 New York Guilford press
Cited by
Sorted by citations
Engagement and retention in digital mental health interventions: a narrative review
Boucher, E. M., & Raiker, J. S. (2024) · BMC Digital Health · doi:10.1186/s44247-024-00105-9 · Cited by 201 · see citing works
Human Support in App-Based Cognitive Behavioral Therapies for Emotional Disorders: Scoping Review
Bernstein, E. E., Weingarden, H. M., Wolfe, E. C., Hall, M. D., Snorrason, Í., & Wilhelm, S. (2022) · Journal of Medical Internet Research · doi:10.2196/33307 · Cited by 55 · see citing works
Meheli, S., Sinha, C., & Kadaba, M. (2022) · JMIR Human Factors · doi:10.2196/35671 · Cited by 46 · see citing works
Duan, L., Zhang, S., Yan, Q., & Hu, X. (2025) · Psycho-Oncology · doi:10.1002/pon.70078 · Cited by 47 · see citing works
Haller, K., Becker, P., Niemeyer, H., & Boettcher, J. (2023) · Internet Interventions · doi:10.1016/j.invent.2023.100635 · Cited by 46 · see citing works
Castro, Ó., Mair, J. L., Salamanca-Sanabria, A., Alattas, A., Keller, R., Zheng, S., Jabir, A. I., Lin, X., Frese, B. F., Lim, C. S., et al. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1039171 · Cited by 42 · see citing works
Dweik, R. A., Ajaj, R., Kotb, R. E., Halabi, D. E., Sadier, N. S., Sarsour, H. H. H., & Elhadi, Y. A. M. (2024) · BMC Public Health · doi:10.1186/s12889-024-19980-y · Cited by 39 · see citing works
Fatouros, P., Tsirmpas, C., Andrikopoulos, D., Kaplow, S., Kontoangelos, K. A., & Papageorgiou, C. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01511-7 · Cited by 27 · see citing works
Practical application of digital therapeutics in people with mood disorders
Orsolini, L., Longo, G., & Volpe, U. (2023) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000906 · Cited by 18 · see citing works
Lee, M.-W., Jang, S., Shin, H. K., Choi, S., Kim, H. T., Oh, J., Kwon, J. H., Choi, Y., Kang, S., Back, I.-S., et al. (2024) · Yonsei Medical Journal · doi:10.3349/ymj.2024.0002 · Cited by 16 · see citing works
The soft-skills characteristics of Generation Z employees: A scoping review and research agenda
Visser, C., & Terblanche, N. H. D. (2025) · SA Journal of Human Resource Management · doi:10.4102/sajhrm.v23i0.2975 · Cited by 19 · see citing works
The New Emerging Treatment Choice for Major Depressive Disorders: Digital Therapeutics
Cho, C., Lee, H., & Kim, Y. (2024) · Advances in experimental medicine and biology · doi:10.1007/978-981-97-4402-2_16 · Cited by 13 · see citing works
Venkatesan, A., Forster, B., Rao, P., Miller, M., & Scahill, M. D. (2022) · JMIR Formative Research · doi:10.2196/38005 · Cited by 13 · see citing works
Stuart, R., Fischer, H. J., Leitzke, A., Becker, D., Saheba, N., & Coleman, K. J. (2022) · The Permanente Journal · doi:10.7812/tpp/21.183 · Cited by 13 · see citing works
Omylinska‐Thurston, J., Aithal, S., Liverpool, S., Clark, R. D., Moula, Z., Wood, J., Viliardos, L., Rodríguez-Dorans, E., Farish-Edwards, F., Parsons, A. S., et al. (2024) · JMIR Mental Health · doi:10.2196/55500 · Cited by 14 · see citing works
Venkatesan, A., Krymis, H., Scharff, J., & Waber, A. (2021) · JMIR Formative Research · doi:10.2196/25078 · Cited by 11 · see citing works
Langhammer, T., Hilbert, K., Praxl, B., Kirschbaum, C., Ertle, A., Asbrand, J., & Lueken, U. (2021) · Mental Health & Prevention · doi:10.1016/j.mhp.2021.200221 · Cited by 11 · see citing works
Drüge, M., Guthardt, L., Haller, E., Michalak, J., & Apolinário-Hagen, J. (2024) · Advances in Experimental Medicine and Biology · doi:10.1007/978-981-97-4402-2_11 · Cited by 11 · see citing works
Whitehead, J. C., Neeman, R., & Doniger, G. M. (2022) · JMIR Formative Research · doi:10.2196/35636 · Cited by 11 · see citing works
Diabetes Technology Meeting 2021
Xu, N. Y., Nguyen, K. T., DuBord, A. Y., Pickup, J. C., Sherr, J. L., Teymourian, H., Cengiz, E., Ginsberg, B. H., Cobelli, C., Ahn, D. T., et al. (2022) · Journal of Diabetes Science and Technology · doi:10.1177/19322968221090279 · Cited by 9 · see citing works
Garzón‐Partida, A. P., Padilla-Gómez, C. B., Martínez-Fernández, D. E., Garcı́a‐Estrada, J., Luquı́n, S., & Fernández-Quezada, D. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1595243 · Cited by 8 · see citing works
Kusumadewi, A. F., Marchira, C. R., Widyandana, D., & Wirasto, R. T. (2023) · Trends in Psychiatry and Psychotherapy · doi:10.47626/2237-6089-2023-0713 · Cited by 6 · see citing works
Adjei-Boateng, D., & Ikoh, C. L. (2025) · Cureus · doi:10.7759/cureus.85943 · Cited by 6 · see citing works
Abueva, N. A., Бузело, А. С., Wu, Y., Turniyazova, Z., Karakushev, D., & Obrenovic, B. (2025) · Psychology Research and Behavior Management · doi:10.2147/prbm.s540053 · Cited by 5 · see citing works
Gordon, T. C., Kemp, A. H., & Edwards, D. J. (2024) · BMJ Open · doi:10.1136/bmjopen-2023-080972 · Cited by 4 · see citing works
“47 One meta-analysis author suggested that DHIs may need to be complemented by existing mental health support.”
BackgroundGarzón‐Partida, A. P., Magaña-Plascencia, K., Martínez-Fernández, D. E., Garcı́a‐Estrada, J., Luquı́n, S., & Fernández-Quezada, D. (2025) · JMIR Research Protocols · doi:10.2196/71374 · Cited by 5 · see citing works
Quan, L., Wu, S., Li, K., Zhang, Y., Hou, S., Zhu, B., & Wang, W. (2025) · Digital Health · doi:10.1177/20552076251379339 · Cited by 4 · see citing works
Dimopoulou, M., Dimopoulou, A., & Gortzi, O. (2025) · Psychology International · doi:10.3390/psycholint7040087 · Cited by 4 · see citing works
Ahmadi, F. B., Dehghan, M. J., Baharvand, V., & Azizi, A. (2023) · Frontiers in Health Informatics · doi:10.30699/fhi.v12i0.410 · Cited by 6 · see citing works
Bisconti, N., Odier, M., Becker, M. A., & Bullock, K. D. (2024) · JMIR Mental Health · doi:10.2196/52369 · Cited by 4 · see citing works
An, P. H. (2023) · iRASD Journal of Management · doi:10.52131/jom.2023.0504.0119 · Cited by 3 · see citing works
Agyemang, G. K., Lamina, Y., Adeyeye, Y. I., Musongong, J. A., Ajayi, J. E., Awotipe, T., Bakare, O. I., & Kyeremeh, N. (2023) · International Journal of Scientific Research in Science and Technology · doi:10.32628/ijsrst23121165 · Cited by 4 · see citing works
Designing and Evaluating Digital Mental Health Interventions: Scoping Review
Mbawa, S. Z., de Vries, R. A. J., Siebert, L. C., van Turnhout, K., & Brinkman, W. (2026) · JMIR Mental Health · doi:10.2196/77038 · Cited by 2 · see citing works
Heinz, M. V., Lekkas, D., Abreu, V., Lee, C. M., Marsch, L. A., & Jacobson, N. C. (2024) · npj Mental Health Research · doi:10.1038/s44184-024-00086-7 · Cited by 2 · see citing works
Blockchain-Based IoT Computing Services in Medical Healthcare Solutions
Arunachalam, M., Sidharth, P., Nair, S. S., Rajiv, N., Babu, R. T. S., & Sanjay, T. (2024) · Advances in civil and industrial engineering book series · doi:10.4018/979-8-3693-8568-5.ch008 · Cited by 2 · see citing works
Digital therapeutics in depression and bipolar disorder: a comprehensive systematic review
Orsolini, L., Longo, G., Nuzzo, G. L., & Volpe, U. (2025) · Minerva Psychiatry · doi:10.23736/s2724-6612.25.02637-5 · Cited by 1 · see citing works
Iqbal, I., Afna, M., & Sari, R. (2020) · DINAMIKA ILMU · doi:10.21093/di.v20i2.2512 · Cited by 1 · see citing works
Kroll, D. S. (2022) · Springer eBooks · doi:10.1007/978-3-031-08495-9_5
Hu, F., Guo, L., Luo, Z., & Zeng, M. (2026) · Psycho-Oncologie · doi:10.18282/po4119
An app responding to behavior of people to promote mental wellbeing in anxious youth
Hagalwadi, J., Sutherland, D., Dölek, S., Marin-Dragu, S., Bagnell, A. L., Wozney, L., Orji, R., & Sandra, M. (2026) · Journal of Affective Disorders · doi:10.1016/j.jad.2026.121503
Rigas, C., Lavín, P., Su, C., Hassan, M., Cinalioglu, K., Vacaflor, B., Dikaios, E., Goodman, A., Ibrahim, M., Gruber, J., et al. (2026) · BMC Psychiatry · doi:10.1186/s12888-025-07688-1
Pilarek, M., Laskowska, W., Kwolek, K., Bigajski, H., Banaś, A., Dacyl, H., Janczarski, S., Michalik, M., Sarna, D., & Widera, P. (2026) · International Journal of Innovative Technologies in Social Science · doi:10.31435/ijitss.1(49).2026.5164
Enhancing Urban Wellbeing Through Digital Innovation: A Community-Based Mental Health Platform
Rani, A. A., Pertiwi, C. M., & Ferdianto (2026) · International Conference on ICT for Smart Society (ICISS) · doi:10.1109/iciss71466.2026.11715212
Cognitive Behavioral Therapy and Mindfulness in Chronic Low Back Pain
Rai, A., & Kumar, V. (2026) · Springer eBooks · doi:10.1007/978-981-97-4087-1_56-1
Suranata, K., Apriliana, I. P. A., Bakar, A. Y. A., Suwendra, I. W., Darmawan, G. E. B., & Ifdil (2026) · SAGE Open · doi:10.1177/21582440261461208
- Authors
- Venkatesan, A., Rahimi, L., Kaur, M., & Mosunic, C.
- Corresponding author
- Venkatesan, Aarathi
- Venue
- JMIR Mental Health
- Publisher
- JMIR Publications Inc.
- Published
- 2020-08-26
- Volume
- 7
- Issue
- 8
- Pages
- e21304
- ISSN
- 2368-7959 (ISSN-L)
- PMC
- PMC7481876
- OpenAlex
- W3046189340
- Cited by
- 47
- References
- 32
- Citations by year
- 2026: 8 · 2025: 11 · 2024: 10 · 2023: 7 · 2022: 8 · 2021: 2 · 2020: 1
- FWCI
- 4.07
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Mental Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
- Keywords
- depression, anxiety, mental health apps, video counseling, PHQ-8, GAD-7, symptom improvement over time, digital mental health interventions, barriers to mental health care
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